1 | // Copyright (C) 2002, International Business Machines |
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2 | // Corporation and others. All Rights Reserved. |
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3 | #if defined(_MSC_VER) |
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4 | // Turn off compiler warning about long names |
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5 | # pragma warning(disable:4786) |
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6 | #endif |
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7 | #include <string> |
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8 | //#define CBC_DEBUG 1 |
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9 | //#define CHECK_CUT_COUNTS |
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10 | //#define CHECK_NODE_FULL |
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11 | #include <cassert> |
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12 | #include <cmath> |
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13 | #include <cfloat> |
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14 | |
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15 | #include "OsiSolverInterface.hpp" |
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16 | #include "CoinWarmStartBasis.hpp" |
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17 | #include "CoinPackedMatrix.hpp" |
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18 | #include "CbcBranchActual.hpp" |
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19 | #include "CbcHeuristic.hpp" |
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20 | #include "CbcModel.hpp" |
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21 | #include "CbcMessage.hpp" |
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22 | #include "OsiRowCut.hpp" |
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23 | #include "OsiColCut.hpp" |
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24 | #include "OsiRowCutDebugger.hpp" |
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25 | #include "OsiCuts.hpp" |
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26 | #include "CbcCountRowCut.hpp" |
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27 | #include "CbcCutGenerator.hpp" |
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28 | // include Probing |
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29 | #include "CglProbing.hpp" |
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30 | |
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31 | #define COIN_USE_CLP |
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32 | #ifdef COIN_USE_CLP |
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33 | // include Presolve from Clp |
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34 | #include "ClpPresolve.hpp" |
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35 | // Temporary |
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36 | #include "OsiClpSolverInterface.hpp" |
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37 | #endif |
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38 | |
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39 | #include "CoinTime.hpp" |
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40 | |
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41 | #include "CbcCompareActual.hpp" |
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42 | #include "CbcTree.hpp" |
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43 | /* Various functions local to CbcModel.cpp */ |
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44 | |
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45 | namespace { |
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46 | |
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47 | //------------------------------------------------------------------- |
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48 | // Returns the greatest common denominator of two |
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49 | // positive integers, a and b, found using Euclid's algorithm |
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50 | //------------------------------------------------------------------- |
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51 | static int gcd(int a, int b) |
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52 | { |
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53 | int remainder = -1; |
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54 | // make sure a<=b (will always remain so) |
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55 | if(a > b) { |
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56 | // Swap a and b |
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57 | int temp = a; |
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58 | a = b; |
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59 | b = temp; |
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60 | } |
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61 | // if zero then gcd is nonzero (zero may occur in rhs of packed) |
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62 | if (!a) { |
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63 | if (b) { |
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64 | return b; |
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65 | } else { |
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66 | printf("**** gcd given two zeros!!\n"); |
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67 | abort(); |
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68 | } |
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69 | } |
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70 | while (remainder) { |
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71 | remainder = b % a; |
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72 | b = a; |
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73 | a = remainder; |
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74 | } |
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75 | return b; |
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76 | } |
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77 | |
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78 | |
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79 | |
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80 | #ifdef CHECK_NODE_FULL |
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81 | |
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82 | /* |
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83 | Routine to verify that tree linkage is correct. The invariant that is tested |
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84 | is |
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85 | |
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86 | reference count = (number of actual references) + (number of branches left) |
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87 | |
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88 | The routine builds a set of paired arrays, info and count, by traversing the |
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89 | tree. Each CbcNodeInfo is recorded in info, and the number of times it is |
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90 | referenced (via the parent field) is recorded in count. Then a final check is |
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91 | made to see if the numberPointingToThis_ field agrees. |
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92 | */ |
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93 | |
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94 | void verifyTreeNodes (const CbcTree * branchingTree, const CbcModel &model) |
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95 | |
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96 | { printf("*** CHECKING tree after %d nodes\n",model.getNodeCount()) ; |
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97 | |
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98 | int j ; |
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99 | int nNodes = branchingTree->size() ; |
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100 | # define MAXINFO 1000 |
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101 | int *count = new int [MAXINFO] ; |
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102 | CbcNodeInfo **info = new CbcNodeInfo*[MAXINFO] ; |
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103 | int nInfo = 0 ; |
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104 | /* |
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105 | Collect all CbcNodeInfo objects in info, by starting from each live node and |
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106 | traversing back to the root. Nodes in the live set should have unexplored |
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107 | branches remaining. |
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108 | |
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109 | TODO: The `while (nodeInfo)' loop could be made to break on reaching a |
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110 | common ancester (nodeInfo is found in info[k]). Alternatively, the |
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111 | check could change to signal an error if nodeInfo is not found above a |
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112 | common ancestor. |
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113 | */ |
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114 | for (j = 0 ; j < nNodes ; j++) |
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115 | { CbcNode *node = branchingTree->nodePointer(j) ; |
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116 | CbcNodeInfo *nodeInfo = node->nodeInfo() ; |
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117 | int change = node->nodeInfo()->numberBranchesLeft() ; |
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118 | assert(change) ; |
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119 | while (nodeInfo) |
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120 | { int k ; |
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121 | for (k = 0 ; k < nInfo ; k++) |
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122 | { if (nodeInfo == info[k]) break ; } |
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123 | if (k == nInfo) |
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124 | { assert(nInfo < MAXINFO) ; |
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125 | nInfo++ ; |
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126 | info[k] = nodeInfo ; |
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127 | count[k] = 0 ; } |
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128 | nodeInfo = nodeInfo->parent() ; } } |
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129 | /* |
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130 | Walk the info array. For each nodeInfo, look up its parent in info and |
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131 | increment the corresponding count. |
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132 | */ |
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133 | for (j = 0 ; j < nInfo ; j++) |
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134 | { CbcNodeInfo *nodeInfo = info[j] ; |
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135 | nodeInfo = nodeInfo->parent() ; |
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136 | if (nodeInfo) |
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137 | { int k ; |
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138 | for (k = 0 ; k < nInfo ; k++) |
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139 | { if (nodeInfo == info[k]) break ; } |
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140 | assert (k < nInfo) ; |
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141 | count[k]++ ; } } |
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142 | /* |
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143 | Walk the info array one more time and check that the invariant holds. The |
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144 | number of references (numberPointingToThis()) should equal the sum of the |
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145 | number of actual references (held in count[]) plus the number of potential |
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146 | references (unexplored branches, numberBranchesLeft()). |
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147 | */ |
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148 | for (j = 0;j < nInfo;j++) { |
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149 | CbcNodeInfo * nodeInfo = info[j] ; |
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150 | if (nodeInfo) { |
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151 | int k ; |
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152 | for (k = 0;k < nInfo;k++) |
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153 | if (nodeInfo == info[k]) |
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154 | break ; |
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155 | printf("Nodeinfo %x - %d left, %d count\n", |
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156 | nodeInfo, |
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157 | nodeInfo->numberBranchesLeft(), |
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158 | nodeInfo->numberPointingToThis()) ; |
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159 | assert(nodeInfo->numberPointingToThis() == |
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160 | count[k]+nodeInfo->numberBranchesLeft()) ; } } |
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161 | |
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162 | delete [] count ; |
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163 | delete [] info ; |
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164 | |
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165 | return ; } |
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166 | |
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167 | #endif /* CHECK_NODE_FULL */ |
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168 | |
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169 | |
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170 | |
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171 | #ifdef CHECK_CUT_COUNTS |
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172 | |
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173 | /* |
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174 | Routine to verify that cut reference counts are correct. |
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175 | */ |
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176 | void verifyCutCounts (const CbcTree * branchingTree, CbcModel &model) |
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177 | |
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178 | { printf("*** CHECKING cuts after %d nodes\n",model.getNodeCount()) ; |
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179 | |
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180 | int j ; |
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181 | int nNodes = branchingTree->size() ; |
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182 | |
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183 | /* |
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184 | cut.tempNumber_ exists for the purpose of doing this verification. Clear it |
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185 | in all cuts. We traverse the tree by starting from each live node and working |
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186 | back to the root. At each CbcNodeInfo, check for cuts. |
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187 | */ |
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188 | for (j = 0 ; j < nNodes ; j++) |
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189 | { CbcNode *node = branchingTree->nodePointer(j) ; |
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190 | CbcNodeInfo * nodeInfo = node->nodeInfo() ; |
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191 | assert (node->nodeInfo()->numberBranchesLeft()) ; |
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192 | while (nodeInfo) |
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193 | { int k ; |
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194 | for (k = 0 ; k < nodeInfo->numberCuts() ; k++) |
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195 | { CbcCountRowCut *cut = nodeInfo->cuts()[k] ; |
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196 | if (cut) cut->tempNumber_ = 0; } |
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197 | nodeInfo = nodeInfo->parent() ; } } |
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198 | /* |
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199 | Walk the live set again, this time collecting the list of cuts in use at each |
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200 | node. addCuts1 will collect the cuts in model.addedCuts_. Take into account |
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201 | that when we recreate the basis for a node, we compress out the slack cuts. |
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202 | */ |
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203 | for (j = 0 ; j < nNodes ; j++) |
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204 | { CoinWarmStartBasis *debugws = model.getEmptyBasis() ; |
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205 | CbcNode *node = branchingTree->nodePointer(j) ; |
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206 | CbcNodeInfo *nodeInfo = node->nodeInfo(); |
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207 | int change = node->nodeInfo()->numberBranchesLeft() ; |
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208 | printf("Node %d %x (info %x) var %d way %d obj %g",j,node, |
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209 | node->nodeInfo(),node->variable(),node->way(), |
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210 | node->objectiveValue()) ; |
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211 | |
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212 | model.addCuts1(node,debugws) ; |
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213 | |
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214 | int i ; |
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215 | int numberRowsAtContinuous = model.numberRowsAtContinuous() ; |
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216 | CbcCountRowCut **addedCuts = model.addedCuts() ; |
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217 | for (i = 0 ; i < model.currentNumberCuts() ; i++) |
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218 | { CoinWarmStartBasis::Status status = |
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219 | debugws->getArtifStatus(i+numberRowsAtContinuous) ; |
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220 | if (status != CoinWarmStartBasis::basic && addedCuts[i]) |
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221 | { addedCuts[i]->tempNumber_ += change ; } } |
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222 | |
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223 | while (nodeInfo) |
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224 | { nodeInfo = nodeInfo->parent() ; |
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225 | if (nodeInfo) printf(" -> %x",nodeInfo); } |
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226 | printf("\n") ; |
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227 | delete debugws ; } |
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228 | /* |
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229 | The moment of truth: We've tallied up the references by direct scan of the |
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230 | search tree. Check for agreement with the count in the cut. |
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231 | |
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232 | TODO: Rewrite to check and print mismatch only when tempNumber_ == 0? |
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233 | */ |
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234 | for (j = 0 ; j < nNodes ; j++) |
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235 | { CbcNode *node = branchingTree->nodePointer(j) ; |
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236 | CbcNodeInfo *nodeInfo = node->nodeInfo(); |
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237 | while (nodeInfo) |
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238 | { int k ; |
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239 | for (k = 0 ; k < nodeInfo->numberCuts() ; k++) |
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240 | { CbcCountRowCut *cut = nodeInfo->cuts()[k] ; |
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241 | if (cut && cut->tempNumber_ >= 0) |
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242 | { if (cut->tempNumber_ != cut->numberPointingToThis()) |
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243 | printf("mismatch %x %d %x %d %d\n",nodeInfo,k, |
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244 | cut,cut->tempNumber_,cut->numberPointingToThis()) ; |
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245 | else |
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246 | printf(" match %x %d %x %d %d\n", nodeInfo,k, |
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247 | cut,cut->tempNumber_,cut->numberPointingToThis()) ; |
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248 | cut->tempNumber_ = -1 ; } } |
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249 | nodeInfo = nodeInfo->parent() ; } } |
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250 | |
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251 | return ; } |
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252 | |
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253 | #endif /* CHECK_CUT_COUNTS */ |
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254 | |
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255 | } |
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256 | |
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257 | /* End unnamed namespace for CbcModel.cpp */ |
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258 | |
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259 | |
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260 | |
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261 | void |
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262 | CbcModel::analyzeObjective () |
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263 | /* |
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264 | Try to find a minimum change in the objective function. The first scan |
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265 | checks that there are no continuous variables with non-zero coefficients, |
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266 | and grabs the largest objective coefficient associated with an unfixed |
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267 | integer variable. The second scan attempts to scale up the objective |
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268 | coefficients to a point where they are sufficiently close to integer that |
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269 | we can pretend they are integer, and calculate a gcd over the coefficients |
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270 | of interest. This will be the minimum increment for the scaled coefficients. |
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271 | The final action is to scale the increment back for the original coefficients |
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272 | and install it, if it's better than the existing value. |
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273 | |
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274 | John's note: We could do better than this. |
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275 | |
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276 | John's second note - apologies for changing s to z |
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277 | */ |
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278 | { const double *objective = getObjCoefficients() ; |
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279 | const double *lower = getColLower() ; |
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280 | const double *upper = getColUpper() ; |
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281 | /* |
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282 | Take a first scan to see if there are unfixed continuous variables in the |
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283 | objective. If so, the minimum objective change could be arbitrarily small. |
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284 | Also pick off the maximum coefficient of an unfixed integer variable. |
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285 | |
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286 | If the objective is found to contain only integer variables, set the |
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287 | fathoming discipline to strict. |
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288 | */ |
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289 | double maximumCost = 0.0 ; |
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290 | bool possibleMultiple = true ; |
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291 | int iColumn ; |
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292 | int numberColumns = getNumCols() ; |
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293 | for (iColumn = 0 ; iColumn < numberColumns ; iColumn++) |
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294 | { if (upper[iColumn] > lower[iColumn]+1.0e-8) |
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295 | { if (isInteger(iColumn)) |
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296 | maximumCost = CoinMax(maximumCost,fabs(objective[iColumn])) ; |
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297 | else if (objective[iColumn]) |
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298 | possibleMultiple = false ; } } |
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299 | setIntParam(CbcModel::CbcFathomDiscipline,possibleMultiple) ; |
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300 | /* |
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301 | If a nontrivial increment is possible, try and figure it out. We're looking |
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302 | for gcd(c<j>) for all c<j> that are coefficients of unfixed integer |
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303 | variables. Since the c<j> might not be integers, try and inflate them |
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304 | sufficiently that they look like integers (and we'll deflate the gcd |
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305 | later). |
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306 | |
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307 | 2520.0 is used as it is a nice multiple of 2,3,5,7 |
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308 | */ |
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309 | if (possibleMultiple&&maximumCost) |
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310 | { int increment = 0 ; |
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311 | double multiplier = 2520.0 ; |
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312 | while (10.0*multiplier*maximumCost < 1.0e8) |
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313 | multiplier *= 10.0 ; |
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314 | |
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315 | for (iColumn = 0 ; iColumn < numberColumns ; iColumn++) |
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316 | { if (upper[iColumn] > lower[iColumn]+1.0e-8) |
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317 | { if (isInteger(iColumn)&&objective[iColumn]) |
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318 | { double value = fabs(objective[iColumn])*multiplier ; |
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319 | int nearest = (int) floor(value+0.5) ; |
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320 | if (fabs(value-floor(value+0.5)) > 1.0e-8) |
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321 | { increment = 0 ; |
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322 | break ; } |
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323 | else if (!increment) |
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324 | { increment = nearest ; } |
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325 | else |
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326 | { increment = gcd(increment,nearest) ; } } } } |
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327 | /* |
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328 | If the increment beats the current value for objective change, install it. |
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329 | */ |
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330 | if (increment) |
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331 | { double value = increment ; |
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332 | double cutoff = getDblParam(CbcModel::CbcCutoffIncrement) ; |
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333 | value /= multiplier ; |
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334 | if (value*0.999 > cutoff) |
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335 | { messageHandler()->message(CBC_INTEGERINCREMENT, |
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336 | messages()) |
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337 | << value << CoinMessageEol ; |
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338 | setDblParam(CbcModel::CbcCutoffIncrement,value*0.999) ; } } } |
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339 | |
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340 | return ; |
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341 | } |
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342 | |
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343 | |
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344 | |
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345 | /** |
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346 | \todo |
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347 | Normally, it looks like we enter here from command dispatch in the main |
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348 | routine, after calling the solver for an initial solution |
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349 | (CbcModel::initialSolve, which simply calls the solver's initialSolve |
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350 | routine.) The first thing we do is call resolve. Presumably there are |
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351 | circumstances where this is nontrivial? There's also a call from |
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352 | CbcModel::originalModel (tied up with integer presolve), which should be |
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353 | checked. |
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354 | |
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355 | */ |
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356 | |
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357 | /* |
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358 | The overall flow can be divided into three stages: |
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359 | * Prep: Check that the lp relaxation remains feasible at the root. If so, |
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360 | do all the setup for B&C. |
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361 | * Process the root node: Generate cuts, apply heuristics, and in general do |
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362 | the best we can to resolve the problem without B&C. |
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363 | * Do B&C search until we hit a limit or exhaust the search tree. |
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364 | |
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365 | Keep in mind that in general there is no node in the search tree that |
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366 | corresponds to the active subproblem. The active subproblem is represented |
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367 | by the current state of the model, of the solver, and of the constraint |
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368 | system held by the solver. |
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369 | */ |
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370 | |
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371 | void CbcModel::branchAndBound() |
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372 | |
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373 | { |
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374 | # ifdef CBC_DEBUG |
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375 | std::string problemName ; |
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376 | solver_->getStrParam(OsiProbName,problemName) ; |
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377 | printf("Problem name - %s\n",problemName.c_str()) ; |
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378 | solver_->setHintParam(OsiDoReducePrint,false,OsiHintDo,0) ; |
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379 | # endif |
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380 | /* |
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381 | Assume we're done, and see if we're proven wrong. |
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382 | */ |
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383 | status_ = 0 ; |
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384 | phase_=0; |
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385 | /* |
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386 | Scan the variables, noting the integer variables. Create an |
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387 | CbcSimpleInteger object for each integer variable. |
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388 | */ |
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389 | findIntegers(false) ; |
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390 | /* |
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391 | Ensure that objects on the lists of CbcObjects, heuristics, and cut |
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392 | generators attached to this model all refer to this model. |
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393 | */ |
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394 | synchronizeModel() ; |
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395 | /* |
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396 | Capture a time stamp before we start. |
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397 | */ |
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398 | dblParam_[CbcStartSeconds] = CoinCpuTime(); |
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399 | // Set so we can tell we are in initial phase in resolve |
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400 | continuousObjective_ = -COIN_DBL_MAX ; |
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401 | /* |
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402 | Solve the relaxation. |
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403 | |
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404 | Apparently there are circumstances where this will be non-trivial --- i.e., |
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405 | we've done something since initialSolve that's trashed the solution to the |
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406 | continuous relaxation. |
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407 | */ |
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408 | bool feasible = resolve() ; |
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409 | /* |
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410 | If the linear relaxation of the root is infeasible, bail out now. Otherwise, |
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411 | continue with processing the root node. |
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412 | */ |
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413 | if (!feasible) |
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414 | { handler_->message(CBC_INFEAS,messages_)<< CoinMessageEol ; |
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415 | status_ = 0 ; |
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416 | originalContinuousObjective_ = COIN_DBL_MAX; |
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417 | return ; } |
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418 | // Save objective (just so user can access it) |
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419 | originalContinuousObjective_ = solver_->getObjValue(); |
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420 | |
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421 | # ifdef CBC_DEBUG |
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422 | /* |
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423 | OsiRowCutDebugger knows an optimal answer for a subset of MIP problems. |
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424 | Assuming it recognises the problem, when called upon it will check a cut to |
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425 | see if it cuts off the optimal answer. |
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426 | */ |
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427 | solver_->activateRowCutDebugger(problemName.c_str()) ; |
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428 | # endif |
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429 | |
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430 | /* |
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431 | Begin setup to process a feasible root node. |
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432 | */ |
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433 | bestObjective_ = CoinMin(bestObjective_,1.0e50) ; |
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434 | numberSolutions_ = 0 ; |
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435 | numberHeuristicSolutions_ = 0 ; |
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436 | // Everything is minimization |
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437 | double cutoff=getCutoff() ; |
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438 | double direction = solver_->getObjSense() ; |
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439 | if (cutoff < 1.0e20&&direction<0.0) |
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440 | messageHandler()->message(CBC_CUTOFF_WARNING1, |
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441 | messages()) |
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442 | << cutoff << -cutoff << CoinMessageEol ; |
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443 | if (cutoff > bestObjective_) |
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444 | cutoff = bestObjective_ ; |
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445 | setCutoff(cutoff) ; |
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446 | /* |
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447 | We probably already have a current solution, but just in case ... |
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448 | */ |
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449 | int numberColumns = getNumCols() ; |
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450 | if (!currentSolution_) |
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451 | currentSolution_ = new double[numberColumns] ; |
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452 | /* |
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453 | Create a copy of the solver, thus capturing the original (root node) |
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454 | constraint system (aka the continuous system). |
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455 | */ |
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456 | continuousSolver_ = solver_->clone() ; |
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457 | numberRowsAtContinuous_ = getNumRows() ; |
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458 | /* |
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459 | Check the objective to see if we can deduce a nontrivial increment. If |
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460 | it's better than the current value for CbcCutoffIncrement, it'll be |
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461 | installed. |
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462 | */ |
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463 | analyzeObjective() ; |
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464 | /* |
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465 | Set up for cut generation. addedCuts_ holds the cuts which are relevant for |
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466 | the active subproblem. whichGenerator will be used to record the generator |
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467 | that produced a given cut. |
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468 | */ |
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469 | int maximumWhich = 1000 ; |
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470 | int * whichGenerator = new int[maximumWhich] ; |
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471 | int currentNumberCuts = 0 ; |
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472 | maximumNumberCuts_ = 0 ; |
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473 | currentNumberCuts_ = 0 ; |
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474 | delete [] addedCuts_ ; |
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475 | addedCuts_ = NULL ; |
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476 | /* |
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477 | Set up an empty heap and associated data structures to hold the live set |
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478 | (problems which require further exploration). |
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479 | */ |
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480 | CbcCompareObjective compareObjective ; |
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481 | CbcCompareDepth compareDepth ; |
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482 | CbcCompareDefault compareDefault(dblParam_[CbcInfeasibilityWeight]) ; |
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483 | if (!nodeCompare_) |
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484 | tree_->setComparison(compareDepth) ; |
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485 | else |
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486 | tree_->setComparison(*nodeCompare_) ; |
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487 | /* |
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488 | Used to record the path from a node to the root of the search tree, so that |
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489 | we can then traverse from the root to the node when restoring a subproblem. |
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490 | */ |
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491 | maximumDepth_ = 10 ; |
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492 | delete [] walkback_ ; |
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493 | walkback_ = new CbcNodeInfo * [maximumDepth_] ; |
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494 | /* |
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495 | Used to generate bound edits for CbcPartialNodeInfo. |
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496 | */ |
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497 | double * lowerBefore = new double [numberColumns] ; |
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498 | double * upperBefore = new double [numberColumns] ; |
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499 | /* |
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500 | |
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501 | Generate cuts at the root node and reoptimise. solveWithCuts does the heavy |
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502 | lifting. It will iterate a generate/reoptimise loop (including reduced cost |
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503 | fixing) until no cuts are generated, the change in objective falls off, or |
---|
504 | the limit on the number of rounds of cut generation is exceeded. |
---|
505 | |
---|
506 | At the end of all this, any cuts will be recorded in cuts and also |
---|
507 | installed in the solver's constraint system. We'll have reoptimised, and |
---|
508 | removed any slack cuts (numberOldActiveCuts and numberNewCuts have been |
---|
509 | adjusted accordingly). |
---|
510 | |
---|
511 | Tell cut generators they can be a bit more aggressive at root node |
---|
512 | |
---|
513 | TODO: Why don't we make a copy of the solution after solveWithCuts? |
---|
514 | TODO: If numberUnsatisfied == 0, don't we have a solution? |
---|
515 | */ |
---|
516 | phase_=1; |
---|
517 | int iCutGenerator; |
---|
518 | for (iCutGenerator = 0;iCutGenerator<numberCutGenerators_;iCutGenerator++) { |
---|
519 | CglCutGenerator * generator = generator_[iCutGenerator]->generator(); |
---|
520 | generator->setAggressiveness(generator->getAggressiveness()+100); |
---|
521 | } |
---|
522 | OsiCuts cuts ; |
---|
523 | int anyAction = -1 ; |
---|
524 | int numberOldActiveCuts = 0 ; |
---|
525 | int numberNewCuts = 0 ; |
---|
526 | { int iObject ; |
---|
527 | int preferredWay ; |
---|
528 | int numberUnsatisfied = 0 ; |
---|
529 | double integerTolerance = getIntegerTolerance() ; |
---|
530 | |
---|
531 | memcpy(currentSolution_,solver_->getColSolution(), |
---|
532 | numberColumns*sizeof(double)) ; |
---|
533 | |
---|
534 | for (iObject = 0 ; iObject < numberObjects_ ; iObject++) |
---|
535 | { double infeasibility = |
---|
536 | object_[iObject]->infeasibility(preferredWay) ; |
---|
537 | if (infeasibility > integerTolerance) numberUnsatisfied++ ; } |
---|
538 | if (numberUnsatisfied) |
---|
539 | { feasible = solveWithCuts(cuts,maximumCutPassesAtRoot_, |
---|
540 | NULL,numberOldActiveCuts,numberNewCuts, |
---|
541 | maximumWhich, whichGenerator) ; } } |
---|
542 | // make cut generators less aggressive |
---|
543 | for (iCutGenerator = 0;iCutGenerator<numberCutGenerators_;iCutGenerator++) { |
---|
544 | CglCutGenerator * generator = generator_[iCutGenerator]->generator(); |
---|
545 | generator->setAggressiveness(generator->getAggressiveness()-100); |
---|
546 | } |
---|
547 | currentNumberCuts_ = numberNewCuts ; |
---|
548 | /* |
---|
549 | We've taken the continuous relaxation as far as we can. Time to branch. |
---|
550 | The first order of business is to actually create a node. chooseBranch |
---|
551 | currently uses strong branching to evaluate branch object candidates, |
---|
552 | unless forced back to simple branching. If chooseBranch concludes that a |
---|
553 | branching candidate is monotone (anyAction == -1) or infeasible (anyAction |
---|
554 | == -2) when forced to integer values, it returns here immediately. |
---|
555 | |
---|
556 | Monotone variables trigger a call to resolve(). If the problem remains |
---|
557 | feasible, try again to choose a branching variable. At the end of the loop, |
---|
558 | resolved == true indicates that some variables were fixed. |
---|
559 | |
---|
560 | Loss of feasibility will result in the deletion of newNode. |
---|
561 | */ |
---|
562 | |
---|
563 | bool resolved = false ; |
---|
564 | CbcNode *newNode = NULL ; |
---|
565 | |
---|
566 | if (feasible) |
---|
567 | { newNode = new CbcNode ; |
---|
568 | newNode->setObjectiveValue(direction*solver_->getObjValue()) ; |
---|
569 | newNode->setNodeNumber(numberNodes_); |
---|
570 | anyAction = -1 ; |
---|
571 | // To make depth available we may need a fake node |
---|
572 | CbcNode fakeNode; |
---|
573 | if (!currentNode_) { |
---|
574 | // Not true if sub trees assert (!numberNodes_); |
---|
575 | currentNode_=&fakeNode; |
---|
576 | } |
---|
577 | phase_=3; |
---|
578 | while (anyAction == -1) |
---|
579 | { anyAction = newNode->chooseBranch(this,NULL) ; |
---|
580 | if (anyAction == -1) |
---|
581 | { feasible = resolve() ; |
---|
582 | resolved = true ; |
---|
583 | # ifdef CBC_DEBUG |
---|
584 | printf("Resolve (root) as something fixed, Obj value %g %d rows\n", |
---|
585 | solver_->getObjValue(), |
---|
586 | solver_->getNumRows()) ; |
---|
587 | # endif |
---|
588 | if (!feasible) anyAction = -2 ; } |
---|
589 | if (anyAction == -2||newNode->objectiveValue() >= cutoff) |
---|
590 | { delete newNode ; |
---|
591 | newNode = NULL ; |
---|
592 | feasible = false ; } } } |
---|
593 | /* |
---|
594 | At this point, the root subproblem is infeasible or fathomed by bound |
---|
595 | (newNode == NULL), or we're live with an objective value that satisfies the |
---|
596 | current objective cutoff. |
---|
597 | */ |
---|
598 | assert (!newNode || newNode->objectiveValue() <= cutoff) ; |
---|
599 | /* |
---|
600 | The common case is that the lp relaxation is feasible but doesn't satisfy |
---|
601 | integrality (i.e., newNode->variable() >= 0, indicating we've been able to |
---|
602 | select a branching variable). Remove any cuts that have gone slack due to |
---|
603 | forcing monotone variables. Then tack on an CbcFullNodeInfo object and full |
---|
604 | basis (via createInfo()) and stash the new cuts in the nodeInfo (via |
---|
605 | addCuts()). If, by some miracle, we have an integral solution at the root |
---|
606 | (newNode->variable() < 0), takeOffCuts() will ensure that the solver holds |
---|
607 | a valid solution for use by setBestSolution(). |
---|
608 | */ |
---|
609 | CoinWarmStartBasis *lastws = 0 ; |
---|
610 | if (feasible && newNode->variable() >= 0) |
---|
611 | { if (resolved) |
---|
612 | { bool needValidSolution = (newNode->variable() < 0) ; |
---|
613 | takeOffCuts(cuts,whichGenerator,numberOldActiveCuts,numberNewCuts, |
---|
614 | needValidSolution) ; |
---|
615 | # ifdef CHECK_CUT_COUNTS |
---|
616 | { printf("Number of rows after chooseBranch fix (root)" |
---|
617 | "(active only) %d\n", |
---|
618 | numberRowsAtContinuous_+numberNewCuts+numberOldActiveCuts) ; |
---|
619 | const CoinWarmStartBasis* debugws = |
---|
620 | dynamic_cast <const CoinWarmStartBasis*>(solver_->getWarmStart()) ; |
---|
621 | debugws->print() ; |
---|
622 | delete debugws ; } |
---|
623 | # endif |
---|
624 | } |
---|
625 | newNode->createInfo(this,NULL,NULL,NULL,NULL,0,0) ; |
---|
626 | newNode->nodeInfo()->addCuts(cuts, |
---|
627 | newNode->numberBranches(),whichGenerator) ; |
---|
628 | /* |
---|
629 | Courtesy of createInfo, there's now a full basis stashed in |
---|
630 | newNode->nodeInfo_->basis_. We're about to make two more copies, lastws and |
---|
631 | model.basis_. |
---|
632 | |
---|
633 | (jf) With some thought I should be able to get rid of lastws and use |
---|
634 | basis_. |
---|
635 | (lh) I agree, but haven't pursued it to the end. |
---|
636 | */ |
---|
637 | if (basis_) delete basis_ ; |
---|
638 | basis_ = dynamic_cast<CoinWarmStartBasis*>(solver_->getWarmStart()) ; |
---|
639 | if (lastws) delete lastws ; |
---|
640 | lastws = dynamic_cast<CoinWarmStartBasis*>(basis_->clone()) ; } |
---|
641 | /* |
---|
642 | Continuous data to be used later |
---|
643 | */ |
---|
644 | continuousObjective_ = 0.0 ; |
---|
645 | continuousInfeasibilities_ = 0 ; |
---|
646 | if (newNode) |
---|
647 | { continuousObjective_ = newNode->objectiveValue() ; |
---|
648 | continuousInfeasibilities_ = newNode->numberUnsatisfied() ; } |
---|
649 | /* |
---|
650 | Bound may have changed so reset in objects |
---|
651 | */ |
---|
652 | { int i ; |
---|
653 | for (i = 0;i < numberObjects_;i++) |
---|
654 | object_[i]->resetBounds() ; } |
---|
655 | /* |
---|
656 | For printing totals and for CbcNode (numberNodes_) |
---|
657 | */ |
---|
658 | numberIterations_ = 0 ; |
---|
659 | numberNodes_ = 0 ; |
---|
660 | bool stoppedOnGap = false ; |
---|
661 | /* |
---|
662 | Feasible? Then we should have either a live node prepped for future |
---|
663 | expansion (indicated by variable() >= 0), or (miracle of miracles) an |
---|
664 | integral solution at the root node. |
---|
665 | |
---|
666 | initializeInfo sets the reference counts in the nodeInfo object. Since |
---|
667 | this node is still live, push it onto the heap that holds the live set. |
---|
668 | */ |
---|
669 | double bestValue = 0.0 ; |
---|
670 | if (newNode) { |
---|
671 | bestValue = newNode->objectiveValue(); |
---|
672 | if (newNode->variable() >= 0) { |
---|
673 | newNode->initializeInfo() ; |
---|
674 | tree_->push(newNode) ; |
---|
675 | # ifdef CHECK_NODE |
---|
676 | printf("Node %x on tree\n",newNode) ; |
---|
677 | # endif |
---|
678 | } else { |
---|
679 | // continuous is integer |
---|
680 | double objectiveValue = newNode->objectiveValue(); |
---|
681 | setBestSolution(CBC_SOLUTION,objectiveValue, |
---|
682 | solver_->getColSolution()) ; |
---|
683 | delete newNode ; |
---|
684 | newNode = NULL ; |
---|
685 | } |
---|
686 | } |
---|
687 | |
---|
688 | if (printFrequency_ <= 0) { |
---|
689 | printFrequency_ = 1000 ; |
---|
690 | if (getNumCols() > 2000) |
---|
691 | printFrequency_ = 100 ; |
---|
692 | } |
---|
693 | /* Tell solver we are in Branch and Cut |
---|
694 | Could use last parameter for subtle differences */ |
---|
695 | solver_->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo,NULL) ; |
---|
696 | /* |
---|
697 | At last, the actual branch-and-cut search loop, which will iterate until |
---|
698 | the live set is empty or we hit some limit (integrality gap, time, node |
---|
699 | count, etc.). The overall flow is to rebuild a subproblem, reoptimise using |
---|
700 | solveWithCuts(), choose a branching pattern with chooseBranch(), and finally |
---|
701 | add the node to the live set. |
---|
702 | |
---|
703 | The first action is to winnow the live set to remove nodes which are worse |
---|
704 | than the current objective cutoff. |
---|
705 | */ |
---|
706 | while (!tree_->empty()) |
---|
707 | { if (cutoff > getCutoff()) { |
---|
708 | // Do from deepest |
---|
709 | tree_->cleanTree(this, getCutoff()) ; |
---|
710 | if (!nodeCompare_) { |
---|
711 | if (!compareDefault.getWeight()) { |
---|
712 | // set to get close to this |
---|
713 | double costPerInteger = |
---|
714 | (bestObjective_-continuousObjective_)/ |
---|
715 | ((double) continuousInfeasibilities_) ; |
---|
716 | compareDefault.setWeight(0.98*costPerInteger) ; |
---|
717 | /*printf("Setting weight per infeasibility to %g\n", |
---|
718 | 0.98*costPerInteger);*/ |
---|
719 | } |
---|
720 | tree_->setComparison(compareDefault) ; |
---|
721 | //tree_->setComparison(compareObjective) ; |
---|
722 | } else { |
---|
723 | nodeCompare_->newSolution(this) ; |
---|
724 | nodeCompare_->newSolution(this,continuousObjective_, |
---|
725 | continuousInfeasibilities_) ; |
---|
726 | tree_->setComparison(*nodeCompare_) ; |
---|
727 | } |
---|
728 | if (tree_->empty()) |
---|
729 | break; // finished |
---|
730 | } |
---|
731 | cutoff = getCutoff() ; |
---|
732 | /* |
---|
733 | Periodic activities: Opportunities to |
---|
734 | + tweak the nodeCompare criteria, |
---|
735 | + check if we've closed the integrality gap enough to quit, |
---|
736 | + print a summary line to let the user know we're working |
---|
737 | */ |
---|
738 | if ((numberNodes_%1000) == 0&&nodeCompare_) { |
---|
739 | bool redoTree=nodeCompare_->every1000Nodes(this, numberNodes_) ; |
---|
740 | // redo tree if wanted |
---|
741 | if (redoTree) |
---|
742 | tree_->setComparison(*nodeCompare_) ; |
---|
743 | } |
---|
744 | if ((numberNodes_%printFrequency_) == 0) { |
---|
745 | int j ; |
---|
746 | int nNodes = tree_->size() ; |
---|
747 | bestValue = 1.0e100 ; |
---|
748 | for (j = 0;j < nNodes;j++) { |
---|
749 | CbcNode * node = tree_->nodePointer(j) ; |
---|
750 | if (node->objectiveValue() < bestValue) |
---|
751 | bestValue = node->objectiveValue() ; |
---|
752 | } |
---|
753 | messageHandler()->message(CBC_STATUS,messages()) |
---|
754 | << numberNodes_<< nNodes<< bestObjective_<< bestValue |
---|
755 | << CoinMessageEol ; |
---|
756 | } |
---|
757 | // See if can stop on gap |
---|
758 | double testGap = CoinMax(dblParam_[CbcAllowableGap], |
---|
759 | CoinMax(fabs(bestObjective_),fabs(bestValue)) |
---|
760 | *dblParam_[CbcAllowableFractionGap]); |
---|
761 | if (bestObjective_-bestValue < testGap) { |
---|
762 | stoppedOnGap = true ; |
---|
763 | } |
---|
764 | |
---|
765 | # ifdef CHECK_NODE_FULL |
---|
766 | verifyTreeNodes(tree_,*this) ; |
---|
767 | # endif |
---|
768 | # ifdef CHECK_CUT_COUNTS |
---|
769 | verifyCutCounts(tree_,*this) ; |
---|
770 | # endif |
---|
771 | |
---|
772 | /* |
---|
773 | Now we come to the meat of the loop. To create the active subproblem, we'll |
---|
774 | pop the most promising node in the live set, rebuild the subproblem it |
---|
775 | represents, and then execute the current arm of the branch to create the |
---|
776 | active subproblem. |
---|
777 | */ |
---|
778 | CbcNode *node = tree_->top() ; |
---|
779 | currentNode_=node; // so can be accessed elsewhere |
---|
780 | #ifdef CBC_DEBUG |
---|
781 | printf("%d unsat, way %d, obj %g est %g\n", |
---|
782 | node->numberUnsatisfied(),node->way(),node->objectiveValue(), |
---|
783 | node->guessedObjectiveValue()); |
---|
784 | #endif |
---|
785 | tree_->pop() ; |
---|
786 | bool nodeOnTree=false; // Node has been popped |
---|
787 | |
---|
788 | # ifdef CHECK_NODE |
---|
789 | /* |
---|
790 | WARNING: The use of integerVariable_[*] here will break as soon as the |
---|
791 | branching object is something other than an integer variable. |
---|
792 | This needs some thought. |
---|
793 | */ |
---|
794 | printf("Node %x popped from tree - %d left, %d count\n",node, |
---|
795 | node->nodeInfo()->numberBranchesLeft(), |
---|
796 | node->nodeInfo()->numberPointingToThis()) ; |
---|
797 | printf("\tdepth = %d, z = %g, unsat = %d, var = %d.\n", |
---|
798 | node->depth(),node->objectiveValue(), |
---|
799 | node->numberUnsatisfied(), |
---|
800 | integerVariable_[node->variable()]) ; |
---|
801 | # endif |
---|
802 | |
---|
803 | /* |
---|
804 | Rebuild the subproblem for this node: Call addCuts() to adjust the model |
---|
805 | to recreate the subproblem for this node (set proper variable bounds, add |
---|
806 | cuts, create a basis). This may result in the problem being fathomed by |
---|
807 | bound or infeasibility. Returns 1 if node is fathomed. |
---|
808 | Execute the current arm of the branch: If the problem survives, save the |
---|
809 | resulting variable bounds and call branch() to modify variable bounds |
---|
810 | according to the current arm of the branching object. If we're processing |
---|
811 | the final arm of the branching object, flag the node for removal from the |
---|
812 | live set. |
---|
813 | */ |
---|
814 | CbcNodeInfo * nodeInfo = node->nodeInfo() ; |
---|
815 | newNode = NULL ; |
---|
816 | if (!addCuts(node,lastws)) |
---|
817 | { int i ; |
---|
818 | const double * lower = getColLower() ; |
---|
819 | const double * upper = getColUpper() ; |
---|
820 | for (i = 0 ; i < numberColumns ; i++) |
---|
821 | { lowerBefore[i]= lower[i] ; |
---|
822 | upperBefore[i]= upper[i] ; } |
---|
823 | bool deleteNode ; |
---|
824 | if (node->branch()) |
---|
825 | { tree_->push(node) ; |
---|
826 | nodeOnTree=true; // back on tree |
---|
827 | deleteNode = false ; |
---|
828 | # ifdef CHECK_NODE |
---|
829 | printf("Node %x pushed back on tree - %d left, %d count\n",node, |
---|
830 | nodeInfo->numberBranchesLeft(), |
---|
831 | nodeInfo->numberPointingToThis()) ; |
---|
832 | # endif |
---|
833 | } |
---|
834 | else |
---|
835 | { deleteNode = true ; } |
---|
836 | |
---|
837 | # ifdef CBC_DEBUG |
---|
838 | /* |
---|
839 | This doesn't work as intended --- getRowCutDebugger will return null |
---|
840 | unless the current feasible solution region includes the optimal solution |
---|
841 | that RowCutDebugger knows. There's no way to tell inactive from off the |
---|
842 | optimal path. |
---|
843 | */ |
---|
844 | const OsiRowCutDebugger *debugger = solver_->getRowCutDebugger() ; |
---|
845 | if (debugger) |
---|
846 | { if(debugger->onOptimalPath(*solver_)) |
---|
847 | printf("On optimal path\n") ; |
---|
848 | else |
---|
849 | printf("Not on optimal path\n") ; } |
---|
850 | # endif |
---|
851 | /* |
---|
852 | Reoptimize, possibly generating cuts and/or using heuristics to find |
---|
853 | solutions. Cut reference counts are unaffected unless we lose feasibility, |
---|
854 | in which case solveWithCuts() will make the adjustment. |
---|
855 | */ |
---|
856 | phase_=2; |
---|
857 | cuts = OsiCuts() ; |
---|
858 | currentNumberCuts = solver_->getNumRows()-numberRowsAtContinuous_ ; |
---|
859 | feasible = solveWithCuts(cuts,maximumCutPasses_,node, |
---|
860 | numberOldActiveCuts,numberNewCuts, |
---|
861 | maximumWhich,whichGenerator) ; |
---|
862 | /* |
---|
863 | Check for abort on limits: node count, solution count, time, integrality gap. |
---|
864 | */ |
---|
865 | double totalTime = CoinCpuTime()-dblParam_[CbcStartSeconds] ; |
---|
866 | if (numberNodes_ < intParam_[CbcMaxNumNode] && |
---|
867 | numberSolutions_ < intParam_[CbcMaxNumSol] && |
---|
868 | totalTime < dblParam_[CbcMaximumSeconds] && |
---|
869 | !stoppedOnGap) |
---|
870 | { |
---|
871 | /* |
---|
872 | Are we still feasible? If so, create a node and do the work to attach a |
---|
873 | branching object, reoptimising as needed if chooseBranch() identifies |
---|
874 | monotone objects. |
---|
875 | |
---|
876 | Finally, attach a partial nodeInfo object and store away any cuts that we |
---|
877 | created back in solveWithCuts. addCuts() will also deal with the cut |
---|
878 | reference counts. |
---|
879 | |
---|
880 | TODO: (lh) I'm confused. We create a nodeInfo without checking whether we |
---|
881 | have a solution or not. Then we use numberUnsatisfied() to decide |
---|
882 | whether to stash the cuts and bump reference counts. Other places we |
---|
883 | use variable() (i.e., presence of a branching variable). Equivalent? |
---|
884 | */ |
---|
885 | if (feasible) |
---|
886 | { newNode = new CbcNode ; |
---|
887 | newNode->setObjectiveValue(direction*solver_->getObjValue()) ; |
---|
888 | if (newNode->objectiveValue() >= getCutoff()) |
---|
889 | anyAction=-2; |
---|
890 | newNode->setNodeNumber(numberNodes_); |
---|
891 | anyAction =-1 ; |
---|
892 | resolved = false ; |
---|
893 | if (newNode->objectiveValue() >= getCutoff()) |
---|
894 | anyAction=-2; |
---|
895 | while (anyAction == -1) |
---|
896 | { anyAction = newNode->chooseBranch(this,node) ; |
---|
897 | if (anyAction == -1) |
---|
898 | { feasible = resolve() ; |
---|
899 | resolved = true ; |
---|
900 | if (feasible) |
---|
901 | { newNode->setObjectiveValue(direction* |
---|
902 | solver_->getObjValue()) ; |
---|
903 | if (newNode->objectiveValue() >= getCutoff()) |
---|
904 | anyAction=-2; |
---|
905 | } |
---|
906 | else |
---|
907 | { anyAction = -2 ; } } } |
---|
908 | if (anyAction >= 0) |
---|
909 | { if (resolved) |
---|
910 | { bool needValidSolution = (newNode->variable() < 0) ; |
---|
911 | takeOffCuts(cuts,whichGenerator,numberOldActiveCuts, |
---|
912 | numberNewCuts,needValidSolution) ; |
---|
913 | # ifdef CHECK_CUT_COUNTS |
---|
914 | { printf("Number of rows after chooseBranch fix (node)" |
---|
915 | "(active only) %d\n", |
---|
916 | numberRowsAtContinuous_+numberNewCuts+ |
---|
917 | numberOldActiveCuts) ; |
---|
918 | const CoinWarmStartBasis* debugws = |
---|
919 | dynamic_cast<const CoinWarmStartBasis*> |
---|
920 | (solver_->getWarmStart()) ; |
---|
921 | debugws->print() ; |
---|
922 | delete debugws ; } |
---|
923 | # endif |
---|
924 | } |
---|
925 | newNode->createInfo(this,node,lastws,lowerBefore,upperBefore, |
---|
926 | numberOldActiveCuts,numberNewCuts) ; |
---|
927 | if (newNode->numberUnsatisfied()) |
---|
928 | newNode->nodeInfo()->addCuts(cuts,newNode->numberBranches(), |
---|
929 | whichGenerator) ; } } |
---|
930 | else |
---|
931 | { anyAction = -2 ; } |
---|
932 | // May have slipped through i.e. anyAction == 0 and objective above cutoff |
---|
933 | if ( anyAction >=0 ) { |
---|
934 | assert (newNode); |
---|
935 | if (newNode->objectiveValue() >= getCutoff()) |
---|
936 | anyAction = -2; // say bad after all |
---|
937 | } |
---|
938 | /* |
---|
939 | If we end up infeasible, we can delete the new node immediately. Since this |
---|
940 | node won't be needing the cuts we collected, decrement the reference counts. |
---|
941 | If we are feasible, then we'll be placing this node into the live set, so |
---|
942 | increment the reference count in the current (parent) nodeInfo. |
---|
943 | */ |
---|
944 | if (anyAction == -2) |
---|
945 | { delete newNode ; |
---|
946 | newNode = NULL ; |
---|
947 | // switch off any hot start |
---|
948 | hotstartStrategy_=0; |
---|
949 | for (i = 0 ; i < currentNumberCuts_ ; i++) |
---|
950 | { if (addedCuts_[i]) |
---|
951 | { if (!addedCuts_[i]->decrement(1)) |
---|
952 | delete addedCuts_[i] ; } } } |
---|
953 | else |
---|
954 | { nodeInfo->increment() ; } |
---|
955 | /* |
---|
956 | At this point, there are three possibilities: |
---|
957 | * We have a live node (variable() >= 0) which will require further |
---|
958 | branching to resolve. Before we push it onto the search tree, try for |
---|
959 | a heuristic solution. |
---|
960 | * We have a solution, in which case newNode is non-null but we have no |
---|
961 | branching variable. Decrement the cut counts and save the solution. |
---|
962 | * The node was found to be infeasible, in which case it's already been |
---|
963 | deleted, and newNode is null. |
---|
964 | |
---|
965 | TODO: (lh) Now I'm more confused. I thought that the call to addCuts() above |
---|
966 | took care of incrementing the reference counts for cuts at newNode. |
---|
967 | Clearly I need to look more carefully. |
---|
968 | */ |
---|
969 | assert (!newNode || newNode->objectiveValue() <= getCutoff()) ; |
---|
970 | if (newNode) |
---|
971 | { if (newNode->variable() >= 0) |
---|
972 | { handler_->message(CBC_BRANCH,messages_) |
---|
973 | << numberNodes_<< newNode->objectiveValue() |
---|
974 | << newNode->numberUnsatisfied()<< newNode->depth() |
---|
975 | << CoinMessageEol ; |
---|
976 | // Increment cut counts (taking off current) |
---|
977 | int numberLeft = newNode->numberBranches() ; |
---|
978 | for (i = 0;i < currentNumberCuts_;i++) |
---|
979 | { if (addedCuts_[i]) |
---|
980 | { |
---|
981 | # ifdef CHECK_CUT_COUNTS |
---|
982 | printf("Count on cut %x increased by %d\n",addedCuts_[i], |
---|
983 | numberLeft-1) ; |
---|
984 | # endif |
---|
985 | addedCuts_[i]->increment(numberLeft-1) ; } } |
---|
986 | |
---|
987 | double estValue = newNode->guessedObjectiveValue() ; |
---|
988 | int found = -1 ; |
---|
989 | // no - overhead on small problems solver_->resolve() ; // double check current optimal |
---|
990 | // assert (!solver_->getIterationCount()); |
---|
991 | double * newSolution = new double [numberColumns] ; |
---|
992 | double heurValue = getCutoff() ; |
---|
993 | int iHeur ; |
---|
994 | for (iHeur = 0 ; iHeur < numberHeuristics_ ; iHeur++) |
---|
995 | { double saveValue = heurValue ; |
---|
996 | int ifSol = heuristic_[iHeur]->solution(heurValue,newSolution) ; |
---|
997 | if (ifSol > 0) // new solution found |
---|
998 | { found = iHeur ; } |
---|
999 | else |
---|
1000 | if (ifSol < 0) // just returning an estimate |
---|
1001 | { estValue = CoinMin(heurValue,estValue) ; |
---|
1002 | heurValue = saveValue ; } } |
---|
1003 | if (found >= 0) |
---|
1004 | { setBestSolution(CBC_ROUNDING,heurValue,newSolution) ; } |
---|
1005 | delete [] newSolution ; |
---|
1006 | newNode->setGuessedObjectiveValue(estValue) ; |
---|
1007 | tree_->push(newNode) ; |
---|
1008 | # ifdef CHECK_NODE |
---|
1009 | printf("Node %x pushed on tree c\n",newNode) ; |
---|
1010 | # endif |
---|
1011 | } |
---|
1012 | else |
---|
1013 | { for (i = 0 ; i < currentNumberCuts_ ; i++) |
---|
1014 | { if (addedCuts_[i]) |
---|
1015 | { if (!addedCuts_[i]->decrement(1)) |
---|
1016 | delete addedCuts_[i] ; } } |
---|
1017 | double objectiveValue = newNode->objectiveValue(); |
---|
1018 | setBestSolution(CBC_SOLUTION,objectiveValue, |
---|
1019 | solver_->getColSolution()) ; |
---|
1020 | assert(nodeInfo->numberPointingToThis() <= 2) ; |
---|
1021 | // avoid accidental pruning, if newNode was final branch arm |
---|
1022 | nodeInfo->increment(); |
---|
1023 | delete newNode ; |
---|
1024 | nodeInfo->decrement() ; } } |
---|
1025 | /* |
---|
1026 | This node has been completely expanded and can be removed from the live |
---|
1027 | set. |
---|
1028 | */ |
---|
1029 | if (deleteNode) |
---|
1030 | delete node ; } |
---|
1031 | /* |
---|
1032 | End of the non-abort actions. The next block of code is executed if we've |
---|
1033 | aborted because we hit one of the limits. Clean up by deleting the live set |
---|
1034 | and break out of the node processing loop. |
---|
1035 | */ |
---|
1036 | else |
---|
1037 | { |
---|
1038 | tree_->cleanTree(this,-COIN_DBL_MAX) ; |
---|
1039 | delete nextRowCut_; |
---|
1040 | // We need to get rid of node if is has already been popped from tree |
---|
1041 | if (!nodeOnTree&&!stoppedOnGap) |
---|
1042 | delete node; |
---|
1043 | if (stoppedOnGap) |
---|
1044 | { messageHandler()->message(CBC_GAP,messages()) |
---|
1045 | << bestObjective_-bestValue |
---|
1046 | << dblParam_[CbcAllowableGap] |
---|
1047 | << dblParam_[CbcAllowableFractionGap]*100.0 |
---|
1048 | << CoinMessageEol ; |
---|
1049 | status_ = 0 ; } |
---|
1050 | else |
---|
1051 | if (isNodeLimitReached()) |
---|
1052 | { handler_->message(CBC_MAXNODES,messages_) << CoinMessageEol ; |
---|
1053 | status_ = 1 ; } |
---|
1054 | else |
---|
1055 | if (totalTime >= dblParam_[CbcMaximumSeconds]) |
---|
1056 | { handler_->message(CBC_MAXTIME,messages_) << CoinMessageEol ; |
---|
1057 | status_ = 1 ; } |
---|
1058 | else |
---|
1059 | { handler_->message(CBC_MAXSOLS,messages_) << CoinMessageEol ; |
---|
1060 | status_ = 1 ; } |
---|
1061 | break ; } |
---|
1062 | /* |
---|
1063 | Delete cuts to get back to the original system. |
---|
1064 | |
---|
1065 | I'm thinking this is redundant --- the call to addCuts that conditions entry |
---|
1066 | to this code block also performs this action. |
---|
1067 | */ |
---|
1068 | int numberToDelete = getNumRows()-numberRowsAtContinuous_ ; |
---|
1069 | if (numberToDelete) |
---|
1070 | { int * delRows = new int[numberToDelete] ; |
---|
1071 | int i ; |
---|
1072 | for (i = 0 ; i < numberToDelete ; i++) |
---|
1073 | { delRows[i] = i+numberRowsAtContinuous_ ; } |
---|
1074 | solver_->deleteRows(numberToDelete,delRows) ; |
---|
1075 | delete [] delRows ; } } |
---|
1076 | /* |
---|
1077 | This node fathomed when addCuts atttempted to revive it. Toss it. |
---|
1078 | */ |
---|
1079 | else |
---|
1080 | { delete node ; } } |
---|
1081 | /* |
---|
1082 | That's it, we've exhausted the search tree, or broken out of the loop because |
---|
1083 | we hit some limit on evaluation. |
---|
1084 | |
---|
1085 | We may have got an intelligent tree so give it one more chance |
---|
1086 | */ |
---|
1087 | // Tell solver we are not in Branch and Cut |
---|
1088 | solver_->setHintParam(OsiDoInBranchAndCut,false,OsiHintDo,NULL) ; |
---|
1089 | tree_->endSearch(); |
---|
1090 | // If we did any sub trees - did we give up on any? |
---|
1091 | if ( numberStoppedSubTrees_) |
---|
1092 | status_=1; |
---|
1093 | if (!status_) |
---|
1094 | handler_->message(CBC_END_GOOD,messages_) |
---|
1095 | << bestObjective_ << numberIterations_ << numberNodes_ |
---|
1096 | << CoinMessageEol ; |
---|
1097 | else |
---|
1098 | handler_->message(CBC_END,messages_) |
---|
1099 | << bestObjective_ << numberIterations_ << numberNodes_ |
---|
1100 | << CoinMessageEol ; |
---|
1101 | /* |
---|
1102 | If we think we have a solution, restore and confirm it with a call to |
---|
1103 | setBestSolution(). We need to reset the cutoff value so as not to fathom |
---|
1104 | the solution on bounds. Note that calling setBestSolution( ..., true) |
---|
1105 | leaves the continuousSolver_ bounds vectors fixed at the solution value. |
---|
1106 | |
---|
1107 | Running resolve() here is a failsafe --- setBestSolution has already |
---|
1108 | reoptimised using the continuousSolver_. If for some reason we fail to |
---|
1109 | prove optimality, run the problem again after instructing the solver to |
---|
1110 | tell us more. |
---|
1111 | |
---|
1112 | If all looks good, replace solver_ with continuousSolver_, so that the |
---|
1113 | outside world will be able to obtain information about the solution using |
---|
1114 | public methods. |
---|
1115 | */ |
---|
1116 | if (bestSolution_) |
---|
1117 | { setCutoff(1.0e50) ; // As best solution should be worse than cutoff |
---|
1118 | phase_=5; |
---|
1119 | setBestSolution(CBC_SOLUTION,bestObjective_,bestSolution_,true) ; |
---|
1120 | continuousSolver_->resolve() ; |
---|
1121 | if (!continuousSolver_->isProvenOptimal()) |
---|
1122 | { continuousSolver_->messageHandler()->setLogLevel(2) ; |
---|
1123 | continuousSolver_->initialSolve() ; } |
---|
1124 | delete solver_ ; |
---|
1125 | solver_ = continuousSolver_ ; |
---|
1126 | continuousSolver_ = NULL ; } |
---|
1127 | /* |
---|
1128 | Clean up dangling objects. continuousSolver_ may already be toast. |
---|
1129 | */ |
---|
1130 | delete lastws ; |
---|
1131 | delete [] whichGenerator ; |
---|
1132 | delete [] lowerBefore ; |
---|
1133 | delete [] upperBefore ; |
---|
1134 | delete [] walkback_ ; |
---|
1135 | walkback_ = NULL ; |
---|
1136 | delete [] addedCuts_ ; |
---|
1137 | addedCuts_ = NULL ; |
---|
1138 | if (continuousSolver_) |
---|
1139 | { delete continuousSolver_ ; |
---|
1140 | continuousSolver_ = NULL ; } |
---|
1141 | /* |
---|
1142 | Destroy global cuts by replacing with an empty OsiCuts object. |
---|
1143 | */ |
---|
1144 | globalCuts_= OsiCuts() ; |
---|
1145 | |
---|
1146 | return ; } |
---|
1147 | |
---|
1148 | |
---|
1149 | |
---|
1150 | // Solve the initial LP relaxation |
---|
1151 | void |
---|
1152 | CbcModel::initialSolve() |
---|
1153 | { |
---|
1154 | assert (solver_); |
---|
1155 | solver_->initialSolve(); |
---|
1156 | } |
---|
1157 | |
---|
1158 | /*! \brief Get an empty basis object |
---|
1159 | |
---|
1160 | Return an empty CoinWarmStartBasis object with the requested capacity, |
---|
1161 | appropriate for the current solver. The object is cloned from the object |
---|
1162 | cached as emptyWarmStart_. If there is no cached object, the routine |
---|
1163 | queries the solver for a warm start object, empties it, and caches the |
---|
1164 | result. |
---|
1165 | */ |
---|
1166 | |
---|
1167 | CoinWarmStartBasis *CbcModel::getEmptyBasis (int ns, int na) const |
---|
1168 | |
---|
1169 | { CoinWarmStartBasis *emptyBasis ; |
---|
1170 | /* |
---|
1171 | Acquire an empty basis object, if we don't yet have one. |
---|
1172 | */ |
---|
1173 | if (emptyWarmStart_ == 0) |
---|
1174 | { if (solver_ == 0) |
---|
1175 | { throw CoinError("Cannot construct basis without solver!", |
---|
1176 | "getEmptyBasis","CbcModel") ; } |
---|
1177 | emptyBasis = |
---|
1178 | dynamic_cast<CoinWarmStartBasis *>(solver_->getEmptyWarmStart()) ; |
---|
1179 | if (emptyBasis == 0) |
---|
1180 | { throw CoinError( |
---|
1181 | "Solver does not appear to use a basis-oriented warm start.", |
---|
1182 | "getEmptyBasis","CbcModel") ; } |
---|
1183 | emptyBasis->setSize(0,0) ; |
---|
1184 | emptyWarmStart_ = dynamic_cast<CoinWarmStart *>(emptyBasis) ; } |
---|
1185 | /* |
---|
1186 | Clone the empty basis object, resize it as requested, and return. |
---|
1187 | */ |
---|
1188 | emptyBasis = dynamic_cast<CoinWarmStartBasis *>(emptyWarmStart_->clone()) ; |
---|
1189 | assert(emptyBasis) ; |
---|
1190 | if (ns != 0 || na != 0) emptyBasis->setSize(ns,na) ; |
---|
1191 | |
---|
1192 | return (emptyBasis) ; } |
---|
1193 | |
---|
1194 | |
---|
1195 | /** Default Constructor |
---|
1196 | |
---|
1197 | Creates an empty model without an associated solver. |
---|
1198 | */ |
---|
1199 | CbcModel::CbcModel() |
---|
1200 | |
---|
1201 | : |
---|
1202 | solver_(NULL), |
---|
1203 | ourSolver_(true), |
---|
1204 | continuousSolver_(NULL), |
---|
1205 | defaultHandler_(true), |
---|
1206 | emptyWarmStart_(NULL), |
---|
1207 | basis_(NULL), |
---|
1208 | bestObjective_(COIN_DBL_MAX), |
---|
1209 | bestSolution_(NULL), |
---|
1210 | currentSolution_(NULL), |
---|
1211 | minimumDrop_(1.0e-4), |
---|
1212 | numberSolutions_(0), |
---|
1213 | hotstartStrategy_(0), |
---|
1214 | numberHeuristicSolutions_(0), |
---|
1215 | numberNodes_(0), |
---|
1216 | numberIterations_(0), |
---|
1217 | status_(0), |
---|
1218 | numberIntegers_(0), |
---|
1219 | numberRowsAtContinuous_(0), |
---|
1220 | maximumNumberCuts_(0), |
---|
1221 | phase_(0), |
---|
1222 | currentNumberCuts_(0), |
---|
1223 | maximumDepth_(0), |
---|
1224 | walkback_(NULL), |
---|
1225 | addedCuts_(NULL), |
---|
1226 | nextRowCut_(NULL), |
---|
1227 | currentNode_(NULL), |
---|
1228 | integerVariable_(NULL), |
---|
1229 | strategy_(0), |
---|
1230 | subTreeModel_(NULL), |
---|
1231 | numberStoppedSubTrees_(0), |
---|
1232 | presolve_(0), |
---|
1233 | numberStrong_(5), |
---|
1234 | printFrequency_(0), |
---|
1235 | numberCutGenerators_(0), |
---|
1236 | generator_(NULL), |
---|
1237 | virginGenerator_(NULL), |
---|
1238 | numberHeuristics_(0), |
---|
1239 | heuristic_(NULL), |
---|
1240 | numberObjects_(0), |
---|
1241 | object_(NULL), |
---|
1242 | originalColumns_(NULL), |
---|
1243 | priority_(NULL), |
---|
1244 | howOftenGlobalScan_(1), |
---|
1245 | numberGlobalViolations_(0), |
---|
1246 | continuousObjective_(COIN_DBL_MAX), |
---|
1247 | originalContinuousObjective_(COIN_DBL_MAX), |
---|
1248 | continuousInfeasibilities_(INT_MAX), |
---|
1249 | maximumCutPassesAtRoot_(20), |
---|
1250 | maximumCutPasses_(10), |
---|
1251 | resolveAfterTakeOffCuts_(true) |
---|
1252 | { |
---|
1253 | intParam_[CbcMaxNumNode] = 99999999; |
---|
1254 | intParam_[CbcMaxNumSol] = 9999999; |
---|
1255 | intParam_[CbcFathomDiscipline] = 0; |
---|
1256 | |
---|
1257 | dblParam_[CbcIntegerTolerance] = 1e-6; |
---|
1258 | dblParam_[CbcInfeasibilityWeight] = 0.0; |
---|
1259 | dblParam_[CbcCutoffIncrement] = 1e-5; |
---|
1260 | dblParam_[CbcAllowableGap] = 1.0e-10; |
---|
1261 | dblParam_[CbcAllowableFractionGap] = 0.0; |
---|
1262 | dblParam_[CbcMaximumSeconds] = 1.0e100; |
---|
1263 | dblParam_[CbcStartSeconds] = 0.0; |
---|
1264 | nodeCompare_=NULL; |
---|
1265 | tree_= new CbcTree(); |
---|
1266 | branchingMethod_=NULL; |
---|
1267 | appData_=NULL; |
---|
1268 | handler_ = new CoinMessageHandler(); |
---|
1269 | handler_->setLogLevel(2); |
---|
1270 | messages_ = CbcMessage(); |
---|
1271 | } |
---|
1272 | |
---|
1273 | /** Constructor from solver. |
---|
1274 | |
---|
1275 | Creates a model complete with a clone of the solver passed as a parameter. |
---|
1276 | */ |
---|
1277 | |
---|
1278 | CbcModel::CbcModel(const OsiSolverInterface &rhs) |
---|
1279 | : |
---|
1280 | continuousSolver_(NULL), |
---|
1281 | defaultHandler_(true), |
---|
1282 | emptyWarmStart_(NULL), |
---|
1283 | basis_(NULL) , |
---|
1284 | bestObjective_(COIN_DBL_MAX), |
---|
1285 | minimumDrop_(1.0e-4), |
---|
1286 | numberSolutions_(0), |
---|
1287 | hotstartStrategy_(0), |
---|
1288 | numberHeuristicSolutions_(0), |
---|
1289 | numberNodes_(0), |
---|
1290 | numberIterations_(0), |
---|
1291 | status_(0), |
---|
1292 | numberRowsAtContinuous_(0), |
---|
1293 | maximumNumberCuts_(0), |
---|
1294 | phase_(0), |
---|
1295 | currentNumberCuts_(0), |
---|
1296 | maximumDepth_(0), |
---|
1297 | walkback_(NULL), |
---|
1298 | addedCuts_(NULL), |
---|
1299 | nextRowCut_(NULL), |
---|
1300 | currentNode_(NULL), |
---|
1301 | strategy_(0), |
---|
1302 | subTreeModel_(NULL), |
---|
1303 | numberStoppedSubTrees_(0), |
---|
1304 | presolve_(0), |
---|
1305 | numberStrong_(5), |
---|
1306 | printFrequency_(0), |
---|
1307 | numberCutGenerators_(0), |
---|
1308 | generator_(NULL), |
---|
1309 | virginGenerator_(NULL), |
---|
1310 | numberHeuristics_(0), |
---|
1311 | heuristic_(NULL), |
---|
1312 | numberObjects_(0), |
---|
1313 | object_(NULL), |
---|
1314 | originalColumns_(NULL), |
---|
1315 | priority_(NULL), |
---|
1316 | howOftenGlobalScan_(1), |
---|
1317 | numberGlobalViolations_(0), |
---|
1318 | continuousObjective_(COIN_DBL_MAX), |
---|
1319 | originalContinuousObjective_(COIN_DBL_MAX), |
---|
1320 | continuousInfeasibilities_(INT_MAX), |
---|
1321 | maximumCutPassesAtRoot_(20), |
---|
1322 | maximumCutPasses_(10), |
---|
1323 | resolveAfterTakeOffCuts_(true) |
---|
1324 | { |
---|
1325 | intParam_[CbcMaxNumNode] = 99999999; |
---|
1326 | intParam_[CbcMaxNumSol] = 9999999; |
---|
1327 | intParam_[CbcFathomDiscipline] = 0; |
---|
1328 | |
---|
1329 | dblParam_[CbcIntegerTolerance] = 1e-6; |
---|
1330 | dblParam_[CbcInfeasibilityWeight] = 0.0; |
---|
1331 | dblParam_[CbcCutoffIncrement] = 1e-5; |
---|
1332 | dblParam_[CbcAllowableGap] = 1.0e-10; |
---|
1333 | dblParam_[CbcAllowableFractionGap] = 0.0; |
---|
1334 | dblParam_[CbcMaximumSeconds] = 1.0e100; |
---|
1335 | dblParam_[CbcStartSeconds] = 0.0; |
---|
1336 | |
---|
1337 | nodeCompare_=NULL; |
---|
1338 | tree_= new CbcTree(); |
---|
1339 | branchingMethod_=NULL; |
---|
1340 | appData_=NULL; |
---|
1341 | handler_ = new CoinMessageHandler(); |
---|
1342 | handler_->setLogLevel(2); |
---|
1343 | messages_ = CbcMessage(); |
---|
1344 | solver_ = rhs.clone(); |
---|
1345 | ourSolver_ = true ; |
---|
1346 | |
---|
1347 | // Initialize solution and integer variable vectors |
---|
1348 | bestSolution_ = NULL; // to say no solution found |
---|
1349 | numberIntegers_=0; |
---|
1350 | int numberColumns = solver_->getNumCols(); |
---|
1351 | int iColumn; |
---|
1352 | if (numberColumns) { |
---|
1353 | // Space for current solution |
---|
1354 | currentSolution_ = new double[numberColumns]; |
---|
1355 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
---|
1356 | if( solver_->isInteger(iColumn)) |
---|
1357 | numberIntegers_++; |
---|
1358 | } |
---|
1359 | } else { |
---|
1360 | // empty model |
---|
1361 | currentSolution_=NULL; |
---|
1362 | } |
---|
1363 | if (numberIntegers_) { |
---|
1364 | integerVariable_ = new int [numberIntegers_]; |
---|
1365 | numberIntegers_=0; |
---|
1366 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
---|
1367 | if( solver_->isInteger(iColumn)) |
---|
1368 | integerVariable_[numberIntegers_++]=iColumn; |
---|
1369 | } |
---|
1370 | } else { |
---|
1371 | integerVariable_ = NULL; |
---|
1372 | } |
---|
1373 | } |
---|
1374 | |
---|
1375 | /* |
---|
1376 | Assign a solver to the model (model assumes ownership) |
---|
1377 | |
---|
1378 | The integer variable vector is initialized if it's not already present. |
---|
1379 | |
---|
1380 | Assuming ownership matches usage in OsiSolverInterface |
---|
1381 | (cf. assignProblem, loadProblem). |
---|
1382 | |
---|
1383 | TODO: What to do about solver parameters? A simple copy likely won't do it, |
---|
1384 | because the SI must push the settings into the underlying solver. In |
---|
1385 | the context of switching solvers in cbc, this means that command line |
---|
1386 | settings will get lost. Stash the command line somewhere and reread it |
---|
1387 | here, maybe? |
---|
1388 | |
---|
1389 | TODO: More generally, how much state should be transferred from the old |
---|
1390 | solver to the new solver? Best perhaps to see how usage develops. |
---|
1391 | What's done here mimics the CbcModel(OsiSolverInterface) constructor. |
---|
1392 | */ |
---|
1393 | void |
---|
1394 | CbcModel::assignSolver(OsiSolverInterface *&solver) |
---|
1395 | |
---|
1396 | { |
---|
1397 | // Keep the current message level for solver (if solver exists) |
---|
1398 | if (solver_) |
---|
1399 | solver->messageHandler()->setLogLevel(solver_->messageHandler()->logLevel()) ; |
---|
1400 | |
---|
1401 | if (ourSolver_) delete solver_ ; |
---|
1402 | solver_ = solver; |
---|
1403 | solver = NULL ; |
---|
1404 | ourSolver_ = true ; |
---|
1405 | /* |
---|
1406 | Basis information is solver-specific. |
---|
1407 | */ |
---|
1408 | if (basis_) |
---|
1409 | { delete basis_ ; |
---|
1410 | basis_ = 0 ; } |
---|
1411 | if (emptyWarmStart_) |
---|
1412 | { delete emptyWarmStart_ ; |
---|
1413 | emptyWarmStart_ = 0 ; } |
---|
1414 | /* |
---|
1415 | Initialize integer variable vector. |
---|
1416 | */ |
---|
1417 | numberIntegers_=0; |
---|
1418 | int numberColumns = solver_->getNumCols(); |
---|
1419 | int iColumn; |
---|
1420 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
---|
1421 | if( solver_->isInteger(iColumn)) |
---|
1422 | numberIntegers_++; |
---|
1423 | } |
---|
1424 | if (numberIntegers_) { |
---|
1425 | delete [] integerVariable_; |
---|
1426 | integerVariable_ = new int [numberIntegers_]; |
---|
1427 | numberIntegers_=0; |
---|
1428 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
---|
1429 | if( solver_->isInteger(iColumn)) |
---|
1430 | integerVariable_[numberIntegers_++]=iColumn; |
---|
1431 | } |
---|
1432 | } else { |
---|
1433 | integerVariable_ = NULL; |
---|
1434 | } |
---|
1435 | |
---|
1436 | return ; |
---|
1437 | } |
---|
1438 | |
---|
1439 | // Copy constructor. |
---|
1440 | |
---|
1441 | CbcModel::CbcModel(const CbcModel & rhs, bool noTree) |
---|
1442 | : |
---|
1443 | continuousSolver_(NULL), |
---|
1444 | defaultHandler_(rhs.defaultHandler_), |
---|
1445 | emptyWarmStart_(NULL), |
---|
1446 | basis_(NULL), |
---|
1447 | bestObjective_(rhs.bestObjective_), |
---|
1448 | minimumDrop_(rhs.minimumDrop_), |
---|
1449 | numberSolutions_(rhs.numberSolutions_), |
---|
1450 | hotstartStrategy_(rhs.hotstartStrategy_), |
---|
1451 | numberHeuristicSolutions_(rhs.numberHeuristicSolutions_), |
---|
1452 | numberNodes_(rhs.numberNodes_), |
---|
1453 | numberIterations_(rhs.numberIterations_), |
---|
1454 | status_(rhs.status_), |
---|
1455 | strategy_(rhs.strategy_), |
---|
1456 | subTreeModel_(rhs.subTreeModel_), |
---|
1457 | numberStoppedSubTrees_(rhs.numberStoppedSubTrees_), |
---|
1458 | presolve_(rhs.presolve_), |
---|
1459 | numberStrong_(rhs.numberStrong_), |
---|
1460 | printFrequency_(rhs.printFrequency_), |
---|
1461 | howOftenGlobalScan_(rhs.howOftenGlobalScan_), |
---|
1462 | numberGlobalViolations_(rhs.numberGlobalViolations_), |
---|
1463 | continuousObjective_(rhs.continuousObjective_), |
---|
1464 | originalContinuousObjective_(rhs.originalContinuousObjective_), |
---|
1465 | continuousInfeasibilities_(rhs.continuousInfeasibilities_), |
---|
1466 | maximumCutPassesAtRoot_(rhs.maximumCutPassesAtRoot_), |
---|
1467 | maximumCutPasses_( rhs.maximumCutPasses_), |
---|
1468 | resolveAfterTakeOffCuts_(rhs.resolveAfterTakeOffCuts_) |
---|
1469 | { |
---|
1470 | intParam_[CbcMaxNumNode] = rhs.intParam_[CbcMaxNumNode]; |
---|
1471 | intParam_[CbcMaxNumSol] = rhs.intParam_[CbcMaxNumSol]; |
---|
1472 | intParam_[CbcFathomDiscipline] = rhs.intParam_[CbcFathomDiscipline]; |
---|
1473 | dblParam_[CbcIntegerTolerance] = rhs.dblParam_[CbcIntegerTolerance]; |
---|
1474 | dblParam_[CbcInfeasibilityWeight] = rhs.dblParam_[CbcInfeasibilityWeight]; |
---|
1475 | dblParam_[CbcCutoffIncrement] = rhs.dblParam_[CbcCutoffIncrement]; |
---|
1476 | dblParam_[CbcAllowableGap] = rhs.dblParam_[CbcAllowableGap]; |
---|
1477 | dblParam_[CbcAllowableFractionGap] = rhs.dblParam_[CbcAllowableFractionGap]; |
---|
1478 | dblParam_[CbcMaximumSeconds] = rhs.dblParam_[CbcMaximumSeconds]; |
---|
1479 | dblParam_[CbcStartSeconds] = dblParam_[CbcStartSeconds]; // will be overwritten hopefully |
---|
1480 | if (rhs.emptyWarmStart_) emptyWarmStart_ = rhs.emptyWarmStart_->clone() ; |
---|
1481 | if (rhs.basis_) basis_ = |
---|
1482 | dynamic_cast<CoinWarmStartBasis *>(rhs.basis_->clone()) ; |
---|
1483 | if (defaultHandler_) { |
---|
1484 | handler_ = new CoinMessageHandler(); |
---|
1485 | handler_->setLogLevel(2); |
---|
1486 | } else { |
---|
1487 | handler_ = rhs.handler_; |
---|
1488 | } |
---|
1489 | messageHandler()->setLogLevel(rhs.messageHandler()->logLevel()); |
---|
1490 | numberCutGenerators_ = rhs.numberCutGenerators_; |
---|
1491 | if (numberCutGenerators_) { |
---|
1492 | generator_ = new CbcCutGenerator * [numberCutGenerators_]; |
---|
1493 | virginGenerator_ = new CbcCutGenerator * [numberCutGenerators_]; |
---|
1494 | int i; |
---|
1495 | for (i=0;i<numberCutGenerators_;i++) { |
---|
1496 | generator_[i]=new CbcCutGenerator(*rhs.generator_[i]); |
---|
1497 | virginGenerator_[i]=new CbcCutGenerator(*rhs.virginGenerator_[i]); |
---|
1498 | } |
---|
1499 | } else { |
---|
1500 | generator_=NULL; |
---|
1501 | virginGenerator_=NULL; |
---|
1502 | } |
---|
1503 | if (!noTree) |
---|
1504 | globalCuts_ = rhs.globalCuts_; |
---|
1505 | numberHeuristics_ = rhs.numberHeuristics_; |
---|
1506 | if (numberHeuristics_) { |
---|
1507 | heuristic_ = new CbcHeuristic * [numberHeuristics_]; |
---|
1508 | int i; |
---|
1509 | for (i=0;i<numberHeuristics_;i++) { |
---|
1510 | heuristic_[i]=rhs.heuristic_[i]->clone(); |
---|
1511 | } |
---|
1512 | } else { |
---|
1513 | heuristic_=NULL; |
---|
1514 | } |
---|
1515 | numberObjects_=rhs.numberObjects_; |
---|
1516 | if (numberObjects_) { |
---|
1517 | object_ = new CbcObject * [numberObjects_]; |
---|
1518 | int i; |
---|
1519 | for (i=0;i<numberObjects_;i++) |
---|
1520 | object_[i]=(rhs.object_[i])->clone(); |
---|
1521 | } else { |
---|
1522 | object_=NULL; |
---|
1523 | } |
---|
1524 | if (rhs.priority_) { |
---|
1525 | priority_= new int [numberObjects_]; |
---|
1526 | memcpy(priority_,rhs.priority_,numberObjects_*sizeof(int)); |
---|
1527 | } else { |
---|
1528 | priority_=NULL; |
---|
1529 | } |
---|
1530 | if (!noTree||!rhs.continuousSolver_) |
---|
1531 | solver_ = rhs.solver_->clone(); |
---|
1532 | else |
---|
1533 | solver_ = rhs.continuousSolver_->clone(); |
---|
1534 | if (rhs.originalColumns_) { |
---|
1535 | int numberColumns = solver_->getNumCols(); |
---|
1536 | originalColumns_= new int [numberColumns]; |
---|
1537 | memcpy(originalColumns_,rhs.originalColumns_,numberColumns*sizeof(int)); |
---|
1538 | } else { |
---|
1539 | originalColumns_=NULL; |
---|
1540 | } |
---|
1541 | nodeCompare_=rhs.nodeCompare_; |
---|
1542 | tree_= rhs.tree_->clone(); |
---|
1543 | branchingMethod_=rhs.branchingMethod_; |
---|
1544 | appData_=rhs.appData_; |
---|
1545 | messages_ = rhs.messages_; |
---|
1546 | ourSolver_ = true ; |
---|
1547 | messageHandler()->setLogLevel(rhs.messageHandler()->logLevel()); |
---|
1548 | numberIntegers_=rhs.numberIntegers_; |
---|
1549 | if (numberIntegers_) { |
---|
1550 | integerVariable_ = new int [numberIntegers_]; |
---|
1551 | memcpy(integerVariable_,rhs.integerVariable_,numberIntegers_*sizeof(int)); |
---|
1552 | } else { |
---|
1553 | integerVariable_ = NULL; |
---|
1554 | } |
---|
1555 | if (rhs.bestSolution_&&!noTree) { |
---|
1556 | int numberColumns = solver_->getNumCols(); |
---|
1557 | bestSolution_ = new double[numberColumns]; |
---|
1558 | memcpy(bestSolution_,rhs.bestSolution_,numberColumns*sizeof(double)); |
---|
1559 | } else { |
---|
1560 | bestSolution_=NULL; |
---|
1561 | } |
---|
1562 | if (rhs.currentSolution_&&!noTree) { |
---|
1563 | int numberColumns = solver_->getNumCols(); |
---|
1564 | currentSolution_ = new double[numberColumns]; |
---|
1565 | memcpy(currentSolution_,rhs.currentSolution_,numberColumns*sizeof(double)); |
---|
1566 | } else { |
---|
1567 | currentSolution_=NULL; |
---|
1568 | } |
---|
1569 | numberRowsAtContinuous_ = rhs.numberRowsAtContinuous_; |
---|
1570 | maximumNumberCuts_=rhs.maximumNumberCuts_; |
---|
1571 | phase_ = rhs.phase_; |
---|
1572 | currentNumberCuts_=rhs.currentNumberCuts_; |
---|
1573 | maximumDepth_= rhs.maximumDepth_; |
---|
1574 | if (noTree) { |
---|
1575 | bestObjective_ = COIN_DBL_MAX; |
---|
1576 | numberSolutions_ =0; |
---|
1577 | numberHeuristicSolutions_=0; |
---|
1578 | numberNodes_=0; |
---|
1579 | numberIterations_=0; |
---|
1580 | status_=0; |
---|
1581 | subTreeModel_=NULL; |
---|
1582 | numberStoppedSubTrees_=0; |
---|
1583 | continuousObjective_=COIN_DBL_MAX; |
---|
1584 | originalContinuousObjective_=COIN_DBL_MAX; |
---|
1585 | continuousInfeasibilities_=INT_MAX; |
---|
1586 | maximumNumberCuts_=0; |
---|
1587 | tree_->cleanTree(this,-COIN_DBL_MAX); |
---|
1588 | } |
---|
1589 | // These are only used as temporary arrays so need not be filled |
---|
1590 | if (maximumNumberCuts_) { |
---|
1591 | addedCuts_ = new CbcCountRowCut * [maximumNumberCuts_]; |
---|
1592 | } else { |
---|
1593 | addedCuts_ = NULL; |
---|
1594 | } |
---|
1595 | nextRowCut_ = NULL; |
---|
1596 | currentNode_ = NULL; |
---|
1597 | if (maximumDepth_) |
---|
1598 | walkback_ = new CbcNodeInfo * [maximumDepth_]; |
---|
1599 | else |
---|
1600 | walkback_ = NULL; |
---|
1601 | synchronizeModel(); |
---|
1602 | } |
---|
1603 | |
---|
1604 | // Assignment operator |
---|
1605 | CbcModel & |
---|
1606 | CbcModel::operator=(const CbcModel& rhs) |
---|
1607 | { |
---|
1608 | if (this!=&rhs) { |
---|
1609 | |
---|
1610 | if (defaultHandler_) |
---|
1611 | { delete handler_; |
---|
1612 | handler_ = NULL; } |
---|
1613 | defaultHandler_ = rhs.defaultHandler_; |
---|
1614 | if (defaultHandler_) |
---|
1615 | { handler_ = new CoinMessageHandler(); |
---|
1616 | handler_->setLogLevel(2); } |
---|
1617 | else |
---|
1618 | { handler_ = rhs.handler_; } |
---|
1619 | messages_ = rhs.messages_; |
---|
1620 | messageHandler()->setLogLevel(rhs.messageHandler()->logLevel()); |
---|
1621 | |
---|
1622 | delete solver_; |
---|
1623 | if (rhs.solver_) |
---|
1624 | { solver_ = rhs.solver_->clone() ; } |
---|
1625 | else |
---|
1626 | { solver_ = 0 ; } |
---|
1627 | ourSolver_ = true ; |
---|
1628 | delete continuousSolver_ ; |
---|
1629 | if (rhs.continuousSolver_) |
---|
1630 | { solver_ = rhs.continuousSolver_->clone() ; } |
---|
1631 | else |
---|
1632 | { continuousSolver_ = 0 ; } |
---|
1633 | |
---|
1634 | delete emptyWarmStart_ ; |
---|
1635 | if (rhs.emptyWarmStart_) |
---|
1636 | { emptyWarmStart_ = rhs.emptyWarmStart_->clone() ; } |
---|
1637 | else |
---|
1638 | { emptyWarmStart_ = 0 ; } |
---|
1639 | delete basis_ ; |
---|
1640 | if (rhs.basis_) |
---|
1641 | { basis_ = dynamic_cast<CoinWarmStartBasis *>(rhs.basis_->clone()) ; } |
---|
1642 | else |
---|
1643 | { basis_ = 0 ; } |
---|
1644 | |
---|
1645 | bestObjective_ = rhs.bestObjective_; |
---|
1646 | delete [] bestSolution_; |
---|
1647 | if (rhs.bestSolution_) { |
---|
1648 | int numberColumns = rhs.getNumCols(); |
---|
1649 | bestSolution_ = new double[numberColumns]; |
---|
1650 | memcpy(bestSolution_,rhs.bestSolution_,numberColumns*sizeof(double)); |
---|
1651 | } else { |
---|
1652 | bestSolution_=NULL; |
---|
1653 | } |
---|
1654 | if (rhs.currentSolution_) { |
---|
1655 | int numberColumns = rhs.getNumCols(); |
---|
1656 | currentSolution_ = new double[numberColumns]; |
---|
1657 | memcpy(currentSolution_,rhs.currentSolution_,numberColumns*sizeof(double)); |
---|
1658 | } else { |
---|
1659 | currentSolution_=NULL; |
---|
1660 | } |
---|
1661 | minimumDrop_ = rhs.minimumDrop_; |
---|
1662 | numberSolutions_=rhs.numberSolutions_; |
---|
1663 | hotstartStrategy_=rhs.hotstartStrategy_; |
---|
1664 | numberHeuristicSolutions_=rhs.numberHeuristicSolutions_; |
---|
1665 | numberNodes_ = rhs.numberNodes_; |
---|
1666 | numberIterations_ = rhs.numberIterations_; |
---|
1667 | status_ = rhs.status_; |
---|
1668 | strategy_ = rhs.strategy_; |
---|
1669 | subTreeModel_ = rhs.subTreeModel_; |
---|
1670 | numberStoppedSubTrees_ = rhs.numberStoppedSubTrees_; |
---|
1671 | presolve_ = rhs.presolve_; |
---|
1672 | numberStrong_ = rhs.numberStrong_; |
---|
1673 | printFrequency_ = rhs.printFrequency_; |
---|
1674 | howOftenGlobalScan_=rhs.howOftenGlobalScan_; |
---|
1675 | numberGlobalViolations_=rhs.numberGlobalViolations_; |
---|
1676 | continuousObjective_=rhs.continuousObjective_; |
---|
1677 | originalContinuousObjective_ = rhs.originalContinuousObjective_; |
---|
1678 | continuousInfeasibilities_ = rhs.continuousInfeasibilities_; |
---|
1679 | maximumCutPassesAtRoot_ = rhs.maximumCutPassesAtRoot_; |
---|
1680 | maximumCutPasses_ = rhs.maximumCutPasses_; |
---|
1681 | resolveAfterTakeOffCuts_=rhs.resolveAfterTakeOffCuts_; |
---|
1682 | intParam_[CbcMaxNumNode] = rhs.intParam_[CbcMaxNumNode]; |
---|
1683 | intParam_[CbcMaxNumSol] = rhs.intParam_[CbcMaxNumSol]; |
---|
1684 | intParam_[CbcFathomDiscipline] = rhs.intParam_[CbcFathomDiscipline]; |
---|
1685 | dblParam_[CbcIntegerTolerance] = rhs.dblParam_[CbcIntegerTolerance]; |
---|
1686 | dblParam_[CbcInfeasibilityWeight] = rhs.dblParam_[CbcInfeasibilityWeight]; |
---|
1687 | dblParam_[CbcCutoffIncrement] = rhs.dblParam_[CbcCutoffIncrement]; |
---|
1688 | dblParam_[CbcAllowableGap] = rhs.dblParam_[CbcAllowableGap]; |
---|
1689 | dblParam_[CbcAllowableFractionGap] = rhs.dblParam_[CbcAllowableFractionGap]; |
---|
1690 | dblParam_[CbcMaximumSeconds] = rhs.dblParam_[CbcMaximumSeconds]; |
---|
1691 | dblParam_[CbcStartSeconds] = dblParam_[CbcStartSeconds]; // will be overwritten hopefully |
---|
1692 | globalCuts_ = rhs.globalCuts_; |
---|
1693 | int i; |
---|
1694 | for (i=0;i<numberCutGenerators_;i++) { |
---|
1695 | delete generator_[i]; |
---|
1696 | delete virginGenerator_[i]; |
---|
1697 | } |
---|
1698 | delete [] generator_; |
---|
1699 | delete [] virginGenerator_; |
---|
1700 | delete [] heuristic_; |
---|
1701 | numberCutGenerators_ = rhs.numberCutGenerators_; |
---|
1702 | if (numberCutGenerators_) { |
---|
1703 | generator_ = new CbcCutGenerator * [numberCutGenerators_]; |
---|
1704 | virginGenerator_ = new CbcCutGenerator * [numberCutGenerators_]; |
---|
1705 | int i; |
---|
1706 | for (i=0;i<numberCutGenerators_;i++) { |
---|
1707 | generator_[i]=new CbcCutGenerator(*rhs.generator_[i]); |
---|
1708 | virginGenerator_[i]=new CbcCutGenerator(*rhs.virginGenerator_[i]); |
---|
1709 | } |
---|
1710 | } else { |
---|
1711 | generator_=NULL; |
---|
1712 | virginGenerator_=NULL; |
---|
1713 | } |
---|
1714 | numberHeuristics_ = rhs.numberHeuristics_; |
---|
1715 | if (numberHeuristics_) { |
---|
1716 | heuristic_ = new CbcHeuristic * [numberHeuristics_]; |
---|
1717 | memcpy(heuristic_,rhs.heuristic_, |
---|
1718 | numberHeuristics_*sizeof(CbcHeuristic *)); |
---|
1719 | } else { |
---|
1720 | heuristic_=NULL; |
---|
1721 | } |
---|
1722 | for (i=0;i<numberObjects_;i++) |
---|
1723 | delete object_[i]; |
---|
1724 | delete [] object_; |
---|
1725 | numberObjects_=rhs.numberObjects_; |
---|
1726 | if (numberObjects_) { |
---|
1727 | object_ = new CbcObject * [numberObjects_]; |
---|
1728 | int i; |
---|
1729 | for (i=0;i<numberObjects_;i++) |
---|
1730 | object_[i]=(rhs.object_[i])->clone(); |
---|
1731 | } else { |
---|
1732 | object_=NULL; |
---|
1733 | } |
---|
1734 | delete [] priority_; |
---|
1735 | if (rhs.priority_) { |
---|
1736 | priority_= new int [numberObjects_]; |
---|
1737 | memcpy(priority_,rhs.priority_,numberObjects_*sizeof(int)); |
---|
1738 | } else { |
---|
1739 | priority_=NULL; |
---|
1740 | } |
---|
1741 | delete [] originalColumns_; |
---|
1742 | if (rhs.originalColumns_) { |
---|
1743 | int numberColumns = rhs.getNumCols(); |
---|
1744 | originalColumns_= new int [numberColumns]; |
---|
1745 | memcpy(originalColumns_,rhs.originalColumns_,numberColumns*sizeof(int)); |
---|
1746 | } else { |
---|
1747 | originalColumns_=NULL; |
---|
1748 | } |
---|
1749 | nodeCompare_=rhs.nodeCompare_; |
---|
1750 | delete tree_; |
---|
1751 | tree_= rhs.tree_->clone(); |
---|
1752 | branchingMethod_=rhs.branchingMethod_; |
---|
1753 | appData_=rhs.appData_; |
---|
1754 | |
---|
1755 | delete [] integerVariable_; |
---|
1756 | numberIntegers_=rhs.numberIntegers_; |
---|
1757 | if (numberIntegers_) { |
---|
1758 | integerVariable_ = new int [numberIntegers_]; |
---|
1759 | memcpy(integerVariable_,rhs.integerVariable_, |
---|
1760 | numberIntegers_*sizeof(int)); |
---|
1761 | } else { |
---|
1762 | integerVariable_ = NULL; |
---|
1763 | } |
---|
1764 | numberRowsAtContinuous_ = rhs.numberRowsAtContinuous_; |
---|
1765 | maximumNumberCuts_=rhs.maximumNumberCuts_; |
---|
1766 | phase_ = rhs.phase_; |
---|
1767 | currentNumberCuts_=rhs.currentNumberCuts_; |
---|
1768 | maximumDepth_= rhs.maximumDepth_; |
---|
1769 | delete [] addedCuts_; |
---|
1770 | delete [] walkback_; |
---|
1771 | // These are only used as temporary arrays so need not be filled |
---|
1772 | if (maximumNumberCuts_) { |
---|
1773 | addedCuts_ = new CbcCountRowCut * [maximumNumberCuts_]; |
---|
1774 | } else { |
---|
1775 | addedCuts_ = NULL; |
---|
1776 | } |
---|
1777 | nextRowCut_ = NULL; |
---|
1778 | currentNode_ = NULL; |
---|
1779 | if (maximumDepth_) |
---|
1780 | walkback_ = new CbcNodeInfo * [maximumDepth_]; |
---|
1781 | else |
---|
1782 | walkback_ = NULL; |
---|
1783 | synchronizeModel(); |
---|
1784 | } |
---|
1785 | return *this; |
---|
1786 | } |
---|
1787 | |
---|
1788 | // Destructor |
---|
1789 | CbcModel::~CbcModel () |
---|
1790 | { |
---|
1791 | if (defaultHandler_) { |
---|
1792 | delete handler_; |
---|
1793 | handler_ = NULL; |
---|
1794 | } |
---|
1795 | delete tree_; |
---|
1796 | if (ourSolver_) delete solver_; |
---|
1797 | gutsOfDestructor(); |
---|
1798 | } |
---|
1799 | // Clears out as much as possible (except solver) |
---|
1800 | void |
---|
1801 | CbcModel::gutsOfDestructor() |
---|
1802 | { |
---|
1803 | delete emptyWarmStart_ ; |
---|
1804 | emptyWarmStart_ =NULL; |
---|
1805 | delete basis_ ; |
---|
1806 | basis_ =NULL; |
---|
1807 | delete continuousSolver_; |
---|
1808 | continuousSolver_=NULL; |
---|
1809 | delete [] bestSolution_; |
---|
1810 | bestSolution_=NULL; |
---|
1811 | delete [] currentSolution_; |
---|
1812 | currentSolution_=NULL; |
---|
1813 | delete [] integerVariable_; |
---|
1814 | integerVariable_=NULL; |
---|
1815 | int i; |
---|
1816 | for (i=0;i<numberCutGenerators_;i++) { |
---|
1817 | delete generator_[i]; |
---|
1818 | delete virginGenerator_[i]; |
---|
1819 | } |
---|
1820 | delete [] generator_; |
---|
1821 | delete [] virginGenerator_; |
---|
1822 | generator_=NULL; |
---|
1823 | virginGenerator_=NULL; |
---|
1824 | for (i=0;i<numberHeuristics_;i++) |
---|
1825 | delete heuristic_[i]; |
---|
1826 | delete [] heuristic_; |
---|
1827 | heuristic_=NULL; |
---|
1828 | delete [] addedCuts_; |
---|
1829 | addedCuts_=NULL; |
---|
1830 | nextRowCut_ = NULL; |
---|
1831 | currentNode_ = NULL; |
---|
1832 | delete [] walkback_; |
---|
1833 | walkback_=NULL; |
---|
1834 | for (i=0;i<numberObjects_;i++) |
---|
1835 | delete object_[i]; |
---|
1836 | delete [] object_; |
---|
1837 | object_=NULL; |
---|
1838 | delete [] priority_; |
---|
1839 | priority_=NULL; |
---|
1840 | delete [] originalColumns_; |
---|
1841 | originalColumns_=NULL; |
---|
1842 | } |
---|
1843 | // Are there a numerical difficulties? |
---|
1844 | bool |
---|
1845 | CbcModel::isAbandoned() const |
---|
1846 | { |
---|
1847 | return status_ == 2; |
---|
1848 | } |
---|
1849 | // Is optimality proven? |
---|
1850 | bool |
---|
1851 | CbcModel::isProvenOptimal() const |
---|
1852 | { |
---|
1853 | if (!status_ && bestObjective_<1.0e30) |
---|
1854 | return true; |
---|
1855 | else |
---|
1856 | return false; |
---|
1857 | } |
---|
1858 | // Is infeasiblity proven (or none better than cutoff)? |
---|
1859 | bool |
---|
1860 | CbcModel::isProvenInfeasible() const |
---|
1861 | { |
---|
1862 | if (!status_ && bestObjective_>=1.0e30) |
---|
1863 | return true; |
---|
1864 | else |
---|
1865 | return false; |
---|
1866 | } |
---|
1867 | // Node limit reached? |
---|
1868 | bool |
---|
1869 | CbcModel::isNodeLimitReached() const |
---|
1870 | { |
---|
1871 | return numberNodes_ >= intParam_[CbcMaxNumNode]; |
---|
1872 | } |
---|
1873 | // Solution limit reached? |
---|
1874 | bool |
---|
1875 | CbcModel::isSolutionLimitReached() const |
---|
1876 | { |
---|
1877 | return numberSolutions_ >= intParam_[CbcMaxNumSol]; |
---|
1878 | } |
---|
1879 | // Set language |
---|
1880 | void |
---|
1881 | CbcModel::newLanguage(CoinMessages::Language language) |
---|
1882 | { |
---|
1883 | messages_ = CbcMessage(language); |
---|
1884 | } |
---|
1885 | void |
---|
1886 | CbcModel::setNumberStrong(int number) |
---|
1887 | { |
---|
1888 | if (number<0) |
---|
1889 | numberStrong_=0; |
---|
1890 | else |
---|
1891 | numberStrong_=number; |
---|
1892 | } |
---|
1893 | void |
---|
1894 | CbcModel::setHowOftenGlobalScan(int number) |
---|
1895 | { |
---|
1896 | if (number<-1) |
---|
1897 | howOftenGlobalScan_=0; |
---|
1898 | else |
---|
1899 | howOftenGlobalScan_=number; |
---|
1900 | } |
---|
1901 | |
---|
1902 | // Add one generator |
---|
1903 | void |
---|
1904 | CbcModel::addCutGenerator(CglCutGenerator * generator, |
---|
1905 | int howOften, const char * name, |
---|
1906 | bool normal, bool atSolution, |
---|
1907 | bool whenInfeasible,int howOftenInSub, |
---|
1908 | int whatDepth, int whatDepthInSub) |
---|
1909 | { |
---|
1910 | CbcCutGenerator ** temp = generator_; |
---|
1911 | generator_ = new CbcCutGenerator * [numberCutGenerators_+1]; |
---|
1912 | memcpy(generator_,temp,numberCutGenerators_*sizeof(CbcCutGenerator *)); |
---|
1913 | delete[] temp ; |
---|
1914 | generator_[numberCutGenerators_]= |
---|
1915 | new CbcCutGenerator(this,generator, howOften, name, |
---|
1916 | normal,atSolution,whenInfeasible,howOftenInSub, |
---|
1917 | whatDepth, whatDepthInSub); |
---|
1918 | // and before any cahnges |
---|
1919 | temp = virginGenerator_; |
---|
1920 | virginGenerator_ = new CbcCutGenerator * [numberCutGenerators_+1]; |
---|
1921 | memcpy(virginGenerator_,temp,numberCutGenerators_*sizeof(CbcCutGenerator *)); |
---|
1922 | delete[] temp ; |
---|
1923 | virginGenerator_[numberCutGenerators_++]= |
---|
1924 | new CbcCutGenerator(this,generator, howOften, name, |
---|
1925 | normal,atSolution,whenInfeasible,howOftenInSub, |
---|
1926 | whatDepth, whatDepthInSub); |
---|
1927 | |
---|
1928 | } |
---|
1929 | // Add one heuristic |
---|
1930 | void |
---|
1931 | CbcModel::addHeuristic(CbcHeuristic * generator) |
---|
1932 | { |
---|
1933 | CbcHeuristic ** temp = heuristic_; |
---|
1934 | heuristic_ = new CbcHeuristic * [numberHeuristics_+1]; |
---|
1935 | memcpy(heuristic_,temp,numberHeuristics_*sizeof(CbcHeuristic *)); |
---|
1936 | delete [] temp; |
---|
1937 | heuristic_[numberHeuristics_++]=generator->clone(); |
---|
1938 | } |
---|
1939 | |
---|
1940 | /* |
---|
1941 | The last subproblem handled by the solver is not necessarily related to the |
---|
1942 | one being recreated, so the first action is to remove all cuts from the |
---|
1943 | constraint system. Next, traverse the tree from node to the root to |
---|
1944 | determine the basis size required for this subproblem and create an empty |
---|
1945 | basis with the right capacity. Finally, traverse the tree from root to |
---|
1946 | node, adjusting bounds in the constraint system, adjusting the basis, and |
---|
1947 | collecting the cuts that must be added to the constraint system. |
---|
1948 | applyToModel does the heavy lifting. |
---|
1949 | |
---|
1950 | addCuts1 is used in contexts where all that's desired is the list of cuts: |
---|
1951 | the node is already fathomed, and we're collecting cuts so that we can |
---|
1952 | adjust reference counts as we prune nodes. Arguably the two functions |
---|
1953 | should be separated. The culprit is applyToModel, which performs cut |
---|
1954 | collection and model adjustment. |
---|
1955 | |
---|
1956 | Certainly in the contexts where all we need is a list of cuts, there's no |
---|
1957 | point in passing in a valid basis --- an empty basis will do just fine. |
---|
1958 | */ |
---|
1959 | void CbcModel::addCuts1 (CbcNode * node, CoinWarmStartBasis *&lastws) |
---|
1960 | { int i; |
---|
1961 | int nNode=0; |
---|
1962 | int numberColumns = getNumCols(); |
---|
1963 | CbcNodeInfo * nodeInfo = node->nodeInfo(); |
---|
1964 | |
---|
1965 | /* |
---|
1966 | Remove all cuts from the constraint system. |
---|
1967 | (original comment includes ``see note below for later efficiency'', but |
---|
1968 | the reference isn't clear to me). |
---|
1969 | */ |
---|
1970 | int currentNumberCuts = solver_->getNumRows()-numberRowsAtContinuous_; |
---|
1971 | int *which = new int[currentNumberCuts]; |
---|
1972 | for (i = 0 ; i < currentNumberCuts ; i++) |
---|
1973 | which[i] = i+numberRowsAtContinuous_; |
---|
1974 | solver_->deleteRows(currentNumberCuts,which); |
---|
1975 | delete [] which; |
---|
1976 | /* |
---|
1977 | Accumulate the path from node to the root in walkback_, and accumulate a |
---|
1978 | cut count in currentNumberCuts. |
---|
1979 | |
---|
1980 | original comment: when working then just unwind until where new node joins |
---|
1981 | old node (for cuts?) |
---|
1982 | */ |
---|
1983 | currentNumberCuts = 0; |
---|
1984 | while (nodeInfo) { |
---|
1985 | //printf("nNode = %d, nodeInfo = %x\n",nNode,nodeInfo); |
---|
1986 | walkback_[nNode++]=nodeInfo; |
---|
1987 | currentNumberCuts += nodeInfo->numberCuts() ; |
---|
1988 | nodeInfo = nodeInfo->parent() ; |
---|
1989 | if (nNode==maximumDepth_) { |
---|
1990 | maximumDepth_ *= 2; |
---|
1991 | CbcNodeInfo ** temp = new CbcNodeInfo * [maximumDepth_]; |
---|
1992 | for (i=0;i<nNode;i++) |
---|
1993 | temp[i] = walkback_[i]; |
---|
1994 | delete [] walkback_; |
---|
1995 | walkback_ = temp; |
---|
1996 | } |
---|
1997 | } |
---|
1998 | /* |
---|
1999 | Create an empty basis with sufficient capacity for the constraint system |
---|
2000 | we'll construct: original system plus cuts. Make sure we have capacity to |
---|
2001 | record those cuts in addedCuts_. |
---|
2002 | |
---|
2003 | The method of adjusting the basis at a FullNodeInfo object (the root, for |
---|
2004 | example) is to use a copy constructor to duplicate the basis held in the |
---|
2005 | nodeInfo, then resize it and return the new basis object. Guaranteed, |
---|
2006 | lastws will point to a different basis when it returns. We pass in a basis |
---|
2007 | because we need the parameter to return the allocated basis, and it's an |
---|
2008 | easy way to pass in the size. But we take a hit for memory allocation. |
---|
2009 | */ |
---|
2010 | currentNumberCuts_=currentNumberCuts; |
---|
2011 | if (currentNumberCuts >= maximumNumberCuts_) { |
---|
2012 | maximumNumberCuts_ = currentNumberCuts; |
---|
2013 | delete [] addedCuts_; |
---|
2014 | addedCuts_ = new CbcCountRowCut * [maximumNumberCuts_]; |
---|
2015 | } |
---|
2016 | lastws->setSize(numberColumns,numberRowsAtContinuous_+currentNumberCuts); |
---|
2017 | /* |
---|
2018 | This last bit of code traverses the path collected in walkback_ from the |
---|
2019 | root back to node. At the end of the loop, |
---|
2020 | * lastws will be an appropriate basis for node; |
---|
2021 | * variable bounds in the constraint system will be set to be correct for |
---|
2022 | node; and |
---|
2023 | * addedCuts_ will be set to a list of cuts that need to be added to the |
---|
2024 | constraint system at node. |
---|
2025 | applyToModel does all the heavy lifting. |
---|
2026 | */ |
---|
2027 | currentNumberCuts=0; |
---|
2028 | while (nNode) { |
---|
2029 | --nNode; |
---|
2030 | walkback_[nNode]->applyToModel(this,lastws,addedCuts_,currentNumberCuts); |
---|
2031 | } |
---|
2032 | } |
---|
2033 | |
---|
2034 | /* |
---|
2035 | adjustCuts might be a better name: If the node is feasible, we sift through |
---|
2036 | the cuts we've collected, add the ones that are tight and omit the ones that |
---|
2037 | are loose. If the node is infeasible, we just adjust the reference counts to |
---|
2038 | reflect that we're about to prune this node and its descendants. |
---|
2039 | |
---|
2040 | The reason we need to pass in lastws is that OsiClp automagically corrects |
---|
2041 | the basis when it deletes constraints. So when all cuts are stripped within |
---|
2042 | addCuts1, we lose their basis entries, hence the ability to determine if |
---|
2043 | they are loose or tight. The question is whether we really need to pass in |
---|
2044 | a basis or if we can capture it here. I'm thinking we can capture it here |
---|
2045 | and pass it back out if required. |
---|
2046 | */ |
---|
2047 | int CbcModel::addCuts (CbcNode *node, CoinWarmStartBasis *&lastws) |
---|
2048 | { |
---|
2049 | /* |
---|
2050 | addCuts1 performs step 1 of restoring the subproblem at this node; see the |
---|
2051 | comments there. |
---|
2052 | */ |
---|
2053 | addCuts1(node,lastws); |
---|
2054 | int i; |
---|
2055 | int numberColumns = getNumCols(); |
---|
2056 | CbcNodeInfo * nodeInfo = node->nodeInfo(); |
---|
2057 | double cutoff = getCutoff() ; |
---|
2058 | int currentNumberCuts=currentNumberCuts_; |
---|
2059 | /* |
---|
2060 | If the node can't be fathomed by bound, reinstall tight cuts in the |
---|
2061 | constraint system. |
---|
2062 | */ |
---|
2063 | if (node->objectiveValue() < cutoff) |
---|
2064 | { int numberToAdd = 0; |
---|
2065 | const OsiRowCut * * addCuts; |
---|
2066 | if (currentNumberCuts == 0) |
---|
2067 | addCuts = NULL; |
---|
2068 | else |
---|
2069 | addCuts = new const OsiRowCut * [currentNumberCuts]; |
---|
2070 | # ifdef CHECK_CUT_COUNTS |
---|
2071 | printf("addCuts: expanded basis; rows %d+%d\n", |
---|
2072 | numberRowsAtContinuous_,currentNumberCuts); |
---|
2073 | lastws->print(); |
---|
2074 | # endif |
---|
2075 | /* |
---|
2076 | Adjust the basis and constraint system so that we retain only active cuts. |
---|
2077 | There are three steps: |
---|
2078 | 1) Scan the basis. If the logical associated with the cut is basic, it's |
---|
2079 | loose and we drop it. The status of the logical for tight cuts is |
---|
2080 | written back into the status array, compressing as we go. |
---|
2081 | 2) Resize the basis to fit the number of active cuts, stash a clone, and |
---|
2082 | install with a call to setWarmStart(). |
---|
2083 | 3) Install the tight cuts into the constraint system (applyRowCuts). |
---|
2084 | |
---|
2085 | TODO: After working through the code in createInfo, I'm more comfortable if |
---|
2086 | inactive cuts are retained in lastws. So, instead of cloning |
---|
2087 | lastws into basis_ after the compression loop, do it ahead of time |
---|
2088 | and then recover lastws from basis_ after the setWarmStart(). |
---|
2089 | (Minimal code change :-). See CbcNode::createInfo for more. |
---|
2090 | */ |
---|
2091 | if (basis_) delete basis_ ; |
---|
2092 | basis_= dynamic_cast<CoinWarmStartBasis *>(lastws->clone()) ; |
---|
2093 | for (i=0;i<currentNumberCuts;i++) { |
---|
2094 | CoinWarmStartBasis::Status status = |
---|
2095 | lastws->getArtifStatus(i+numberRowsAtContinuous_); |
---|
2096 | if (status != CoinWarmStartBasis::basic&&addedCuts_[i]) { |
---|
2097 | # ifdef CHECK_CUT_COUNTS |
---|
2098 | printf("Using cut %d %x as row %d\n",i,addedCuts_[i], |
---|
2099 | numberRowsAtContinuous_+numberToAdd); |
---|
2100 | # endif |
---|
2101 | lastws->setArtifStatus(numberToAdd+numberRowsAtContinuous_,status); |
---|
2102 | addCuts[numberToAdd++] = new OsiRowCut(*addedCuts_[i]); |
---|
2103 | } else { |
---|
2104 | # ifdef CHECK_CUT_COUNTS |
---|
2105 | printf("Dropping cut %d %x\n",i,addedCuts_[i]); |
---|
2106 | # endif |
---|
2107 | addedCuts_[i]=NULL; |
---|
2108 | } |
---|
2109 | } |
---|
2110 | int numberRowsNow=numberRowsAtContinuous_+numberToAdd; |
---|
2111 | lastws->resize(numberRowsNow,numberColumns); |
---|
2112 | #ifdef FULL_DEBUG |
---|
2113 | printf("addCuts: stripped basis; rows %d + %d\n", |
---|
2114 | numberRowsAtContinuous_,numberToAdd); |
---|
2115 | lastws->print(); |
---|
2116 | #endif |
---|
2117 | /* |
---|
2118 | Apply the cuts and set the basis in the solver. |
---|
2119 | */ |
---|
2120 | solver_->applyRowCuts(numberToAdd,addCuts); |
---|
2121 | solver_->setWarmStart(lastws); |
---|
2122 | /* |
---|
2123 | TODO: Undo the debugging change. Delete lastws and assign basis_. |
---|
2124 | */ |
---|
2125 | delete lastws ; |
---|
2126 | lastws = basis_ ; |
---|
2127 | basis_ = 0 ; |
---|
2128 | |
---|
2129 | #if 0 |
---|
2130 | if ((numberNodes_%printFrequency_)==0) { |
---|
2131 | printf("Objective %g, depth %d, unsatisfied %d\n", |
---|
2132 | node->objectiveValue(), |
---|
2133 | node->depth(),node->numberUnsatisfied()); |
---|
2134 | } |
---|
2135 | #endif |
---|
2136 | /* |
---|
2137 | Clean up and we're out of here. |
---|
2138 | */ |
---|
2139 | for (i=0;i<numberToAdd;i++) |
---|
2140 | delete addCuts[i]; |
---|
2141 | delete [] addCuts; |
---|
2142 | numberNodes_++; |
---|
2143 | return 0; |
---|
2144 | } |
---|
2145 | /* |
---|
2146 | This node has been fathomed by bound as we try to revive it out of the live |
---|
2147 | set. Adjust the cut reference counts to reflect that we no longer need to |
---|
2148 | explore the remaining branch arms, hence they will no longer reference any |
---|
2149 | cuts. Cuts whose reference count falls to zero are deleted. |
---|
2150 | */ |
---|
2151 | else |
---|
2152 | { int i; |
---|
2153 | int numberLeft = nodeInfo->numberBranchesLeft(); |
---|
2154 | for (i = 0 ; i < currentNumberCuts ; i++) |
---|
2155 | { if (addedCuts_[i]) |
---|
2156 | { if (!addedCuts_[i]->decrement(numberLeft)) |
---|
2157 | { delete addedCuts_[i]; |
---|
2158 | addedCuts_[i] = NULL; } } } |
---|
2159 | return 1 ; } |
---|
2160 | } |
---|
2161 | |
---|
2162 | |
---|
2163 | /* |
---|
2164 | Perform reduced cost fixing on integer variables. |
---|
2165 | |
---|
2166 | The variables in question are already nonbasic at bound. We're just nailing |
---|
2167 | down the current situation. |
---|
2168 | */ |
---|
2169 | |
---|
2170 | void CbcModel::reducedCostFix () |
---|
2171 | |
---|
2172 | { double cutoff = getCutoff() ; |
---|
2173 | double direction = solver_->getObjSense() ; |
---|
2174 | double gap = cutoff - solver_->getObjValue()*direction ; |
---|
2175 | double integerTolerance = getDblParam(CbcIntegerTolerance) ; |
---|
2176 | |
---|
2177 | const double *lower = solver_->getColLower() ; |
---|
2178 | const double *upper = solver_->getColUpper() ; |
---|
2179 | const double *solution = solver_->getColSolution() ; |
---|
2180 | const double *reducedCost = solver_->getReducedCost() ; |
---|
2181 | |
---|
2182 | int numberFixed = 0 ; |
---|
2183 | for (int i = 0 ; i < numberIntegers_ ; i++) |
---|
2184 | { int iColumn = integerVariable_[i] ; |
---|
2185 | double djValue = direction*reducedCost[iColumn] ; |
---|
2186 | if (upper[iColumn]-lower[iColumn] > integerTolerance) |
---|
2187 | { if (solution[iColumn] < lower[iColumn]+integerTolerance && djValue > gap) |
---|
2188 | { solver_->setColUpper(iColumn,lower[iColumn]) ; |
---|
2189 | numberFixed++ ; } |
---|
2190 | else |
---|
2191 | if (solution[iColumn] > upper[iColumn]-integerTolerance && -djValue > gap) |
---|
2192 | { solver_->setColLower(iColumn,upper[iColumn]) ; |
---|
2193 | numberFixed++ ; } } } |
---|
2194 | |
---|
2195 | return ; } |
---|
2196 | |
---|
2197 | |
---|
2198 | |
---|
2199 | |
---|
2200 | /** Solve the model using cuts |
---|
2201 | |
---|
2202 | This version takes off redundant cuts from node. |
---|
2203 | Returns true if feasible. |
---|
2204 | |
---|
2205 | \todo |
---|
2206 | Why do I need to resolve the problem? What has been done between the last |
---|
2207 | relaxation and calling solveWithCuts? |
---|
2208 | |
---|
2209 | If numberTries == 0 then user did not want any cuts. |
---|
2210 | */ |
---|
2211 | |
---|
2212 | bool |
---|
2213 | CbcModel::solveWithCuts (OsiCuts &cuts, int numberTries, CbcNode *node, |
---|
2214 | int &numberOldActiveCuts, int &numberNewCuts, |
---|
2215 | int &maximumWhich, int *&whichGenerator) |
---|
2216 | /* |
---|
2217 | Parameters: |
---|
2218 | numberTries: (i) the maximum number of iterations for this round of cut |
---|
2219 | generation; if negative then we don't mind if drop is tiny. |
---|
2220 | |
---|
2221 | cuts: (o) all cuts generated in this round of cut generation |
---|
2222 | whichGenerator: (i/o) whichGenerator[i] is loaded with the index of the |
---|
2223 | generator that produced cuts[i]; reallocated as |
---|
2224 | required |
---|
2225 | numberOldActiveCuts: (o) the number of active cuts at this node from |
---|
2226 | previous rounds of cut generation |
---|
2227 | numberNewCuts: (o) the number of cuts produced in this round of cut |
---|
2228 | generation |
---|
2229 | maximumWhich: (i/o) capacity of whichGenerator; may be updated if |
---|
2230 | whichGenerator grows. |
---|
2231 | |
---|
2232 | node: (currently unused) |
---|
2233 | */ |
---|
2234 | |
---|
2235 | |
---|
2236 | { bool feasible = true ; |
---|
2237 | int lastNumberCuts = 0 ; |
---|
2238 | double lastObjective = -1.0e100 ; |
---|
2239 | int violated = 0 ; |
---|
2240 | int numberRowsAtStart = solver_->getNumRows() ; |
---|
2241 | int numberColumns = solver_->getNumCols() ; |
---|
2242 | |
---|
2243 | numberOldActiveCuts = numberRowsAtStart-numberRowsAtContinuous_ ; |
---|
2244 | numberNewCuts = 0 ; |
---|
2245 | |
---|
2246 | # ifdef CBC_DEBUG |
---|
2247 | /* |
---|
2248 | See OsiRowCutDebugger for details. In a nutshell, make sure that current |
---|
2249 | variable values do not conflict with a known optimal solution. (Obviously |
---|
2250 | this can be fooled when there are multiple solutions.) |
---|
2251 | */ |
---|
2252 | bool onOptimalPath = false ; |
---|
2253 | const OsiRowCutDebugger *debugger = solver_->getRowCutDebugger() ; |
---|
2254 | if (debugger) |
---|
2255 | onOptimalPath = (debugger->onOptimalPath(*solver_)) ; |
---|
2256 | # endif |
---|
2257 | /* |
---|
2258 | Resolve the problem. If we've lost feasibility, might as well bail out right |
---|
2259 | after the debug stuff. |
---|
2260 | */ |
---|
2261 | feasible = resolve() ; |
---|
2262 | |
---|
2263 | #ifdef CBC_DEBUG |
---|
2264 | if (feasible) |
---|
2265 | { printf("Obj value %g (%s) %d rows\n",solver_->getObjValue(), |
---|
2266 | (solver_->isProvenOptimal())?"proven":"unproven", |
---|
2267 | solver_->getNumRows()) ; } |
---|
2268 | else |
---|
2269 | { printf("Infeasible %d rows\n",solver_->getNumRows()) ; } |
---|
2270 | /* |
---|
2271 | If the RowCutDebugger said we were compatible with the optimal solution, |
---|
2272 | and now we're suddenly infeasible, we might be confused. Then again, we |
---|
2273 | may have fathomed by bound, heading for a rediscovery of an optimal solution. |
---|
2274 | */ |
---|
2275 | if (onOptimalPath && !solver_->isDualObjectiveLimitReached()) { |
---|
2276 | if (!feasible) { |
---|
2277 | solver_->writeMps("infeas"); |
---|
2278 | CoinWarmStartBasis *slack = |
---|
2279 | dynamic_cast<CoinWarmStartBasis *>(solver_->getEmptyWarmStart()) ; |
---|
2280 | solver_->setWarmStart(slack); |
---|
2281 | delete slack ; |
---|
2282 | solver_->setHintParam(OsiDoReducePrint,false,OsiHintDo,0) ; |
---|
2283 | solver_->initialSolve(); |
---|
2284 | } |
---|
2285 | assert(feasible) ; |
---|
2286 | } |
---|
2287 | # endif |
---|
2288 | |
---|
2289 | if (!feasible) return (false) ; |
---|
2290 | // Return at once if numberTries zero |
---|
2291 | if (!numberTries) { |
---|
2292 | cuts=OsiCuts(); |
---|
2293 | numberNewCuts=0; |
---|
2294 | return true; |
---|
2295 | } |
---|
2296 | /* |
---|
2297 | Do reduced cost fixing, and then grab the primal solution and bounds vectors. |
---|
2298 | */ |
---|
2299 | reducedCostFix() ; |
---|
2300 | const double *lower = solver_->getColLower() ; |
---|
2301 | const double *upper = solver_->getColUpper() ; |
---|
2302 | const double *solution = solver_->getColSolution() ; |
---|
2303 | /* |
---|
2304 | Set up for at most numberTries rounds of cut generation. If numberTries is |
---|
2305 | negative, we'll ignore the minimumDrop_ cutoff and keep generating cuts for |
---|
2306 | the specified number of rounds. |
---|
2307 | */ |
---|
2308 | double minimumDrop = minimumDrop_ ; |
---|
2309 | if (numberTries<0) |
---|
2310 | { numberTries = -numberTries ; |
---|
2311 | minimumDrop = -1.0 ; } |
---|
2312 | /* |
---|
2313 | Is it time to scan the cuts in order to remove redundant cuts? If so, set |
---|
2314 | up to do it. |
---|
2315 | */ |
---|
2316 | # define SCANCUTS 100 |
---|
2317 | int *countColumnCuts = NULL ; |
---|
2318 | // Always accumulate row cut counts |
---|
2319 | int * countRowCuts =new int[numberCutGenerators_+numberHeuristics_] ; |
---|
2320 | memset(countRowCuts,0, |
---|
2321 | (numberCutGenerators_+numberHeuristics_)*sizeof(int)) ; |
---|
2322 | bool fullScan = false ; |
---|
2323 | if ((numberNodes_%SCANCUTS) == 0) |
---|
2324 | { fullScan = true ; |
---|
2325 | countColumnCuts = new int[numberCutGenerators_+numberHeuristics_] ; |
---|
2326 | memset(countColumnCuts,0, |
---|
2327 | (numberCutGenerators_+numberHeuristics_)*sizeof(int)) ; } |
---|
2328 | |
---|
2329 | double direction = solver_->getObjSense() ; |
---|
2330 | double startObjective = solver_->getObjValue()*direction ; |
---|
2331 | |
---|
2332 | currentPassNumber_ = 0 ; |
---|
2333 | double primalTolerance = 1.0e-7 ; |
---|
2334 | /* |
---|
2335 | Begin cut generation loop. Cuts generated during each iteration are |
---|
2336 | collected in theseCuts. The loop can be divided into four phases: |
---|
2337 | 1) Prep: Fix variables using reduced cost. In the first iteration only, |
---|
2338 | consider scanning globalCuts_ and activating any applicable cuts. |
---|
2339 | 2) Cut Generation: Call each generator and heuristic registered in the |
---|
2340 | generator_ and heuristic_ arrays. Newly generated global cuts are |
---|
2341 | copied to globalCuts_ at this time. |
---|
2342 | 3) Cut Installation and Reoptimisation: Install column and row cuts in |
---|
2343 | the solver. Copy row cuts to cuts (parameter). Reoptimise. |
---|
2344 | 4) Cut Purging: takeOffCuts() removes inactive cuts from the solver, and |
---|
2345 | does the necessary bookkeeping in the model. |
---|
2346 | */ |
---|
2347 | do |
---|
2348 | { currentPassNumber_++ ; |
---|
2349 | numberTries-- ; |
---|
2350 | OsiCuts theseCuts ; |
---|
2351 | /* |
---|
2352 | Scan previously generated global column and row cuts to see if any are |
---|
2353 | useful. |
---|
2354 | I can't see why this code |
---|
2355 | needs its own copy of the primal solution. Removed the dec'l. |
---|
2356 | */ |
---|
2357 | int numberViolated=0; |
---|
2358 | if (currentPassNumber_ == 1 && howOftenGlobalScan_ > 0 && |
---|
2359 | (numberNodes_%howOftenGlobalScan_) == 0) |
---|
2360 | { int numberCuts = globalCuts_.sizeColCuts() ; |
---|
2361 | int i; |
---|
2362 | for ( i = 0 ; i < numberCuts ; i++) |
---|
2363 | { const OsiColCut *thisCut = globalCuts_.colCutPtr(i) ; |
---|
2364 | if (thisCut->violated(solution)>primalTolerance) { |
---|
2365 | printf("Global cut added - violation %g\n", |
---|
2366 | thisCut->violated(solution)) ; |
---|
2367 | whichGenerator[numberViolated++]=-1; |
---|
2368 | theseCuts.insert(*thisCut) ; |
---|
2369 | } |
---|
2370 | } |
---|
2371 | numberCuts = globalCuts_.sizeRowCuts() ; |
---|
2372 | for ( i = 0;i<numberCuts;i++) { |
---|
2373 | const OsiRowCut * thisCut = globalCuts_.rowCutPtr(i) ; |
---|
2374 | if (thisCut->violated(solution)>primalTolerance) { |
---|
2375 | //printf("Global cut added - violation %g\n", |
---|
2376 | // thisCut->violated(solution)) ; |
---|
2377 | whichGenerator[numberViolated++]=-1; |
---|
2378 | theseCuts.insert(*thisCut) ; |
---|
2379 | } |
---|
2380 | } |
---|
2381 | numberGlobalViolations_+=numberViolated; |
---|
2382 | } |
---|
2383 | /* |
---|
2384 | Generate new cuts (global and/or local) and/or apply heuristics. If |
---|
2385 | CglProbing is used, then it should be first as it can fix continuous |
---|
2386 | variables. |
---|
2387 | |
---|
2388 | At present, CglProbing is the only case where generateCuts will return |
---|
2389 | true. generateCuts actually modifies variable bounds in the solver when |
---|
2390 | CglProbing indicates that it can fix a variable. Reoptimisation is required |
---|
2391 | to take full advantage. |
---|
2392 | */ |
---|
2393 | if (nextRowCut_) { |
---|
2394 | // branch was a cut - add it |
---|
2395 | theseCuts.insert(*nextRowCut_); |
---|
2396 | //nextRowCut_->print(); |
---|
2397 | const OsiRowCut * cut=nextRowCut_; |
---|
2398 | const double * solution = solver_->getColSolution(); |
---|
2399 | double lb = cut->lb(); |
---|
2400 | double ub = cut->ub(); |
---|
2401 | int n=cut->row().getNumElements(); |
---|
2402 | const int * column = cut->row().getIndices(); |
---|
2403 | const double * element = cut->row().getElements(); |
---|
2404 | double sum=0.0; |
---|
2405 | for (int i=0;i<n;i++) { |
---|
2406 | int iColumn = column[i]; |
---|
2407 | double value = element[i]; |
---|
2408 | //if (solution[iColumn]>1.0e-7) |
---|
2409 | //printf("value of %d is %g\n",iColumn,solution[iColumn]); |
---|
2410 | sum += value * solution[iColumn]; |
---|
2411 | } |
---|
2412 | delete nextRowCut_; |
---|
2413 | nextRowCut_=NULL; |
---|
2414 | if (handler_->logLevel()>1) |
---|
2415 | printf("applying branch cut, sum is %g, bounds %g %g\n",sum,lb,ub); |
---|
2416 | // set whichgenerator (also serves as marker to say don't delete0 |
---|
2417 | whichGenerator[numberViolated++]=-2; |
---|
2418 | } |
---|
2419 | double * newSolution = new double [numberColumns] ; |
---|
2420 | double heuristicValue = getCutoff() ; |
---|
2421 | int found = -1; // no solution found |
---|
2422 | |
---|
2423 | for (int i = 0;i<numberCutGenerators_+numberHeuristics_;i++) { |
---|
2424 | int numberRowCutsBefore = theseCuts.sizeRowCuts() ; |
---|
2425 | int numberColumnCutsBefore = theseCuts.sizeColCuts() ; |
---|
2426 | if (i<numberCutGenerators_) { |
---|
2427 | if (generator_[i]->normal()) { |
---|
2428 | bool mustResolve = |
---|
2429 | generator_[i]->generateCuts(theseCuts,fullScan,node) ; |
---|
2430 | #ifdef CBC_DEBUG |
---|
2431 | { |
---|
2432 | int numberRowCutsAfter = theseCuts.sizeRowCuts() ; |
---|
2433 | int k ; |
---|
2434 | for (k = numberRowCutsBefore;k<numberRowCutsAfter;k++) { |
---|
2435 | OsiRowCut thisCut = theseCuts.rowCut(k) ; |
---|
2436 | /* check size of elements. |
---|
2437 | We can allow smaller but this helsp debug generators as it |
---|
2438 | is unsafe to have small elements */ |
---|
2439 | int n=thisCut.row().getNumElements(); |
---|
2440 | const int * column = thisCut.row().getIndices(); |
---|
2441 | const double * element = thisCut.row().getElements(); |
---|
2442 | for (int i=0;i<n;i++) { |
---|
2443 | int iColumn = column[i]; |
---|
2444 | double value = element[i]; |
---|
2445 | assert(fabs(value)>1.0e-12); |
---|
2446 | } |
---|
2447 | } |
---|
2448 | } |
---|
2449 | #endif |
---|
2450 | if (mustResolve) { |
---|
2451 | feasible = resolve() ; |
---|
2452 | # ifdef CBC_DEBUG |
---|
2453 | debugger = solver_->getRowCutDebugger() ; |
---|
2454 | if (debugger) |
---|
2455 | onOptimalPath = (debugger->onOptimalPath(*solver_)) ; |
---|
2456 | else |
---|
2457 | onOptimalPath=false; |
---|
2458 | if (onOptimalPath && !solver_->isDualObjectiveLimitReached()) |
---|
2459 | assert(feasible) ; |
---|
2460 | # endif |
---|
2461 | if (!feasible) |
---|
2462 | break ; |
---|
2463 | } |
---|
2464 | } |
---|
2465 | } else { |
---|
2466 | // see if heuristic will do anything |
---|
2467 | double saveValue = heuristicValue ; |
---|
2468 | int ifSol = |
---|
2469 | heuristic_[i-numberCutGenerators_]->solution(heuristicValue, |
---|
2470 | newSolution, |
---|
2471 | theseCuts) ; |
---|
2472 | if (ifSol>0) { |
---|
2473 | // better solution found |
---|
2474 | found = i ; |
---|
2475 | } else if (ifSol<0) { |
---|
2476 | heuristicValue = saveValue ; |
---|
2477 | } |
---|
2478 | } |
---|
2479 | int numberRowCutsAfter = theseCuts.sizeRowCuts() ; |
---|
2480 | int numberColumnCutsAfter = theseCuts.sizeColCuts() ; |
---|
2481 | |
---|
2482 | #ifdef CBC_DEBUG |
---|
2483 | if (onOptimalPath) { |
---|
2484 | int k ; |
---|
2485 | for (k = numberRowCutsBefore;k<numberRowCutsAfter;k++) { |
---|
2486 | OsiRowCut thisCut = theseCuts.rowCut(k) ; |
---|
2487 | assert(!debugger->invalidCut(thisCut)) ; |
---|
2488 | } |
---|
2489 | } |
---|
2490 | #endif |
---|
2491 | |
---|
2492 | /* |
---|
2493 | The cut generator/heuristic has done its thing, and maybe it generated some |
---|
2494 | cuts and/or a new solution. Do a bit of bookkeeping: load |
---|
2495 | whichGenerator[i] with the index of the generator responsible for a cut, |
---|
2496 | and place cuts flagged as global in the global cut pool for the model. |
---|
2497 | |
---|
2498 | lastNumberCuts is the sum of cuts added in previous iterations; it's the |
---|
2499 | offset to the proper starting position in whichGenerator. |
---|
2500 | |
---|
2501 | TODO: Why is whichGenerator increased to 2*maximumWhich when it grows? |
---|
2502 | */ |
---|
2503 | int numberBefore = |
---|
2504 | numberRowCutsBefore+numberColumnCutsBefore+lastNumberCuts ; |
---|
2505 | int numberAfter = |
---|
2506 | numberRowCutsAfter+numberColumnCutsAfter+lastNumberCuts ; |
---|
2507 | if (numberAfter > maximumWhich) { |
---|
2508 | maximumWhich = CoinMax(maximumWhich*2+100,numberAfter) ; |
---|
2509 | int * temp = new int[2*maximumWhich] ; |
---|
2510 | memcpy(temp,whichGenerator,numberBefore*sizeof(int)) ; |
---|
2511 | delete [] whichGenerator ; |
---|
2512 | whichGenerator = temp ; |
---|
2513 | } |
---|
2514 | int j ; |
---|
2515 | if (fullScan) { |
---|
2516 | // counts |
---|
2517 | countColumnCuts[i] += numberColumnCutsAfter-numberColumnCutsBefore ; |
---|
2518 | } |
---|
2519 | countRowCuts[i] += numberRowCutsAfter-numberRowCutsBefore ; |
---|
2520 | |
---|
2521 | for (j = numberRowCutsBefore;j<numberRowCutsAfter;j++) { |
---|
2522 | whichGenerator[numberBefore++] = i ; |
---|
2523 | const OsiRowCut * thisCut = theseCuts.rowCutPtr(j) ; |
---|
2524 | if (thisCut->lb()>thisCut->ub()) |
---|
2525 | violated=-2; // sub-problem is infeasible |
---|
2526 | if (thisCut->globallyValid()) { |
---|
2527 | // add to global list |
---|
2528 | globalCuts_.insert(*thisCut) ; |
---|
2529 | } |
---|
2530 | } |
---|
2531 | for (j = numberColumnCutsBefore;j<numberColumnCutsAfter;j++) { |
---|
2532 | whichGenerator[numberBefore++] = i ; |
---|
2533 | const OsiColCut * thisCut = theseCuts.colCutPtr(j) ; |
---|
2534 | if (thisCut->globallyValid()) { |
---|
2535 | // add to global list |
---|
2536 | globalCuts_.insert(*thisCut) ; |
---|
2537 | } |
---|
2538 | } |
---|
2539 | } |
---|
2540 | /* |
---|
2541 | End of the loop to exercise each generator/heuristic. |
---|
2542 | |
---|
2543 | Did any of the heuristics turn up a new solution? Record it before we free |
---|
2544 | the vector. |
---|
2545 | */ |
---|
2546 | if (found >= 0) |
---|
2547 | { |
---|
2548 | phase_=4; |
---|
2549 | setBestSolution(CBC_ROUNDING,heuristicValue,newSolution) ; } |
---|
2550 | delete [] newSolution ; |
---|
2551 | |
---|
2552 | #if 0 |
---|
2553 | // switch on to get all cuts printed |
---|
2554 | theseCuts.printCuts() ; |
---|
2555 | #endif |
---|
2556 | int numberColumnCuts = theseCuts.sizeColCuts() ; |
---|
2557 | int numberRowCuts = theseCuts.sizeRowCuts() ; |
---|
2558 | if (violated>=0) |
---|
2559 | violated = numberRowCuts + numberColumnCuts ; |
---|
2560 | /* |
---|
2561 | Apply column cuts (aka bound tightening). This may be partially redundant |
---|
2562 | for column cuts returned by CglProbing, as generateCuts installs bounds |
---|
2563 | from CglProbing when it determines it can fix a variable. |
---|
2564 | |
---|
2565 | TODO: Looks like the use of violated has evolved. The value set above is |
---|
2566 | completely ignored. All that's left is violated == -1 indicates some |
---|
2567 | cut is violated, violated == -2 indicates infeasibility. Only |
---|
2568 | infeasibility warrants exceptional action. |
---|
2569 | |
---|
2570 | TODO: Strikes me that this code will fail to detect infeasibility, because |
---|
2571 | the breaks escape the inner loops but the outer loop keeps going. |
---|
2572 | Infeasibility in an early cut will be overwritten if a later cut is |
---|
2573 | merely violated. |
---|
2574 | */ |
---|
2575 | if (numberColumnCuts) { |
---|
2576 | |
---|
2577 | #ifdef CBC_DEBUG |
---|
2578 | double * oldLower = new double [numberColumns] ; |
---|
2579 | double * oldUpper = new double [numberColumns] ; |
---|
2580 | memcpy(oldLower,lower,numberColumns*sizeof(double)) ; |
---|
2581 | memcpy(oldUpper,upper,numberColumns*sizeof(double)) ; |
---|
2582 | #endif |
---|
2583 | |
---|
2584 | double integerTolerance = getDblParam(CbcIntegerTolerance) ; |
---|
2585 | for (int i = 0;i<numberColumnCuts;i++) { |
---|
2586 | const OsiColCut * thisCut = theseCuts.colCutPtr(i) ; |
---|
2587 | const CoinPackedVector & lbs = thisCut->lbs() ; |
---|
2588 | const CoinPackedVector & ubs = thisCut->ubs() ; |
---|
2589 | int j ; |
---|
2590 | int n ; |
---|
2591 | const int * which ; |
---|
2592 | const double * values ; |
---|
2593 | n = lbs.getNumElements() ; |
---|
2594 | which = lbs.getIndices() ; |
---|
2595 | values = lbs.getElements() ; |
---|
2596 | for (j = 0;j<n;j++) { |
---|
2597 | int iColumn = which[j] ; |
---|
2598 | double value = solution[iColumn] ; |
---|
2599 | #if CBC_DEBUG>1 |
---|
2600 | printf("%d %g %g %g %g\n",iColumn,oldLower[iColumn], |
---|
2601 | solution[iColumn],oldUpper[iColumn],values[j]) ; |
---|
2602 | #endif |
---|
2603 | solver_->setColLower(iColumn,values[j]) ; |
---|
2604 | if (value<values[j]-integerTolerance) |
---|
2605 | violated = -1 ; |
---|
2606 | if (values[j]>upper[iColumn]+integerTolerance) { |
---|
2607 | // infeasible |
---|
2608 | violated = -2 ; |
---|
2609 | break ; |
---|
2610 | } |
---|
2611 | } |
---|
2612 | n = ubs.getNumElements() ; |
---|
2613 | which = ubs.getIndices() ; |
---|
2614 | values = ubs.getElements() ; |
---|
2615 | for (j = 0;j<n;j++) { |
---|
2616 | int iColumn = which[j] ; |
---|
2617 | double value = solution[iColumn] ; |
---|
2618 | #if CBC_DEBUG>1 |
---|
2619 | printf("%d %g %g %g %g\n",iColumn,oldLower[iColumn], |
---|
2620 | solution[iColumn],oldUpper[iColumn],values[j]) ; |
---|
2621 | #endif |
---|
2622 | solver_->setColUpper(iColumn,values[j]) ; |
---|
2623 | if (value>values[j]+integerTolerance) |
---|
2624 | violated = -1 ; |
---|
2625 | if (values[j]<lower[iColumn]-integerTolerance) { |
---|
2626 | // infeasible |
---|
2627 | violated = -2 ; |
---|
2628 | break ; |
---|
2629 | } |
---|
2630 | } |
---|
2631 | } |
---|
2632 | #ifdef CBC_DEBUG |
---|
2633 | delete [] oldLower ; |
---|
2634 | delete [] oldUpper ; |
---|
2635 | #endif |
---|
2636 | } |
---|
2637 | /* |
---|
2638 | End installation of column cuts. The break here escapes the numberTries |
---|
2639 | loop. |
---|
2640 | */ |
---|
2641 | if (violated == -2||!feasible) { |
---|
2642 | // infeasible |
---|
2643 | feasible = false ; |
---|
2644 | violated = -2; |
---|
2645 | if (!numberNodes_) |
---|
2646 | messageHandler()->message(CBC_INFEAS, |
---|
2647 | messages()) |
---|
2648 | << CoinMessageEol ; |
---|
2649 | break ; |
---|
2650 | } |
---|
2651 | /* |
---|
2652 | Now apply the row (constraint) cuts. This is a bit more work because we need |
---|
2653 | to obtain and augment the current basis. |
---|
2654 | |
---|
2655 | TODO: Why do this work, if there are no row cuts? The current basis will do |
---|
2656 | just fine. |
---|
2657 | */ |
---|
2658 | int numberRowsNow = solver_->getNumRows() ; |
---|
2659 | assert(numberRowsNow == numberRowsAtStart+lastNumberCuts) ; |
---|
2660 | int numberToAdd = theseCuts.sizeRowCuts() ; |
---|
2661 | numberNewCuts = lastNumberCuts+numberToAdd ; |
---|
2662 | /* |
---|
2663 | Get a basis by asking the solver for warm start information. Resize it |
---|
2664 | (retaining the basis) so it can accommodate the cuts. |
---|
2665 | */ |
---|
2666 | delete basis_ ; |
---|
2667 | basis_ = dynamic_cast<CoinWarmStartBasis*>(solver_->getWarmStart()) ; |
---|
2668 | assert(basis_ != NULL); // make sure not volume |
---|
2669 | basis_->resize(numberRowsAtStart+numberNewCuts,numberColumns) ; |
---|
2670 | /* |
---|
2671 | Now actually add the row cuts and reoptimise. |
---|
2672 | |
---|
2673 | Install the cuts in the solver using applyRowCuts and |
---|
2674 | augment the basis with the corresponding slack. We also add each row cut to |
---|
2675 | the set of row cuts (cuts.insert()) supplied as a parameter. The new basis |
---|
2676 | must be set with setWarmStart(). |
---|
2677 | |
---|
2678 | TODO: It's not clear to me why we can't separate this into two sections. |
---|
2679 | The first would add the row cuts, and be executed only if row cuts |
---|
2680 | need to be installed. The second would call resolve() and would be |
---|
2681 | executed if either row or column cuts have been installed. |
---|
2682 | |
---|
2683 | TODO: Seems to me the original code could allocate addCuts with size 0, if |
---|
2684 | numberRowCuts was 0 and numberColumnCuts was nonzero. That might |
---|
2685 | explain the memory fault noted in the comment by AJK. Unfortunately, |
---|
2686 | just commenting out the delete[] results in massive memory leaks. Try |
---|
2687 | a revision to separate the row cut case. Why do we need addCuts at |
---|
2688 | all? A typing issue, apparently: OsiCut vs. OsiRowCut. |
---|
2689 | |
---|
2690 | TODO: It looks to me as if numberToAdd and numberRowCuts are identical at |
---|
2691 | this point. Confirm & get rid of one of them. |
---|
2692 | |
---|
2693 | TODO: Any reason why the three loops can't be consolidated? |
---|
2694 | */ |
---|
2695 | if (numberRowCuts > 0 || numberColumnCuts > 0) |
---|
2696 | { if (numberToAdd > 0) |
---|
2697 | { int i ; |
---|
2698 | // Faster to add all at once |
---|
2699 | const OsiRowCut ** addCuts = new const OsiRowCut * [numberToAdd] ; |
---|
2700 | for (i = 0 ; i < numberToAdd ; i++) |
---|
2701 | { addCuts[i] = &theseCuts.rowCut(i) ; } |
---|
2702 | solver_->applyRowCuts(numberToAdd,addCuts) ; |
---|
2703 | // AJK this caused a memory fault on Win32 |
---|
2704 | // may be okay now with ** form |
---|
2705 | delete [] addCuts ; |
---|
2706 | for (i = 0 ; i < numberToAdd ; i++) |
---|
2707 | { cuts.insert(theseCuts.rowCut(i)) ; } |
---|
2708 | for (i = 0 ; i < numberToAdd ; i++) |
---|
2709 | { basis_->setArtifStatus(numberRowsNow+i, |
---|
2710 | CoinWarmStartBasis::basic) ; } |
---|
2711 | if (solver_->setWarmStart(basis_) == false) |
---|
2712 | { throw CoinError("Fail setWarmStart() after cut installation.", |
---|
2713 | "solveWithCuts","CbcModel") ; } } |
---|
2714 | feasible = resolve() ; |
---|
2715 | # ifdef CBC_DEBUG |
---|
2716 | printf("Obj value after cuts %g %d rows\n",solver_->getObjValue(), |
---|
2717 | solver_->getNumRows()) ; |
---|
2718 | if (onOptimalPath && !solver_->isDualObjectiveLimitReached()) |
---|
2719 | assert(feasible) ; |
---|
2720 | # endif |
---|
2721 | } |
---|
2722 | /* |
---|
2723 | No cuts. Cut short the cut generation (numberTries) loop. |
---|
2724 | */ |
---|
2725 | else |
---|
2726 | { numberTries = 0 ; } |
---|
2727 | /* |
---|
2728 | If the problem is still feasible, first, call takeOffCuts() to remove cuts |
---|
2729 | that are now slack. takeOffCuts() will call the solver to reoptimise if |
---|
2730 | that's needed to restore a valid solution. |
---|
2731 | |
---|
2732 | Next, see if we should quit due to diminishing returns: |
---|
2733 | * we've tried three rounds of cut generation and we're getting |
---|
2734 | insufficient improvement in the objective; or |
---|
2735 | * we generated no cuts; or |
---|
2736 | * the solver declared optimality with 0 iterations after we added the |
---|
2737 | cuts generated in this round. |
---|
2738 | If we decide to keep going, prep for the next iteration. |
---|
2739 | |
---|
2740 | It just seems more safe to tell takeOffCuts() to call resolve(), even if |
---|
2741 | we're not continuing cut generation. Otherwise code executed between here |
---|
2742 | and final disposition of the node will need to be careful not to access the |
---|
2743 | lp solution. It can happen that we lose feasibility in takeOffCuts --- |
---|
2744 | numerical jitters when the cutoff bound is epsilon less than the current |
---|
2745 | best, and we're evaluating an alternative optimum. |
---|
2746 | |
---|
2747 | TODO: After successive rounds of code motion, there seems no need to |
---|
2748 | distinguish between the two checks for aborting the cut generation |
---|
2749 | loop. Confirm and clean up. |
---|
2750 | */ |
---|
2751 | if (feasible) |
---|
2752 | { int cutIterations = solver_->getIterationCount() ; |
---|
2753 | takeOffCuts(cuts,whichGenerator,numberOldActiveCuts,numberNewCuts,resolveAfterTakeOffCuts_) ; |
---|
2754 | if (solver_->isDualObjectiveLimitReached()&&resolveAfterTakeOffCuts_) |
---|
2755 | { feasible = false ; |
---|
2756 | # ifdef CBC_DEBUG |
---|
2757 | double z = solver_->getObjValue() ; |
---|
2758 | double cut = getCutoff() ; |
---|
2759 | printf("Lost feasibility by %g in takeOffCuts; z = %g, cutoff = %g\n", |
---|
2760 | z-cut,z,cut) ; |
---|
2761 | # endif |
---|
2762 | } |
---|
2763 | if (feasible) |
---|
2764 | { numberRowsAtStart = numberOldActiveCuts+numberRowsAtContinuous_ ; |
---|
2765 | lastNumberCuts = numberNewCuts ; |
---|
2766 | if (direction*solver_->getObjValue() < lastObjective+minimumDrop && |
---|
2767 | currentPassNumber_ >= 3) |
---|
2768 | { numberTries = 0 ; } |
---|
2769 | if (numberRowCuts+numberColumnCuts == 0 || cutIterations == 0) |
---|
2770 | { break ; } |
---|
2771 | if (numberTries > 0) |
---|
2772 | { reducedCostFix() ; |
---|
2773 | lastObjective = direction*solver_->getObjValue() ; |
---|
2774 | lower = solver_->getColLower() ; |
---|
2775 | upper = solver_->getColUpper() ; |
---|
2776 | solution = solver_->getColSolution() ; } } } |
---|
2777 | /* |
---|
2778 | We've lost feasibility --- this node won't be referencing the cuts we've |
---|
2779 | been collecting, so decrement the reference counts. |
---|
2780 | |
---|
2781 | TODO: Presumably this is in preparation for backtracking. Seems like it |
---|
2782 | should be the `else' off the previous `if'. |
---|
2783 | */ |
---|
2784 | if (!feasible) |
---|
2785 | { int i ; |
---|
2786 | for (i = 0;i<currentNumberCuts_;i++) { |
---|
2787 | // take off node |
---|
2788 | if (addedCuts_[i]) { |
---|
2789 | if (!addedCuts_[i]->decrement()) |
---|
2790 | delete addedCuts_[i] ; |
---|
2791 | addedCuts_[i] = NULL ; |
---|
2792 | } |
---|
2793 | } |
---|
2794 | numberTries = 0 ; |
---|
2795 | } |
---|
2796 | } while (numberTries>0) ; |
---|
2797 | /* |
---|
2798 | End of cut generation loop. |
---|
2799 | |
---|
2800 | Now, consider if we want to disable or adjust the frequency of use for any |
---|
2801 | of the cut generators. If the client specified a positive number for |
---|
2802 | howOften, it will never change. If the original value was negative, it'll |
---|
2803 | be converted to 1000000+|howOften|, and this value will be adjusted each |
---|
2804 | time fullScan is true. Actual cut generation is performed every |
---|
2805 | howOften%1000000 nodes; the 1000000 offset is just a convenient way to |
---|
2806 | specify that the frequency is adjustable. |
---|
2807 | |
---|
2808 | During cut generation, we recorded the number of cuts produced by each |
---|
2809 | generator for this node. For all cuts, whichGenerator records the generator |
---|
2810 | that produced a cut. |
---|
2811 | |
---|
2812 | TODO: All this should probably be hidden in a method of the CbcCutGenerator |
---|
2813 | class. |
---|
2814 | */ |
---|
2815 | if (fullScan&&numberCutGenerators_) { |
---|
2816 | /* If cuts just at root node then it will probably be faster to |
---|
2817 | update matrix and leave all in */ |
---|
2818 | bool willBeCutsInTree=false; |
---|
2819 | // Root node or every so often - see what to turn off |
---|
2820 | int i ; |
---|
2821 | double thisObjective = solver_->getObjValue()*direction ; |
---|
2822 | double totalCuts = 0.0 ; |
---|
2823 | for (i = 0;i<numberCutGenerators_;i++) |
---|
2824 | totalCuts += countRowCuts[i] + 5.0*countColumnCuts[i] ; |
---|
2825 | if (!numberNodes_) |
---|
2826 | handler_->message(CBC_ROOT,messages_) |
---|
2827 | <<numberNewCuts |
---|
2828 | <<startObjective<<thisObjective |
---|
2829 | <<currentPassNumber_ |
---|
2830 | <<CoinMessageEol ; |
---|
2831 | int * count = new int[numberCutGenerators_] ; |
---|
2832 | memset(count,0,numberCutGenerators_*sizeof(int)) ; |
---|
2833 | for (i = 0;i<numberNewCuts;i++) { |
---|
2834 | int iGenerator = whichGenerator[i]; |
---|
2835 | if (iGenerator>=0) |
---|
2836 | count[iGenerator]++ ; |
---|
2837 | } |
---|
2838 | double small = (0.5* totalCuts) / |
---|
2839 | ((double) numberCutGenerators_) ; |
---|
2840 | for (i = 0;i<numberCutGenerators_;i++) { |
---|
2841 | int howOften = generator_[i]->howOften() ; |
---|
2842 | if (howOften<-99) |
---|
2843 | continue ; |
---|
2844 | if (howOften<0||howOften >= 1000000) { |
---|
2845 | // If small number switch mostly off |
---|
2846 | double thisCuts = countRowCuts[i] + 5.0*countColumnCuts[i] ; |
---|
2847 | if (!thisCuts||howOften == -99) { |
---|
2848 | if (howOften == -99) |
---|
2849 | howOften = -100 ; |
---|
2850 | else |
---|
2851 | howOften = 1000000+SCANCUTS; // wait until next time |
---|
2852 | } else if (thisCuts<small) { |
---|
2853 | int k = (int) sqrt(small/thisCuts) ; |
---|
2854 | howOften = k+1000000 ; |
---|
2855 | } else { |
---|
2856 | howOften = 1+1000000 ; |
---|
2857 | } |
---|
2858 | } |
---|
2859 | if (howOften>=0&&generator_[i]->generator()->mayGenerateRowCutsInTree()) |
---|
2860 | willBeCutsInTree=true; |
---|
2861 | |
---|
2862 | generator_[i]->setHowOften(howOften) ; |
---|
2863 | int newFrequency = generator_[i]->howOften()%1000000 ; |
---|
2864 | // increment cut counts |
---|
2865 | generator_[i]->incrementNumberCutsInTotal(countRowCuts[i]); |
---|
2866 | generator_[i]->incrementNumberCutsActive(count[i]); |
---|
2867 | if (handler_->logLevel()>1||!numberNodes_) |
---|
2868 | handler_->message(CBC_GENERATOR,messages_) |
---|
2869 | <<i |
---|
2870 | <<generator_[i]->cutGeneratorName() |
---|
2871 | <<countRowCuts[i]<<count[i] |
---|
2872 | <<countColumnCuts[i] |
---|
2873 | <<newFrequency |
---|
2874 | <<CoinMessageEol ; |
---|
2875 | } |
---|
2876 | delete [] count ; |
---|
2877 | if( !numberNodes_) { |
---|
2878 | if( !willBeCutsInTree) { |
---|
2879 | // Take off cuts |
---|
2880 | cuts = OsiCuts(); |
---|
2881 | numberNewCuts=0; |
---|
2882 | // update size of problem |
---|
2883 | numberRowsAtContinuous_ = solver_->getNumRows() ; |
---|
2884 | } else { |
---|
2885 | #ifdef COIN_USE_CLP |
---|
2886 | OsiClpSolverInterface * clpSolver |
---|
2887 | = dynamic_cast<OsiClpSolverInterface *> (solver_); |
---|
2888 | if (clpSolver) { |
---|
2889 | // make sure factorization can't carry over |
---|
2890 | int options = clpSolver->specialOptions(); |
---|
2891 | if (options>=0) |
---|
2892 | clpSolver->setSpecialOptions(clpSolver->specialOptions()&(~8)); |
---|
2893 | } |
---|
2894 | #endif |
---|
2895 | } |
---|
2896 | } |
---|
2897 | } else if (numberCutGenerators_) { |
---|
2898 | int i; |
---|
2899 | // add to counts anyway |
---|
2900 | for (i = 0;i<numberCutGenerators_;i++) |
---|
2901 | generator_[i]->incrementNumberCutsInTotal(countRowCuts[i]); |
---|
2902 | // What if not feasible as cuts may have helped |
---|
2903 | if (feasible) { |
---|
2904 | for (i = 0;i<numberNewCuts;i++) { |
---|
2905 | int iGenerator = whichGenerator[i]; |
---|
2906 | if (iGenerator>=0) |
---|
2907 | generator_[iGenerator]->incrementNumberCutsActive(); |
---|
2908 | } |
---|
2909 | } |
---|
2910 | } |
---|
2911 | |
---|
2912 | delete [] countRowCuts ; |
---|
2913 | delete [] countColumnCuts ; |
---|
2914 | |
---|
2915 | |
---|
2916 | #ifdef CHECK_CUT_COUNTS |
---|
2917 | if (feasible) |
---|
2918 | { delete basis_ ; |
---|
2919 | basis_ = dynamic_cast<CoinWarmStartBasis*>(solver_->getWarmStart()) ; |
---|
2920 | printf("solveWithCuts: Number of rows at end (only active cuts) %d\n", |
---|
2921 | numberRowsAtContinuous_+numberNewCuts+numberOldActiveCuts) ; |
---|
2922 | basis_->print() ; } |
---|
2923 | #endif |
---|
2924 | #ifdef CBC_DEBUG |
---|
2925 | if (onOptimalPath && !solver_->isDualObjectiveLimitReached()) |
---|
2926 | assert(feasible) ; |
---|
2927 | #endif |
---|
2928 | |
---|
2929 | return feasible ; } |
---|
2930 | |
---|
2931 | |
---|
2932 | /* |
---|
2933 | Remove slack cuts. We obtain a basis and scan it. Cuts with basic slacks |
---|
2934 | are purged. If any cuts are purged, resolve() is called to restore the |
---|
2935 | solution held in the solver. If resolve() pivots, there's the possibility |
---|
2936 | that a slack may be pivoted in (trust me :-), so the process iterates. |
---|
2937 | Setting allowResolve to false will suppress reoptimisation (but see note |
---|
2938 | below). |
---|
2939 | |
---|
2940 | At the level of the solver's constraint system, loose cuts are really |
---|
2941 | deleted. There's an implicit assumption that deleteRows will also update |
---|
2942 | the active basis in the solver. |
---|
2943 | |
---|
2944 | At the level of nodes and models, it's more complicated. |
---|
2945 | |
---|
2946 | New cuts exist only in the collection of cuts passed as a parameter. They |
---|
2947 | are deleted from the collection and that's the end of them. |
---|
2948 | |
---|
2949 | Older cuts have made it into addedCuts_. Two separate actions are needed. |
---|
2950 | The reference count for the CbcCountRowCut object is decremented. If this |
---|
2951 | count falls to 0, the node which owns the cut is located, the reference to |
---|
2952 | the cut is removed, and then the cut object is destroyed (courtesy of the |
---|
2953 | CbcCountRowCut destructor). We also need to set the addedCuts_ entry to |
---|
2954 | NULL. This is important so that when it comes time to generate basis edits |
---|
2955 | we can tell this cut was dropped from the basis during processing of the |
---|
2956 | node. |
---|
2957 | |
---|
2958 | NOTE: In general, it's necessary to call resolve() after purging slack |
---|
2959 | cuts. Deleting constraints constitutes a change in the problem, and |
---|
2960 | an OSI is not required to maintain a valid solution when the problem |
---|
2961 | is changed. But ... it's really useful to maintain the active basis, |
---|
2962 | and the OSI is supposed to do that. (Yes, it's splitting hairs.) In |
---|
2963 | some places, it's possible to know that the solution will never be |
---|
2964 | consulted after this call, only the basis. (E.g., this routine is |
---|
2965 | called as a last act before generating info to place the node in the |
---|
2966 | live set.) For such use, set allowResolve to false. |
---|
2967 | |
---|
2968 | TODO: No real harm would be done if we just ignored the rare occasion when |
---|
2969 | the call to resolve() pivoted a slack back into the basis. It's a |
---|
2970 | minor inefficiency, at worst. But it does break assertions which |
---|
2971 | check that there are no loose cuts in the basis. It might be better |
---|
2972 | to remove the assertions. |
---|
2973 | */ |
---|
2974 | |
---|
2975 | void |
---|
2976 | CbcModel::takeOffCuts (OsiCuts &newCuts, int *whichGenerator, |
---|
2977 | int &numberOldActiveCuts, int &numberNewCuts, |
---|
2978 | bool allowResolve) |
---|
2979 | |
---|
2980 | { // int resolveIterations = 0 ; |
---|
2981 | int firstOldCut = numberRowsAtContinuous_ ; |
---|
2982 | int totalNumberCuts = numberNewCuts+numberOldActiveCuts ; |
---|
2983 | int *solverCutIndices = new int[totalNumberCuts] ; |
---|
2984 | int *newCutIndices = new int[numberNewCuts] ; |
---|
2985 | const CoinWarmStartBasis* ws ; |
---|
2986 | CoinWarmStartBasis::Status status ; |
---|
2987 | bool needPurge = true ; |
---|
2988 | /* |
---|
2989 | The outer loop allows repetition of purge in the event that reoptimisation |
---|
2990 | changes the basis. To start an iteration, clear the deletion counts and grab |
---|
2991 | the current basis. |
---|
2992 | */ |
---|
2993 | while (needPurge) |
---|
2994 | { int numberNewToDelete = 0 ; |
---|
2995 | int numberOldToDelete = 0 ; |
---|
2996 | int i ; |
---|
2997 | ws = dynamic_cast<const CoinWarmStartBasis*>(solver_->getWarmStart()) ; |
---|
2998 | /* |
---|
2999 | Scan the basis entries of the old cuts generated prior to this round of cut |
---|
3000 | generation. Loose cuts are `removed' by decrementing their reference count |
---|
3001 | and setting the addedCuts_ entry to NULL. (If the reference count falls to |
---|
3002 | 0, they're really deleted. See CbcModel and CbcCountRowCut doc'n for |
---|
3003 | principles of cut handling.) |
---|
3004 | */ |
---|
3005 | int oldCutIndex = 0 ; |
---|
3006 | for (i = 0 ; i < numberOldActiveCuts ; i++) |
---|
3007 | { status = ws->getArtifStatus(i+firstOldCut) ; |
---|
3008 | while (!addedCuts_[oldCutIndex]) oldCutIndex++ ; |
---|
3009 | assert(oldCutIndex < currentNumberCuts_) ; |
---|
3010 | if (status == CoinWarmStartBasis::basic) |
---|
3011 | { solverCutIndices[numberOldToDelete++] = i+firstOldCut ; |
---|
3012 | if (addedCuts_[oldCutIndex]->decrement() == 0) |
---|
3013 | delete addedCuts_[oldCutIndex] ; |
---|
3014 | addedCuts_[oldCutIndex] = NULL ; |
---|
3015 | oldCutIndex++ ; } |
---|
3016 | else |
---|
3017 | { oldCutIndex++ ; } } |
---|
3018 | /* |
---|
3019 | Scan the basis entries of the new cuts generated with this round of cut |
---|
3020 | generation. At this point, newCuts is the only record of the new cuts, so |
---|
3021 | when we delete loose cuts from newCuts, they're really gone. newCuts is a |
---|
3022 | vector, so it's most efficient to compress it (eraseRowCut) from back to |
---|
3023 | front. |
---|
3024 | */ |
---|
3025 | int firstNewCut = firstOldCut+numberOldActiveCuts ; |
---|
3026 | int k = 0 ; |
---|
3027 | for (i = 0 ; i < numberNewCuts ; i++) |
---|
3028 | { status = ws->getArtifStatus(i+firstNewCut) ; |
---|
3029 | if (status == CoinWarmStartBasis::basic&&whichGenerator[i]!=-2) |
---|
3030 | { solverCutIndices[numberNewToDelete+numberOldToDelete] = i+firstNewCut ; |
---|
3031 | newCutIndices[numberNewToDelete++] = i ; } |
---|
3032 | else |
---|
3033 | { // save which generator did it |
---|
3034 | whichGenerator[k++] = whichGenerator[i] ; } } |
---|
3035 | delete ws ; |
---|
3036 | for (i = numberNewToDelete-1 ; i >= 0 ; i--) |
---|
3037 | { int iCut = newCutIndices[i] ; |
---|
3038 | newCuts.eraseRowCut(iCut) ; } |
---|
3039 | /* |
---|
3040 | Did we delete anything? If so, delete the cuts from the constraint system |
---|
3041 | held in the solver and reoptimise unless we're forbidden to do so. If the |
---|
3042 | call to resolve() results in pivots, there's the possibility we again have |
---|
3043 | basic slacks. Repeat the purging loop. |
---|
3044 | */ |
---|
3045 | if (numberNewToDelete+numberOldToDelete > 0) |
---|
3046 | { solver_->deleteRows(numberNewToDelete+numberOldToDelete, |
---|
3047 | solverCutIndices) ; |
---|
3048 | numberNewCuts -= numberNewToDelete ; |
---|
3049 | numberOldActiveCuts -= numberOldToDelete ; |
---|
3050 | # ifdef CBC_DEBUG |
---|
3051 | std::cout << "takeOffCuts: purged " << numberOldToDelete << "+" |
---|
3052 | << numberNewToDelete << " cuts." << std::endl ; |
---|
3053 | # endif |
---|
3054 | if (allowResolve) |
---|
3055 | { |
---|
3056 | phase_=3; |
---|
3057 | solver_->resolve() ; |
---|
3058 | if (solver_->getIterationCount() == 0) |
---|
3059 | { needPurge = false ; } |
---|
3060 | # ifdef CBC_DEBUG |
---|
3061 | else |
---|
3062 | { std::cout << "Repeating purging loop. " |
---|
3063 | << solver_->getIterationCount() << " iters." |
---|
3064 | << std::endl ; } |
---|
3065 | # endif |
---|
3066 | } |
---|
3067 | else |
---|
3068 | { needPurge = false ; } } |
---|
3069 | else |
---|
3070 | { needPurge = false ; } } |
---|
3071 | /* |
---|
3072 | Clean up and return. |
---|
3073 | */ |
---|
3074 | delete [] solverCutIndices ; |
---|
3075 | delete [] newCutIndices ; |
---|
3076 | } |
---|
3077 | |
---|
3078 | |
---|
3079 | |
---|
3080 | bool |
---|
3081 | CbcModel::resolve() |
---|
3082 | { |
---|
3083 | // We may have deliberately added in violated cuts - check to avoid message |
---|
3084 | int iRow; |
---|
3085 | int numberRows = solver_->getNumRows(); |
---|
3086 | const double * rowLower = solver_->getRowLower(); |
---|
3087 | const double * rowUpper = solver_->getRowUpper(); |
---|
3088 | bool feasible=true; |
---|
3089 | for (iRow= numberRowsAtContinuous_;iRow<numberRows;iRow++) { |
---|
3090 | if (rowLower[iRow]>rowUpper[iRow]+1.0e-8) |
---|
3091 | feasible=false; |
---|
3092 | } |
---|
3093 | /* |
---|
3094 | Reoptimize. Consider the possibility that we should fathom on bounds. But be |
---|
3095 | careful --- where the objective takes on integral values, we may want to keep |
---|
3096 | a solution where the objective is right on the cutoff. |
---|
3097 | */ |
---|
3098 | if (feasible) |
---|
3099 | { solver_->resolve() ; |
---|
3100 | numberIterations_ += getIterationCount() ; |
---|
3101 | feasible = (solver_->isProvenOptimal() && |
---|
3102 | !solver_->isDualObjectiveLimitReached()) ; } |
---|
3103 | if (!feasible&& continuousObjective_ <-1.0e30) { |
---|
3104 | // at root node - double double check |
---|
3105 | bool saveTakeHint; |
---|
3106 | OsiHintStrength saveStrength; |
---|
3107 | solver_->getHintParam(OsiDoDualInResolve,saveTakeHint,saveStrength); |
---|
3108 | if (saveTakeHint||saveStrength==OsiHintIgnore) { |
---|
3109 | solver_->setHintParam(OsiDoDualInResolve,false,OsiHintDo) ; |
---|
3110 | solver_->resolve(); |
---|
3111 | solver_->setHintParam(OsiDoDualInResolve,saveTakeHint,saveStrength); |
---|
3112 | numberIterations_ += getIterationCount() ; |
---|
3113 | feasible = solver_->isProvenOptimal(); |
---|
3114 | } |
---|
3115 | } |
---|
3116 | return feasible ; } |
---|
3117 | |
---|
3118 | |
---|
3119 | /* Set up objects. Only do ones whose length is in range. |
---|
3120 | If makeEquality true then a new model may be returned if |
---|
3121 | modifications had to be made, otherwise "this" is returned. |
---|
3122 | |
---|
3123 | Could use Probing at continuous to extend objects |
---|
3124 | */ |
---|
3125 | CbcModel * |
---|
3126 | CbcModel::findCliques(bool makeEquality, |
---|
3127 | int atLeastThisMany, int lessThanThis, int defaultValue) |
---|
3128 | { |
---|
3129 | // No objects are allowed to exist |
---|
3130 | assert(numberObjects_==numberIntegers_||!numberObjects_); |
---|
3131 | CoinPackedMatrix matrixByRow(*solver_->getMatrixByRow()); |
---|
3132 | int numberRows = solver_->getNumRows(); |
---|
3133 | int numberColumns = solver_->getNumCols(); |
---|
3134 | |
---|
3135 | // We may want to add columns |
---|
3136 | int numberSlacks=0; |
---|
3137 | int * rows = new int[numberRows]; |
---|
3138 | double * element =new double[numberRows]; |
---|
3139 | |
---|
3140 | int iRow; |
---|
3141 | |
---|
3142 | findIntegers(true); |
---|
3143 | numberObjects_=numberIntegers_; |
---|
3144 | |
---|
3145 | int numberCliques=0; |
---|
3146 | CbcObject ** object = new CbcObject * [numberRows]; |
---|
3147 | int * which = new int[numberIntegers_]; |
---|
3148 | char * type = new char[numberIntegers_]; |
---|
3149 | int * lookup = new int[numberColumns]; |
---|
3150 | int i; |
---|
3151 | for (i=0;i<numberColumns;i++) |
---|
3152 | lookup[i]=-1; |
---|
3153 | for (i=0;i<numberIntegers_;i++) |
---|
3154 | lookup[integerVariable_[i]]=i; |
---|
3155 | |
---|
3156 | // Statistics |
---|
3157 | int totalP1=0,totalM1=0; |
---|
3158 | int numberBig=0,totalBig=0; |
---|
3159 | int numberFixed=0; |
---|
3160 | |
---|
3161 | // Row copy |
---|
3162 | const double * elementByRow = matrixByRow.getElements(); |
---|
3163 | const int * column = matrixByRow.getIndices(); |
---|
3164 | const CoinBigIndex * rowStart = matrixByRow.getVectorStarts(); |
---|
3165 | const int * rowLength = matrixByRow.getVectorLengths(); |
---|
3166 | |
---|
3167 | // Column lengths for slacks |
---|
3168 | const int * columnLength = solver_->getMatrixByCol()->getVectorLengths(); |
---|
3169 | |
---|
3170 | const double * lower = getColLower(); |
---|
3171 | const double * upper = getColUpper(); |
---|
3172 | const double * rowLower = getRowLower(); |
---|
3173 | const double * rowUpper = getRowUpper(); |
---|
3174 | |
---|
3175 | for (iRow=0;iRow<numberRows;iRow++) { |
---|
3176 | int numberP1=0, numberM1=0; |
---|
3177 | int j; |
---|
3178 | double upperValue=rowUpper[iRow]; |
---|
3179 | double lowerValue=rowLower[iRow]; |
---|
3180 | bool good=true; |
---|
3181 | int slack = -1; |
---|
3182 | for (j=rowStart[iRow];j<rowStart[iRow]+rowLength[iRow];j++) { |
---|
3183 | int iColumn = column[j]; |
---|
3184 | int iInteger=lookup[iColumn]; |
---|
3185 | if (upper[iColumn]-lower[iColumn]<1.0e-8) { |
---|
3186 | // fixed |
---|
3187 | upperValue -= lower[iColumn]*elementByRow[j]; |
---|
3188 | lowerValue -= lower[iColumn]*elementByRow[j]; |
---|
3189 | continue; |
---|
3190 | } else if (upper[iColumn]!=1.0||lower[iColumn]!=0.0) { |
---|
3191 | good = false; |
---|
3192 | break; |
---|
3193 | } else if (iInteger<0) { |
---|
3194 | good = false; |
---|
3195 | break; |
---|
3196 | } else { |
---|
3197 | if (columnLength[iColumn]==1) |
---|
3198 | slack = iInteger; |
---|
3199 | } |
---|
3200 | if (fabs(elementByRow[j])!=1.0) { |
---|
3201 | good=false; |
---|
3202 | break; |
---|
3203 | } else if (elementByRow[j]>0.0) { |
---|
3204 | which[numberP1++]=iInteger; |
---|
3205 | } else { |
---|
3206 | numberM1++; |
---|
3207 | which[numberIntegers_-numberM1]=iInteger; |
---|
3208 | } |
---|
3209 | } |
---|
3210 | int iUpper = (int) floor(upperValue+1.0e-5); |
---|
3211 | int iLower = (int) ceil(lowerValue-1.0e-5); |
---|
3212 | int state=0; |
---|
3213 | if (upperValue<1.0e6) { |
---|
3214 | if (iUpper==1-numberM1) |
---|
3215 | state=1; |
---|
3216 | else if (iUpper==-numberM1) |
---|
3217 | state=2; |
---|
3218 | else if (iUpper<-numberM1) |
---|
3219 | state=3; |
---|
3220 | } |
---|
3221 | if (!state&&lowerValue>-1.0e6) { |
---|
3222 | if (-iLower==1-numberP1) |
---|
3223 | state=-1; |
---|
3224 | else if (-iLower==-numberP1) |
---|
3225 | state=-2; |
---|
3226 | else if (-iLower<-numberP1) |
---|
3227 | state=-3; |
---|
3228 | } |
---|
3229 | if (good&&state) { |
---|
3230 | if (abs(state)==3) { |
---|
3231 | // infeasible |
---|
3232 | numberObjects_=-1; |
---|
3233 | break; |
---|
3234 | } else if (abs(state)==2) { |
---|
3235 | // we can fix all |
---|
3236 | numberFixed += numberP1+numberM1; |
---|
3237 | if (state>0) { |
---|
3238 | // fix all +1 at 0, -1 at 1 |
---|
3239 | for (i=0;i<numberP1;i++) |
---|
3240 | solver_->setColUpper(integerVariable_[which[i]],0.0); |
---|
3241 | for (i=0;i<numberM1;i++) |
---|
3242 | solver_->setColLower(integerVariable_[which[numberIntegers_-i-1]], |
---|
3243 | 1.0); |
---|
3244 | } else { |
---|
3245 | // fix all +1 at 1, -1 at 0 |
---|
3246 | for (i=0;i<numberP1;i++) |
---|
3247 | solver_->setColLower(integerVariable_[which[i]],1.0); |
---|
3248 | for (i=0;i<numberM1;i++) |
---|
3249 | solver_->setColUpper(integerVariable_[which[numberIntegers_-i-1]], |
---|
3250 | 0.0); |
---|
3251 | } |
---|
3252 | } else { |
---|
3253 | int length = numberP1+numberM1; |
---|
3254 | if (length >= atLeastThisMany&&length<lessThanThis) { |
---|
3255 | // create object |
---|
3256 | bool addOne=false; |
---|
3257 | int objectType; |
---|
3258 | if (iLower==iUpper) { |
---|
3259 | objectType=1; |
---|
3260 | } else { |
---|
3261 | if (makeEquality) { |
---|
3262 | objectType=1; |
---|
3263 | element[numberSlacks]=state; |
---|
3264 | rows[numberSlacks++]=iRow; |
---|
3265 | addOne=true; |
---|
3266 | } else { |
---|
3267 | objectType=0; |
---|
3268 | } |
---|
3269 | } |
---|
3270 | if (state>0) { |
---|
3271 | totalP1 += numberP1; |
---|
3272 | totalM1 += numberM1; |
---|
3273 | for (i=0;i<numberP1;i++) |
---|
3274 | type[i]=1; |
---|
3275 | for (i=0;i<numberM1;i++) { |
---|
3276 | which[numberP1]=which[numberIntegers_-i-1]; |
---|
3277 | type[numberP1++]=0; |
---|
3278 | } |
---|
3279 | } else { |
---|
3280 | totalP1 += numberM1; |
---|
3281 | totalM1 += numberP1; |
---|
3282 | for (i=0;i<numberP1;i++) |
---|
3283 | type[i]=0; |
---|
3284 | for (i=0;i<numberM1;i++) { |
---|
3285 | which[numberP1]=which[numberIntegers_-i-1]; |
---|
3286 | type[numberP1++]=1; |
---|
3287 | } |
---|
3288 | } |
---|
3289 | if (addOne) { |
---|
3290 | // add in slack |
---|
3291 | which[numberP1]=numberIntegers_+numberSlacks-1; |
---|
3292 | slack = numberP1; |
---|
3293 | type[numberP1++]=1; |
---|
3294 | } else if (slack >= 0) { |
---|
3295 | for (i=0;i<numberP1;i++) { |
---|
3296 | if (which[i]==slack) { |
---|
3297 | slack=i; |
---|
3298 | } |
---|
3299 | } |
---|
3300 | } |
---|
3301 | object[numberCliques++] = new CbcClique(this,objectType,numberP1, |
---|
3302 | which,type, |
---|
3303 | 1000000+numberCliques,slack); |
---|
3304 | } else if (numberP1+numberM1 >= lessThanThis) { |
---|
3305 | // too big |
---|
3306 | numberBig++; |
---|
3307 | totalBig += numberP1+numberM1; |
---|
3308 | } |
---|
3309 | } |
---|
3310 | } |
---|
3311 | } |
---|
3312 | delete [] which; |
---|
3313 | delete [] type; |
---|
3314 | delete [] lookup; |
---|
3315 | if (numberCliques<0) { |
---|
3316 | printf("*** Problem infeasible\n"); |
---|
3317 | } else { |
---|
3318 | if (numberCliques) |
---|
3319 | printf("%d cliques of average size %g found, %d P1, %d M1\n", |
---|
3320 | numberCliques, |
---|
3321 | ((double)(totalP1+totalM1))/((double) numberCliques), |
---|
3322 | totalP1,totalM1); |
---|
3323 | else |
---|
3324 | printf("No cliques found\n"); |
---|
3325 | if (numberBig) |
---|
3326 | printf("%d large cliques ( >= %d) found, total %d\n", |
---|
3327 | numberBig,lessThanThis,totalBig); |
---|
3328 | if (numberFixed) |
---|
3329 | printf("%d variables fixed\n",numberFixed); |
---|
3330 | } |
---|
3331 | if (numberCliques>0&&numberSlacks&&makeEquality) { |
---|
3332 | printf("adding %d integer slacks\n",numberSlacks); |
---|
3333 | // add variables to make equality rows |
---|
3334 | int * temp = new int[numberIntegers_+numberSlacks]; |
---|
3335 | memcpy(temp,integerVariable_,numberIntegers_*sizeof(int)); |
---|
3336 | // Get new model |
---|
3337 | CbcModel * newModel = new CbcModel(*this); |
---|
3338 | OsiSolverInterface * newSolver = newModel->solver(); |
---|
3339 | for (i=0;i<numberSlacks;i++) { |
---|
3340 | temp[i+numberIntegers_]=i+numberColumns; |
---|
3341 | int iRow = rows[i]; |
---|
3342 | double value = element[i]; |
---|
3343 | double lowerValue = 0.0; |
---|
3344 | double upperValue = 1.0; |
---|
3345 | double objValue = 0.0; |
---|
3346 | CoinPackedVector column(1,&iRow,&value); |
---|
3347 | newSolver->addCol(column,lowerValue,upperValue,objValue); |
---|
3348 | // set integer |
---|
3349 | newSolver->setInteger(numberColumns+i); |
---|
3350 | if (value >0) |
---|
3351 | newSolver->setRowLower(iRow,rowUpper[iRow]); |
---|
3352 | else |
---|
3353 | newSolver->setRowUpper(iRow,rowLower[iRow]); |
---|
3354 | } |
---|
3355 | // replace list of integers |
---|
3356 | for (i=0;i<newModel->numberObjects_;i++) |
---|
3357 | delete newModel->object_[i]; |
---|
3358 | newModel->numberObjects_ = 0; |
---|
3359 | delete [] newModel->object_; |
---|
3360 | newModel->object_=NULL; |
---|
3361 | newModel->findIntegers(true); //Set up all integer objects |
---|
3362 | if (priority_) { |
---|
3363 | // old model had priorities |
---|
3364 | delete [] newModel->priority_; |
---|
3365 | newModel->priority_ = new int[newModel->numberIntegers_+numberCliques]; |
---|
3366 | memcpy(newModel->priority_,priority_,numberIntegers_*sizeof(int)); |
---|
3367 | for (i=numberIntegers_;i<newModel->numberIntegers_+numberCliques;i++) |
---|
3368 | newModel->priority_[i]=defaultValue; |
---|
3369 | } |
---|
3370 | if (originalColumns_) { |
---|
3371 | // old model had originalColumns |
---|
3372 | delete [] newModel->originalColumns_; |
---|
3373 | newModel->originalColumns_ = new int[numberColumns+numberSlacks]; |
---|
3374 | memcpy(newModel->originalColumns_,originalColumns_,numberColumns*sizeof(int)); |
---|
3375 | // mark as not in previous model |
---|
3376 | for (i=numberColumns;i<numberColumns+numberSlacks;i++) |
---|
3377 | newModel->originalColumns_[i]=-1; |
---|
3378 | } |
---|
3379 | delete [] rows; |
---|
3380 | delete [] element; |
---|
3381 | newModel->addObjects(numberCliques,object); |
---|
3382 | for (;i<numberCliques;i++) |
---|
3383 | delete object[i]; |
---|
3384 | delete [] object; |
---|
3385 | newModel->synchronizeModel(); |
---|
3386 | return newModel; |
---|
3387 | } else { |
---|
3388 | if (numberCliques>0) { |
---|
3389 | addObjects(numberCliques,object); |
---|
3390 | for (;i<numberCliques;i++) |
---|
3391 | delete object[i]; |
---|
3392 | synchronizeModel(); |
---|
3393 | } |
---|
3394 | delete [] object; |
---|
3395 | if (priority_) { |
---|
3396 | // model had priorities |
---|
3397 | int * temp = new int[numberIntegers_+numberCliques]; |
---|
3398 | memcpy(temp,priority_,numberIntegers_*sizeof(int)); |
---|
3399 | delete [] priority_; |
---|
3400 | priority_=temp; |
---|
3401 | for (i=numberIntegers_;i<numberIntegers_+numberCliques;i++) |
---|
3402 | priority_[i]=defaultValue; |
---|
3403 | } |
---|
3404 | delete [] rows; |
---|
3405 | delete [] element; |
---|
3406 | return this; |
---|
3407 | } |
---|
3408 | } |
---|
3409 | |
---|
3410 | /* |
---|
3411 | Set branching priorities. |
---|
3412 | |
---|
3413 | Setting integer priorities looks pretty robust; the call to findIntegers |
---|
3414 | makes sure that SimpleInteger objects are in place. Setting priorities for |
---|
3415 | other objects is entirely dependent on their existence, and the routine may |
---|
3416 | quietly fail in several directions. |
---|
3417 | */ |
---|
3418 | |
---|
3419 | void |
---|
3420 | CbcModel::passInPriorities (const int * priorities, |
---|
3421 | bool ifObject, int defaultValue) |
---|
3422 | { |
---|
3423 | findIntegers(false); |
---|
3424 | int i; |
---|
3425 | if (!priority_) { |
---|
3426 | priority_ = new int[numberObjects_]; |
---|
3427 | for (i=0;i<numberObjects_;i++) |
---|
3428 | priority_[i]=defaultValue; |
---|
3429 | } |
---|
3430 | if (priorities) { |
---|
3431 | if (ifObject) |
---|
3432 | memcpy(priority_+numberIntegers_,priorities, |
---|
3433 | (numberObjects_-numberIntegers_)*sizeof(int)); |
---|
3434 | else |
---|
3435 | memcpy(priority_,priorities,numberIntegers_*sizeof(int)); |
---|
3436 | } |
---|
3437 | } |
---|
3438 | |
---|
3439 | // Delete all object information |
---|
3440 | void |
---|
3441 | CbcModel::deleteObjects() |
---|
3442 | { |
---|
3443 | delete [] priority_; |
---|
3444 | priority_=NULL; |
---|
3445 | int i; |
---|
3446 | for (i=0;i<numberObjects_;i++) |
---|
3447 | delete object_[i]; |
---|
3448 | delete [] object_; |
---|
3449 | object_ = NULL; |
---|
3450 | numberObjects_=0; |
---|
3451 | findIntegers(true); |
---|
3452 | } |
---|
3453 | |
---|
3454 | /*! |
---|
3455 | Ensure all attached objects (CbcObjects, heuristics, and cut |
---|
3456 | generators) point to this model. |
---|
3457 | */ |
---|
3458 | void CbcModel::synchronizeModel() |
---|
3459 | { |
---|
3460 | int i; |
---|
3461 | for (i=0;i<numberHeuristics_;i++) |
---|
3462 | heuristic_[i]->setModel(this); |
---|
3463 | for (i=0;i<numberObjects_;i++) |
---|
3464 | object_[i]->setModel(this); |
---|
3465 | for (i=0;i<numberCutGenerators_;i++) |
---|
3466 | generator_[i]->refreshModel(this); |
---|
3467 | } |
---|
3468 | |
---|
3469 | // Fill in integers and create objects |
---|
3470 | |
---|
3471 | /** |
---|
3472 | The routine first does a scan to count the number of integer variables. |
---|
3473 | It then creates an array, integerVariable_, to store the indices of the |
---|
3474 | integer variables, and an array of `objects', one for each variable. |
---|
3475 | |
---|
3476 | The scan is repeated, this time recording the index of each integer |
---|
3477 | variable in integerVariable_, and creating an CbcSimpleInteger object that |
---|
3478 | contains information about the integer variable. Initially, this is just |
---|
3479 | the index and upper & lower bounds. |
---|
3480 | |
---|
3481 | \todo |
---|
3482 | Note the assumption in cbc that the first numberIntegers_ objects are |
---|
3483 | CbcSimpleInteger. In particular, the code which handles the startAgain |
---|
3484 | case assumes that if the object_ array exists it can simply replace the first |
---|
3485 | numberInteger_ objects. This is arguably unsafe. |
---|
3486 | |
---|
3487 | I am going to re-order if necessary |
---|
3488 | */ |
---|
3489 | |
---|
3490 | void |
---|
3491 | CbcModel::findIntegers(bool startAgain) |
---|
3492 | { |
---|
3493 | assert(solver_); |
---|
3494 | /* |
---|
3495 | No need to do this if we have previous information, unless forced to start |
---|
3496 | over. |
---|
3497 | */ |
---|
3498 | if (numberIntegers_&&!startAgain&&object_) |
---|
3499 | return; |
---|
3500 | /* |
---|
3501 | Clear out the old integer variable list, then count the number of integer |
---|
3502 | variables. |
---|
3503 | */ |
---|
3504 | delete [] integerVariable_; |
---|
3505 | numberIntegers_=0; |
---|
3506 | int numberColumns = getNumCols(); |
---|
3507 | int iColumn; |
---|
3508 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
---|
3509 | if (isInteger(iColumn)) |
---|
3510 | numberIntegers_++; |
---|
3511 | } |
---|
3512 | // Find out how many old non-integer objects there are |
---|
3513 | int nObjects=0; |
---|
3514 | CbcObject ** oldObject = object_; |
---|
3515 | int iObject; |
---|
3516 | for (iObject = 0;iObject<numberObjects_;iObject++) { |
---|
3517 | CbcSimpleInteger * obj = |
---|
3518 | dynamic_cast <CbcSimpleInteger *>(oldObject[iObject]) ; |
---|
3519 | if (obj) |
---|
3520 | delete oldObject[iObject]; |
---|
3521 | else |
---|
3522 | oldObject[nObjects++]=oldObject[iObject]; |
---|
3523 | } |
---|
3524 | |
---|
3525 | /* |
---|
3526 | Found any? Allocate an array to hold the indices of the integer variables. |
---|
3527 | Make a large enough array for all objects |
---|
3528 | */ |
---|
3529 | object_ = new CbcObject * [numberIntegers_+nObjects]; |
---|
3530 | numberObjects_=numberIntegers_+nObjects;; |
---|
3531 | integerVariable_ = new int [numberIntegers_]; |
---|
3532 | /* |
---|
3533 | Walk the variables again, filling in the indices and creating objects for |
---|
3534 | the integer variables. Initially, the objects hold the index and upper & |
---|
3535 | lower bounds. |
---|
3536 | */ |
---|
3537 | numberIntegers_=0; |
---|
3538 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
---|
3539 | if(isInteger(iColumn)) { |
---|
3540 | object_[numberIntegers_] = |
---|
3541 | new CbcSimpleInteger(this,numberIntegers_,iColumn); |
---|
3542 | integerVariable_[numberIntegers_++]=iColumn; |
---|
3543 | } |
---|
3544 | } |
---|
3545 | // Now append other objects |
---|
3546 | memcpy(object_+numberIntegers_,oldObject,nObjects*sizeof(CbcObject *)); |
---|
3547 | // Delete old array (just array) |
---|
3548 | delete [] oldObject; |
---|
3549 | |
---|
3550 | if (!numberObjects_) |
---|
3551 | handler_->message(CBC_NOINT,messages_) << CoinMessageEol ; |
---|
3552 | } |
---|
3553 | |
---|
3554 | /* Add in any object information (objects are cloned - owner can delete |
---|
3555 | originals */ |
---|
3556 | void |
---|
3557 | CbcModel::addObjects(int numberObjects, CbcObject ** objects) |
---|
3558 | { |
---|
3559 | int newNumberObjects= numberObjects+numberObjects_; |
---|
3560 | CbcObject ** temp = new CbcObject * [newNumberObjects]; |
---|
3561 | int i; |
---|
3562 | for (i=0;i<numberObjects_;i++) |
---|
3563 | temp[i]=object_[i]; |
---|
3564 | for (;i<newNumberObjects;i++) { |
---|
3565 | temp[i]=objects[i-numberObjects_]->clone(); |
---|
3566 | temp[i]->setModel(this); |
---|
3567 | } |
---|
3568 | delete [] object_; |
---|
3569 | object_ = temp; |
---|
3570 | numberObjects_ = newNumberObjects; |
---|
3571 | } |
---|
3572 | |
---|
3573 | /** |
---|
3574 | This routine sets the objective cutoff value used for fathoming and |
---|
3575 | determining monotonic variables. |
---|
3576 | |
---|
3577 | If the fathoming discipline is strict, a small tolerance is added to the |
---|
3578 | new cutoff. This avoids problems due to roundoff when the target value |
---|
3579 | is exact. The common example would be an IP with only integer variables in |
---|
3580 | the objective. If the target is set to the exact value z of the optimum, |
---|
3581 | it's possible to end up fathoming an ancestor of the solution because the |
---|
3582 | solver returns z+epsilon. |
---|
3583 | |
---|
3584 | Determining if strict fathoming is needed is best done by analysis. |
---|
3585 | In cbc, that's analyseObjective. The default is false. |
---|
3586 | |
---|
3587 | In cbc we always minimize so add epsilon |
---|
3588 | */ |
---|
3589 | |
---|
3590 | void CbcModel::setCutoff (double value) |
---|
3591 | |
---|
3592 | { |
---|
3593 | #if 0 |
---|
3594 | double tol = 0 ; |
---|
3595 | int fathomStrict = getIntParam(CbcFathomDiscipline) ; |
---|
3596 | if (fathomStrict == 1) |
---|
3597 | { solver_->getDblParam(OsiDualTolerance,tol) ; |
---|
3598 | tol = tol*(1+fabs(value)) ; |
---|
3599 | |
---|
3600 | value += tol ; } |
---|
3601 | #endif |
---|
3602 | // Solvers know about direction |
---|
3603 | double direction = solver_->getObjSense(); |
---|
3604 | solver_->setDblParam(OsiDualObjectiveLimit,value*direction); } |
---|
3605 | |
---|
3606 | |
---|
3607 | |
---|
3608 | /* |
---|
3609 | Call this to really test if a valid solution can be feasible. The cutoff is |
---|
3610 | passed in as a parameter so that we don't need to worry here after swapping |
---|
3611 | solvers. The solution is assumed to be numberColumns in size. If |
---|
3612 | fixVariables is true then the bounds of the continuous solver are updated. |
---|
3613 | The routine returns the objective value determined by reoptimizing from |
---|
3614 | scratch. If the solution is rejected, this will be worse than the cutoff. |
---|
3615 | |
---|
3616 | TODO: There's an issue with getting the correct cutoff value: We update the |
---|
3617 | cutoff in the regular solver, but not in continuousSolver_. But our only |
---|
3618 | use for continuousSolver_ is verifying candidate solutions. Would it |
---|
3619 | make sense to update the cutoff? Then we wouldn't need to step around |
---|
3620 | isDualObjectiveLimitReached(). |
---|
3621 | */ |
---|
3622 | double |
---|
3623 | CbcModel::checkSolution (double cutoff, const double *solution, |
---|
3624 | bool fixVariables) |
---|
3625 | |
---|
3626 | { int numberColumns = solver_->getNumCols(); |
---|
3627 | |
---|
3628 | /* |
---|
3629 | Grab the continuous solver (the pristine copy of the problem, made before |
---|
3630 | starting to work on the root node). Save the bounds on the variables. |
---|
3631 | Install the solution passed as a parameter, and copy it to the model's |
---|
3632 | currentSolution_. |
---|
3633 | |
---|
3634 | TODO: This is a belt-and-suspenders approach. Once the code has settled |
---|
3635 | a bit, we can cast a critical eye here. |
---|
3636 | */ |
---|
3637 | OsiSolverInterface * saveSolver = solver_; |
---|
3638 | if (continuousSolver_) |
---|
3639 | solver_ = continuousSolver_; |
---|
3640 | // move solution to continuous copy |
---|
3641 | solver_->setColSolution(solution); |
---|
3642 | // Put current solution in safe place |
---|
3643 | memcpy(currentSolution_,solver_->getColSolution(), |
---|
3644 | numberColumns*sizeof(double)); |
---|
3645 | //solver_->messageHandler()->setLogLevel(4); |
---|
3646 | |
---|
3647 | // save original bounds |
---|
3648 | double * saveUpper = new double[numberColumns]; |
---|
3649 | double * saveLower = new double[numberColumns]; |
---|
3650 | memcpy(saveUpper,getColUpper(),numberColumns*sizeof(double)); |
---|
3651 | memcpy(saveLower,getColLower(),numberColumns*sizeof(double)); |
---|
3652 | |
---|
3653 | /* |
---|
3654 | Run through the objects and use feasibleRegion() to set variable bounds |
---|
3655 | so as to fix the variables specified in the objects at their value in this |
---|
3656 | solution. Since the object list contains (at least) one object for every |
---|
3657 | integer variable, this has the effect of fixing all integer variables. |
---|
3658 | */ |
---|
3659 | int i; |
---|
3660 | for (i=0;i<numberObjects_;i++) |
---|
3661 | object_[i]->feasibleRegion(); |
---|
3662 | /* |
---|
3663 | Remove any existing warm start information to be sure there is no |
---|
3664 | residual influence on initialSolve(). |
---|
3665 | */ |
---|
3666 | CoinWarmStartBasis *slack = |
---|
3667 | dynamic_cast<CoinWarmStartBasis *>(solver_->getEmptyWarmStart()) ; |
---|
3668 | solver_->setWarmStart(slack); |
---|
3669 | delete slack ; |
---|
3670 | // Give a hint not to do scaling |
---|
3671 | //bool saveTakeHint; |
---|
3672 | //OsiHintStrength saveStrength; |
---|
3673 | //bool gotHint = (solver_->getHintParam(OsiDoScale,saveTakeHint,saveStrength)); |
---|
3674 | //assert (gotHint); |
---|
3675 | //solver_->setHintParam(OsiDoScale,false,OsiHintTry); |
---|
3676 | solver_->initialSolve(); |
---|
3677 | //solver_->setHintParam(OsiDoScale,saveTakeHint,saveStrength); |
---|
3678 | if (!solver_->isProvenOptimal()) |
---|
3679 | { std::cout << "checkSolution infeas! Retrying wihout scaling." |
---|
3680 | << std::endl ; |
---|
3681 | bool saveTakeHint; |
---|
3682 | OsiHintStrength saveStrength; |
---|
3683 | bool savePrintHint; |
---|
3684 | solver_->writeMps("infeas"); |
---|
3685 | bool gotHint = (solver_->getHintParam(OsiDoReducePrint,savePrintHint,saveStrength)); |
---|
3686 | gotHint = (solver_->getHintParam(OsiDoScale,saveTakeHint,saveStrength)); |
---|
3687 | solver_->setHintParam(OsiDoScale,false,OsiHintTry); |
---|
3688 | solver_->setHintParam(OsiDoReducePrint,false,OsiHintTry) ; |
---|
3689 | solver_->initialSolve(); |
---|
3690 | solver_->setHintParam(OsiDoScale,saveTakeHint,saveStrength); |
---|
3691 | solver_->setHintParam(OsiDoReducePrint,savePrintHint,OsiHintTry) ; |
---|
3692 | } |
---|
3693 | assert(solver_->isProvenOptimal()); |
---|
3694 | double objectiveValue = solver_->getObjValue()*solver_->getObjSense(); |
---|
3695 | |
---|
3696 | /* |
---|
3697 | Check that the solution still beats the objective cutoff. |
---|
3698 | |
---|
3699 | If it passes, make a copy of the primal variable values and do some |
---|
3700 | cleanup and checks: |
---|
3701 | + Values of all variables are are within original bounds and values of |
---|
3702 | all integer variables are within tolerance of integral. |
---|
3703 | + There are no constraint violations. |
---|
3704 | There really should be no need for the check against original bounds. |
---|
3705 | Perhaps an opportunity for a sanity check? |
---|
3706 | */ |
---|
3707 | if (solver_->isProvenOptimal() && objectiveValue <= cutoff) |
---|
3708 | { solution = solver_->getColSolution() ; |
---|
3709 | memcpy(currentSolution_,solution,numberColumns*sizeof(double)) ; |
---|
3710 | |
---|
3711 | const double * rowLower = solver_->getRowLower() ; |
---|
3712 | const double * rowUpper = solver_->getRowUpper() ; |
---|
3713 | int numberRows = solver_->getNumRows() ; |
---|
3714 | double *rowActivity = new double[numberRows] ; |
---|
3715 | memset(rowActivity,0,numberRows*sizeof(double)) ; |
---|
3716 | |
---|
3717 | double integerTolerance = getIntegerTolerance() ; |
---|
3718 | |
---|
3719 | int iColumn; |
---|
3720 | for (iColumn = 0 ; iColumn < numberColumns ; iColumn++) |
---|
3721 | { double value = currentSolution_[iColumn] ; |
---|
3722 | value = CoinMax(value, saveLower[iColumn]) ; |
---|
3723 | value = CoinMin(value, saveUpper[iColumn]) ; |
---|
3724 | if (solver_->isInteger(iColumn)) |
---|
3725 | assert(fabs(value-currentSolution_[iColumn]) <= integerTolerance) ; |
---|
3726 | currentSolution_[iColumn] = value ; } |
---|
3727 | |
---|
3728 | solver_->getMatrixByCol()->times(currentSolution_,rowActivity) ; |
---|
3729 | double primalTolerance ; |
---|
3730 | solver_->getDblParam(OsiPrimalTolerance,primalTolerance) ; |
---|
3731 | double largestInfeasibility =0.0; |
---|
3732 | for (i=0 ; i < numberRows ; i++) { |
---|
3733 | largestInfeasibility = CoinMax(largestInfeasibility, |
---|
3734 | rowLower[i]-rowActivity[i]); |
---|
3735 | largestInfeasibility = CoinMax(largestInfeasibility, |
---|
3736 | rowActivity[i]-rowUpper[i]); |
---|
3737 | } |
---|
3738 | if (largestInfeasibility>100.0*primalTolerance) |
---|
3739 | handler_->message(CBC_NOTFEAS3, messages_) |
---|
3740 | << largestInfeasibility << CoinMessageEol ; |
---|
3741 | |
---|
3742 | delete [] rowActivity ; } |
---|
3743 | else |
---|
3744 | { objectiveValue=1.0e50 ; } |
---|
3745 | /* |
---|
3746 | Regardless of what we think of the solution, we may need to restore the |
---|
3747 | original bounds of the continuous solver. Unfortunately, const'ness |
---|
3748 | prevents us from simply reversing the memcpy used to make these snapshots. |
---|
3749 | */ |
---|
3750 | if (!fixVariables) |
---|
3751 | { for (int iColumn = 0 ; iColumn < numberColumns ; iColumn++) |
---|
3752 | { solver_->setColLower(iColumn,saveLower[iColumn]) ; |
---|
3753 | solver_->setColUpper(iColumn,saveUpper[iColumn]) ; } } |
---|
3754 | delete [] saveLower; |
---|
3755 | delete [] saveUpper; |
---|
3756 | |
---|
3757 | /* |
---|
3758 | Restore the usual solver. |
---|
3759 | */ |
---|
3760 | solver_=saveSolver; |
---|
3761 | return objectiveValue; |
---|
3762 | } |
---|
3763 | |
---|
3764 | /* |
---|
3765 | Call this routine from anywhere when a solution is found. The solution |
---|
3766 | vector is assumed to contain one value for each structural variable. |
---|
3767 | |
---|
3768 | The first action is to run checkSolution() to confirm the objective and |
---|
3769 | feasibility. If this check causes the solution to be rejected, we're done. |
---|
3770 | If fixVariables = true, the variable bounds held by the continuous solver |
---|
3771 | will be left fixed to the values in the solution; otherwise they are |
---|
3772 | restored to the original values. |
---|
3773 | |
---|
3774 | If the solution is accepted, install it as the best solution. |
---|
3775 | |
---|
3776 | The routine also contains a hook to run any cut generators that are flagged |
---|
3777 | to run when a new solution is discovered. There's a potential hazard because |
---|
3778 | the cut generators see the continuous solver >after< possible restoration of |
---|
3779 | original bounds (which may well invalidate the solution). |
---|
3780 | */ |
---|
3781 | |
---|
3782 | void |
---|
3783 | CbcModel::setBestSolution (CBC_Message how, |
---|
3784 | double & objectiveValue, const double *solution, |
---|
3785 | bool fixVariables) |
---|
3786 | |
---|
3787 | { double cutoff = getCutoff() ; |
---|
3788 | |
---|
3789 | /* |
---|
3790 | Double check the solution to catch pretenders. |
---|
3791 | */ |
---|
3792 | objectiveValue = checkSolution(cutoff,solution,fixVariables); |
---|
3793 | if (objectiveValue > cutoff) |
---|
3794 | { if (objectiveValue>1.0e30) |
---|
3795 | handler_->message(CBC_NOTFEAS1, messages_) << CoinMessageEol ; |
---|
3796 | else |
---|
3797 | handler_->message(CBC_NOTFEAS2, messages_) |
---|
3798 | << objectiveValue << cutoff << CoinMessageEol ; } |
---|
3799 | /* |
---|
3800 | We have a winner. Install it as the new incumbent. |
---|
3801 | Bump the objective cutoff value and solution counts. Give the user the |
---|
3802 | good news. |
---|
3803 | */ |
---|
3804 | else |
---|
3805 | { bestObjective_ = objectiveValue; |
---|
3806 | int numberColumns = solver_->getNumCols(); |
---|
3807 | if (!bestSolution_) |
---|
3808 | bestSolution_ = new double[numberColumns]; |
---|
3809 | memcpy(bestSolution_,currentSolution_,numberColumns*sizeof(double)); |
---|
3810 | |
---|
3811 | cutoff = bestObjective_-dblParam_[CbcCutoffIncrement]; |
---|
3812 | // This is not correct - that way cutoff can go up if maximization |
---|
3813 | //double direction = solver_->getObjSense(); |
---|
3814 | //setCutoff(cutoff*direction); |
---|
3815 | setCutoff(cutoff); |
---|
3816 | |
---|
3817 | if (how==CBC_ROUNDING) |
---|
3818 | numberHeuristicSolutions_++; |
---|
3819 | numberSolutions_++; |
---|
3820 | |
---|
3821 | handler_->message(how,messages_) |
---|
3822 | <<bestObjective_<<numberIterations_ |
---|
3823 | <<numberNodes_ |
---|
3824 | <<CoinMessageEol; |
---|
3825 | /* |
---|
3826 | Now step through the cut generators and see if any of them are flagged to |
---|
3827 | run when a new solution is discovered. Only global cuts are useful. (The |
---|
3828 | solution being evaluated may not correspond to the current location in the |
---|
3829 | search tree --- discovered by heuristic, for example.) |
---|
3830 | */ |
---|
3831 | OsiCuts theseCuts; |
---|
3832 | int i; |
---|
3833 | int lastNumberCuts=0; |
---|
3834 | for (i=0;i<numberCutGenerators_;i++) { |
---|
3835 | if (generator_[i]->atSolution()) { |
---|
3836 | generator_[i]->generateCuts(theseCuts,true,NULL); |
---|
3837 | int numberCuts = theseCuts.sizeRowCuts(); |
---|
3838 | for (int j=lastNumberCuts;j<numberCuts;j++) { |
---|
3839 | const OsiRowCut * thisCut = theseCuts.rowCutPtr(j); |
---|
3840 | if (thisCut->globallyValid()) { |
---|
3841 | # ifdef CBC_DEBUG |
---|
3842 | /* As these are global cuts - |
---|
3843 | a) Always get debugger object |
---|
3844 | b) Not fatal error to cutoff optimal (if we have just got optimal) |
---|
3845 | */ |
---|
3846 | const OsiRowCutDebugger *debugger = solver_->getRowCutDebuggerAlways() ; |
---|
3847 | if (debugger) { |
---|
3848 | if(debugger->invalidCut(*thisCut)) |
---|
3849 | printf("ZZZZ Global cut - cuts off optimal solution!\n"); |
---|
3850 | } |
---|
3851 | # endif |
---|
3852 | // add to global list |
---|
3853 | globalCuts_.insert(*thisCut); |
---|
3854 | generator_[i]->incrementNumberCutsInTotal(); |
---|
3855 | } |
---|
3856 | } |
---|
3857 | } |
---|
3858 | } |
---|
3859 | int numberCuts = theseCuts.sizeColCuts(); |
---|
3860 | for (i=0;i<numberCuts;i++) { |
---|
3861 | const OsiColCut * thisCut = theseCuts.colCutPtr(i); |
---|
3862 | if (thisCut->globallyValid()) { |
---|
3863 | // add to global list |
---|
3864 | globalCuts_.insert(*thisCut); |
---|
3865 | } |
---|
3866 | } |
---|
3867 | } |
---|
3868 | |
---|
3869 | return ; } |
---|
3870 | |
---|
3871 | |
---|
3872 | /* Test the current solution for feasibility. |
---|
3873 | |
---|
3874 | Calculate the number of standard integer infeasibilities, then scan the |
---|
3875 | remaining objects to see if any of them report infeasibilities. |
---|
3876 | |
---|
3877 | Currently (2003.08) the only object besides SimpleInteger is Clique, hence |
---|
3878 | the comments about `odd ones' infeasibilities. |
---|
3879 | */ |
---|
3880 | bool |
---|
3881 | CbcModel::feasibleSolution(int & numberIntegerInfeasibilities, |
---|
3882 | int & numberObjectInfeasibilities) const |
---|
3883 | { |
---|
3884 | int numberUnsatisfied=0; |
---|
3885 | double sumUnsatisfied=0.0; |
---|
3886 | int preferredWay; |
---|
3887 | double integerTolerance = getIntegerTolerance(); |
---|
3888 | int j; |
---|
3889 | // Put current solution in safe place |
---|
3890 | memcpy(currentSolution_,solver_->getColSolution(), |
---|
3891 | solver_->getNumCols()*sizeof(double)); |
---|
3892 | for (j=0;j<numberIntegers_;j++) { |
---|
3893 | const CbcObject * object = object_[j]; |
---|
3894 | double infeasibility = object->infeasibility(preferredWay); |
---|
3895 | if (infeasibility>integerTolerance) { |
---|
3896 | numberUnsatisfied++; |
---|
3897 | sumUnsatisfied += infeasibility; |
---|
3898 | } |
---|
3899 | } |
---|
3900 | numberIntegerInfeasibilities = numberUnsatisfied; |
---|
3901 | for (;j<numberObjects_;j++) { |
---|
3902 | const CbcObject * object = object_[j]; |
---|
3903 | double infeasibility = object->infeasibility(preferredWay); |
---|
3904 | if (infeasibility>integerTolerance) { |
---|
3905 | numberUnsatisfied++; |
---|
3906 | sumUnsatisfied += infeasibility; |
---|
3907 | } |
---|
3908 | } |
---|
3909 | numberObjectInfeasibilities = numberUnsatisfied-numberIntegerInfeasibilities; |
---|
3910 | return (!numberUnsatisfied); |
---|
3911 | } |
---|
3912 | |
---|
3913 | /* For all vubs see if we can tighten bounds by solving Lp's |
---|
3914 | type - 0 just vubs |
---|
3915 | 1 all (could be very slow) |
---|
3916 | -1 just vubs where variable away from bound |
---|
3917 | Returns false if not feasible |
---|
3918 | */ |
---|
3919 | bool |
---|
3920 | CbcModel::tightenVubs(int type, bool allowMultipleBinary, double useCutoff) |
---|
3921 | { |
---|
3922 | |
---|
3923 | CoinPackedMatrix matrixByRow(*solver_->getMatrixByRow()); |
---|
3924 | int numberRows = solver_->getNumRows(); |
---|
3925 | int numberColumns = solver_->getNumCols(); |
---|
3926 | |
---|
3927 | int iRow,iColumn; |
---|
3928 | |
---|
3929 | // Row copy |
---|
3930 | //const double * elementByRow = matrixByRow.getElements(); |
---|
3931 | const int * column = matrixByRow.getIndices(); |
---|
3932 | const CoinBigIndex * rowStart = matrixByRow.getVectorStarts(); |
---|
3933 | const int * rowLength = matrixByRow.getVectorLengths(); |
---|
3934 | |
---|
3935 | const double * colUpper = solver_->getColUpper(); |
---|
3936 | const double * colLower = solver_->getColLower(); |
---|
3937 | //const double * rowUpper = solver_->getRowUpper(); |
---|
3938 | //const double * rowLower = solver_->getRowLower(); |
---|
3939 | |
---|
3940 | const double * objective = solver_->getObjCoefficients(); |
---|
3941 | //double direction = solver_->getObjSense(); |
---|
3942 | const double * colsol = solver_->getColSolution(); |
---|
3943 | |
---|
3944 | int numberVub=0; |
---|
3945 | int * continuous = new int[numberColumns]; |
---|
3946 | if (type >= 0) { |
---|
3947 | double * sort = new double[numberColumns]; |
---|
3948 | for (iRow=0;iRow<numberRows;iRow++) { |
---|
3949 | int j; |
---|
3950 | int numberBinary=0; |
---|
3951 | int numberUnsatisfiedBinary=0; |
---|
3952 | int numberContinuous=0; |
---|
3953 | int iCont=-1; |
---|
3954 | double weight=1.0e30; |
---|
3955 | for (j=rowStart[iRow];j<rowStart[iRow]+rowLength[iRow];j++) { |
---|
3956 | int iColumn = column[j]; |
---|
3957 | if (colUpper[iColumn]-colLower[iColumn]>1.0e-8) { |
---|
3958 | if (solver_->isFreeBinary(iColumn)) { |
---|
3959 | numberBinary++; |
---|
3960 | /* For sort I make naive assumption: |
---|
3961 | x - a * delta <=0 or |
---|
3962 | -x + a * delta >= 0 |
---|
3963 | */ |
---|
3964 | if (colsol[iColumn]>colLower[iColumn]+1.0e-6&& |
---|
3965 | colsol[iColumn]<colUpper[iColumn]-1.0e-6) { |
---|
3966 | numberUnsatisfiedBinary++; |
---|
3967 | weight = CoinMin(weight,fabs(objective[iColumn])); |
---|
3968 | } |
---|
3969 | } else { |
---|
3970 | numberContinuous++; |
---|
3971 | iCont=iColumn; |
---|
3972 | } |
---|
3973 | } |
---|
3974 | } |
---|
3975 | if (numberContinuous==1&&numberBinary) { |
---|
3976 | if (numberBinary==1||allowMultipleBinary) { |
---|
3977 | // treat as vub |
---|
3978 | if (!numberUnsatisfiedBinary) |
---|
3979 | weight=-1.0; // at end |
---|
3980 | sort[numberVub]=-weight; |
---|
3981 | continuous[numberVub++] = iCont; |
---|
3982 | } |
---|
3983 | } |
---|
3984 | } |
---|
3985 | if (type>0) { |
---|
3986 | // take so many |
---|
3987 | CoinSort_2(sort,sort+numberVub,continuous); |
---|
3988 | numberVub = CoinMin(numberVub,type); |
---|
3989 | } |
---|
3990 | delete [] sort; |
---|
3991 | } else { |
---|
3992 | for (iColumn=0;iColumn<numberColumns;iColumn++) |
---|
3993 | continuous[iColumn]=iColumn; |
---|
3994 | numberVub=numberColumns; |
---|
3995 | } |
---|
3996 | bool feasible = tightenVubs(numberVub,continuous,useCutoff); |
---|
3997 | delete [] continuous; |
---|
3998 | |
---|
3999 | return feasible; |
---|
4000 | } |
---|
4001 | // This version is just handed a list of variables |
---|
4002 | bool |
---|
4003 | CbcModel::tightenVubs(int numberSolves, const int * which, |
---|
4004 | double useCutoff) |
---|
4005 | { |
---|
4006 | |
---|
4007 | int numberColumns = solver_->getNumCols(); |
---|
4008 | |
---|
4009 | int iColumn; |
---|
4010 | |
---|
4011 | OsiSolverInterface * solver = solver_; |
---|
4012 | double saveCutoff = getCutoff() ; |
---|
4013 | |
---|
4014 | double * objective = new double[numberColumns]; |
---|
4015 | memcpy(objective,solver_->getObjCoefficients(),numberColumns*sizeof(double)); |
---|
4016 | double direction = solver_->getObjSense(); |
---|
4017 | |
---|
4018 | // add in objective if there is a cutoff |
---|
4019 | if (useCutoff<1.0e30) { |
---|
4020 | // get new version of model |
---|
4021 | solver = solver_->clone(); |
---|
4022 | CoinPackedVector newRow; |
---|
4023 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
---|
4024 | solver->setObjCoeff(iColumn,0.0); // zero out in new model |
---|
4025 | if (objective[iColumn]) |
---|
4026 | newRow.insert(iColumn,direction * objective[iColumn]); |
---|
4027 | |
---|
4028 | } |
---|
4029 | solver->addRow(newRow,-COIN_DBL_MAX,useCutoff); |
---|
4030 | // signal no objective |
---|
4031 | delete [] objective; |
---|
4032 | objective=NULL; |
---|
4033 | } |
---|
4034 | setCutoff(COIN_DBL_MAX); |
---|
4035 | |
---|
4036 | |
---|
4037 | bool * vub = new bool [numberColumns]; |
---|
4038 | int iVub; |
---|
4039 | |
---|
4040 | // mark vub columns |
---|
4041 | for (iColumn=0;iColumn<numberColumns;iColumn++) |
---|
4042 | vub[iColumn]=false; |
---|
4043 | for (iVub=0;iVub<numberSolves;iVub++) |
---|
4044 | vub[which[iVub]]=true; |
---|
4045 | OsiCuts cuts; |
---|
4046 | // First tighten bounds anyway if CglProbing there |
---|
4047 | CglProbing* generator = NULL; |
---|
4048 | int iGen; |
---|
4049 | for (iGen=0;iGen<numberCutGenerators_;iGen++) { |
---|
4050 | generator = dynamic_cast<CglProbing*>(generator_[iGen]->generator()); |
---|
4051 | if (generator) |
---|
4052 | break; |
---|
4053 | } |
---|
4054 | int numberFixed=0; |
---|
4055 | int numberTightened=0; |
---|
4056 | int numberFixedByProbing=0; |
---|
4057 | int numberTightenedByProbing=0; |
---|
4058 | int printFrequency = (numberSolves+19)/20; // up to 20 messages |
---|
4059 | int save[4]; |
---|
4060 | if (generator) { |
---|
4061 | // set to cheaper and then restore at end |
---|
4062 | save[0]=generator->getMaxPass(); |
---|
4063 | save[1]=generator->getMaxProbe(); |
---|
4064 | save[2]=generator->getMaxLook(); |
---|
4065 | save[3]=generator->rowCuts(); |
---|
4066 | generator->setMaxPass(1); |
---|
4067 | generator->setMaxProbe(10); |
---|
4068 | generator->setMaxLook(50); |
---|
4069 | generator->setRowCuts(0); |
---|
4070 | |
---|
4071 | // Probing - return tight column bounds |
---|
4072 | generator->generateCutsAndModify(*solver,cuts); |
---|
4073 | const double * tightLower = generator->tightLower(); |
---|
4074 | const double * lower = solver->getColLower(); |
---|
4075 | const double * tightUpper = generator->tightUpper(); |
---|
4076 | const double * upper = solver->getColUpper(); |
---|
4077 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
---|
4078 | double newUpper = tightUpper[iColumn]; |
---|
4079 | double newLower = tightLower[iColumn]; |
---|
4080 | if (newUpper<upper[iColumn]-1.0e-8*(fabs(upper[iColumn])+1)|| |
---|
4081 | newLower>lower[iColumn]+1.0e-8*(fabs(lower[iColumn])+1)) { |
---|
4082 | if (newUpper<newLower) { |
---|
4083 | fprintf(stderr,"Problem is infeasible\n"); |
---|
4084 | return false; |
---|
4085 | } |
---|
4086 | if (newUpper==newLower) { |
---|
4087 | numberFixed++; |
---|
4088 | numberFixedByProbing++; |
---|
4089 | solver->setColLower(iColumn,newLower); |
---|
4090 | solver->setColUpper(iColumn,newUpper); |
---|
4091 | printf("Column %d, new bounds %g %g\n",iColumn, |
---|
4092 | newLower,newUpper); |
---|
4093 | } else if (vub[iColumn]) { |
---|
4094 | numberTightened++; |
---|
4095 | numberTightenedByProbing++; |
---|
4096 | if (!solver->isInteger(iColumn)) { |
---|
4097 | // relax |
---|
4098 | newLower=CoinMax(lower[iColumn], |
---|
4099 | newLower |
---|
4100 | -1.0e-5*(fabs(lower[iColumn])+1)); |
---|
4101 | newUpper=CoinMin(upper[iColumn], |
---|
4102 | newUpper |
---|
4103 | +1.0e-5*(fabs(upper[iColumn])+1)); |
---|
4104 | } |
---|
4105 | solver->setColLower(iColumn,newLower); |
---|
4106 | solver->setColUpper(iColumn,newUpper); |
---|
4107 | } |
---|
4108 | } |
---|
4109 | } |
---|
4110 | } |
---|
4111 | CoinWarmStart * ws = solver->getWarmStart(); |
---|
4112 | double * solution = new double [numberColumns]; |
---|
4113 | memcpy(solution,solver->getColSolution(),numberColumns*sizeof(double)); |
---|
4114 | for (iColumn=0;iColumn<numberColumns;iColumn++) |
---|
4115 | solver->setObjCoeff(iColumn,0.0); |
---|
4116 | //solver->messageHandler()->setLogLevel(2); |
---|
4117 | for (iVub=0;iVub<numberSolves;iVub++) { |
---|
4118 | iColumn = which[iVub]; |
---|
4119 | int iTry; |
---|
4120 | for (iTry=0;iTry<2;iTry++) { |
---|
4121 | double saveUpper = solver->getColUpper()[iColumn]; |
---|
4122 | double saveLower = solver->getColLower()[iColumn]; |
---|
4123 | double value; |
---|
4124 | if (iTry==1) { |
---|
4125 | // try all way up |
---|
4126 | solver->setObjCoeff(iColumn,-1.0); |
---|
4127 | } else { |
---|
4128 | // try all way down |
---|
4129 | solver->setObjCoeff(iColumn,1.0); |
---|
4130 | } |
---|
4131 | solver->initialSolve(); |
---|
4132 | value = solver->getColSolution()[iColumn]; |
---|
4133 | bool change=false; |
---|
4134 | if (iTry==1) { |
---|
4135 | if (value<saveUpper-1.0e-4) { |
---|
4136 | if (solver->isInteger(iColumn)) { |
---|
4137 | value = floor(value+0.00001); |
---|
4138 | } else { |
---|
4139 | // relax a bit |
---|
4140 | value=CoinMin(saveUpper,value+1.0e-5*(fabs(saveUpper)+1)); |
---|
4141 | } |
---|
4142 | if (value-saveLower<1.0e-7) |
---|
4143 | value = saveLower; // make sure exactly same |
---|
4144 | solver->setColUpper(iColumn,value); |
---|
4145 | saveUpper=value; |
---|
4146 | change=true; |
---|
4147 | } |
---|
4148 | } else { |
---|
4149 | if (value>saveLower+1.0e-4) { |
---|
4150 | if (solver->isInteger(iColumn)) { |
---|
4151 | value = ceil(value-0.00001); |
---|
4152 | } else { |
---|
4153 | // relax a bit |
---|
4154 | value=CoinMax(saveLower,value-1.0e-5*(fabs(saveLower)+1)); |
---|
4155 | } |
---|
4156 | if (saveUpper-value<1.0e-7) |
---|
4157 | value = saveUpper; // make sure exactly same |
---|
4158 | solver->setColLower(iColumn,value); |
---|
4159 | saveLower=value; |
---|
4160 | change=true; |
---|
4161 | } |
---|
4162 | } |
---|
4163 | solver->setObjCoeff(iColumn,0.0); |
---|
4164 | if (change) { |
---|
4165 | if (saveUpper==saveLower) |
---|
4166 | numberFixed++; |
---|
4167 | else |
---|
4168 | numberTightened++; |
---|
4169 | int saveFixed=numberFixed; |
---|
4170 | |
---|
4171 | int jColumn; |
---|
4172 | if (generator) { |
---|
4173 | // Probing - return tight column bounds |
---|
4174 | cuts = OsiCuts(); |
---|
4175 | generator->generateCutsAndModify(*solver,cuts); |
---|
4176 | const double * tightLower = generator->tightLower(); |
---|
4177 | const double * lower = solver->getColLower(); |
---|
4178 | const double * tightUpper = generator->tightUpper(); |
---|
4179 | const double * upper = solver->getColUpper(); |
---|
4180 | for (jColumn=0;jColumn<numberColumns;jColumn++) { |
---|
4181 | double newUpper = tightUpper[jColumn]; |
---|
4182 | double newLower = tightLower[jColumn]; |
---|
4183 | if (newUpper<upper[jColumn]-1.0e-8*(fabs(upper[jColumn])+1)|| |
---|
4184 | newLower>lower[jColumn]+1.0e-8*(fabs(lower[jColumn])+1)) { |
---|
4185 | if (newUpper<newLower) { |
---|
4186 | fprintf(stderr,"Problem is infeasible\n"); |
---|
4187 | return false; |
---|
4188 | } |
---|
4189 | if (newUpper==newLower) { |
---|
4190 | numberFixed++; |
---|
4191 | numberFixedByProbing++; |
---|
4192 | solver->setColLower(jColumn,newLower); |
---|
4193 | solver->setColUpper(jColumn,newUpper); |
---|
4194 | } else if (vub[jColumn]) { |
---|
4195 | numberTightened++; |
---|
4196 | numberTightenedByProbing++; |
---|
4197 | if (!solver->isInteger(jColumn)) { |
---|
4198 | // relax |
---|
4199 | newLower=CoinMax(lower[jColumn], |
---|
4200 | newLower |
---|
4201 | -1.0e-5*(fabs(lower[jColumn])+1)); |
---|
4202 | newUpper=CoinMin(upper[jColumn], |
---|
4203 | newUpper |
---|
4204 | +1.0e-5*(fabs(upper[jColumn])+1)); |
---|
4205 | } |
---|
4206 | solver->setColLower(jColumn,newLower); |
---|
4207 | solver->setColUpper(jColumn,newUpper); |
---|
4208 | } |
---|
4209 | } |
---|
4210 | } |
---|
4211 | } |
---|
4212 | if (numberFixed>saveFixed) { |
---|
4213 | // original solution may not be feasible |
---|
4214 | // go back to true costs to solve if exists |
---|
4215 | if (objective) { |
---|
4216 | for (jColumn=0;jColumn<numberColumns;jColumn++) |
---|
4217 | solver->setObjCoeff(jColumn,objective[jColumn]); |
---|
4218 | } |
---|
4219 | solver->setColSolution(solution); |
---|
4220 | solver->setWarmStart(ws); |
---|
4221 | solver->resolve(); |
---|
4222 | if (!solver->isProvenOptimal()) { |
---|
4223 | fprintf(stderr,"Problem is infeasible\n"); |
---|
4224 | return false; |
---|
4225 | } |
---|
4226 | delete ws; |
---|
4227 | ws = solver->getWarmStart(); |
---|
4228 | memcpy(solution,solver->getColSolution(), |
---|
4229 | numberColumns*sizeof(double)); |
---|
4230 | for (jColumn=0;jColumn<numberColumns;jColumn++) |
---|
4231 | solver->setObjCoeff(jColumn,0.0); |
---|
4232 | } |
---|
4233 | } |
---|
4234 | solver->setColSolution(solution); |
---|
4235 | solver->setWarmStart(ws); |
---|
4236 | } |
---|
4237 | if (iVub%printFrequency==0) |
---|
4238 | handler_->message(CBC_VUB_PASS,messages_) |
---|
4239 | <<iVub+1<<numberFixed<<numberTightened |
---|
4240 | <<CoinMessageEol; |
---|
4241 | } |
---|
4242 | handler_->message(CBC_VUB_END,messages_) |
---|
4243 | <<numberFixed<<numberTightened |
---|
4244 | <<CoinMessageEol; |
---|
4245 | delete ws; |
---|
4246 | delete [] solution; |
---|
4247 | // go back to true costs to solve if exists |
---|
4248 | if (objective) { |
---|
4249 | for (iColumn=0;iColumn<numberColumns;iColumn++) |
---|
4250 | solver_->setObjCoeff(iColumn,objective[iColumn]); |
---|
4251 | delete [] objective; |
---|
4252 | } |
---|
4253 | delete [] vub; |
---|
4254 | if (generator) { |
---|
4255 | /*printf("Probing fixed %d and tightened %d\n", |
---|
4256 | numberFixedByProbing, |
---|
4257 | numberTightenedByProbing);*/ |
---|
4258 | if (generator_[iGen]->howOften()==-1&& |
---|
4259 | (numberFixedByProbing+numberTightenedByProbing)*5> |
---|
4260 | (numberFixed+numberTightened)) |
---|
4261 | generator_[iGen]->setHowOften(1000000+1); |
---|
4262 | generator->setMaxPass(save[0]); |
---|
4263 | generator->setMaxProbe(save[1]); |
---|
4264 | generator->setMaxLook(save[2]); |
---|
4265 | generator->setRowCuts(save[3]); |
---|
4266 | } |
---|
4267 | |
---|
4268 | if (solver!=solver_) { |
---|
4269 | // move bounds across |
---|
4270 | const double * lower = solver->getColLower(); |
---|
4271 | const double * upper = solver->getColUpper(); |
---|
4272 | const double * lowerOrig = solver_->getColLower(); |
---|
4273 | const double * upperOrig = solver_->getColUpper(); |
---|
4274 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
---|
4275 | solver_->setColLower(iColumn,CoinMax(lower[iColumn],lowerOrig[iColumn])); |
---|
4276 | solver_->setColUpper(iColumn,CoinMin(upper[iColumn],upperOrig[iColumn])); |
---|
4277 | } |
---|
4278 | delete solver; |
---|
4279 | } |
---|
4280 | setCutoff(saveCutoff); |
---|
4281 | return true; |
---|
4282 | } |
---|
4283 | /* |
---|
4284 | Do Integer Presolve. Returns new model. |
---|
4285 | I have to work out cleanest way of getting solution to |
---|
4286 | original problem at end. So this is very preliminary. |
---|
4287 | */ |
---|
4288 | CbcModel * |
---|
4289 | CbcModel::integerPresolve(bool weak) |
---|
4290 | { |
---|
4291 | status_ = 0; |
---|
4292 | // solve LP |
---|
4293 | //solver_->writeMps("bad"); |
---|
4294 | bool feasible = resolve(); |
---|
4295 | |
---|
4296 | CbcModel * newModel = NULL; |
---|
4297 | if (feasible) { |
---|
4298 | |
---|
4299 | // get a new model |
---|
4300 | newModel = new CbcModel(*this); |
---|
4301 | newModel->messageHandler()->setLogLevel(messageHandler()->logLevel()); |
---|
4302 | |
---|
4303 | feasible = newModel->integerPresolveThisModel(solver_,weak); |
---|
4304 | } |
---|
4305 | if (!feasible) { |
---|
4306 | handler_->message(CBC_INFEAS,messages_) |
---|
4307 | <<CoinMessageEol; |
---|
4308 | status_ = 0; |
---|
4309 | delete newModel; |
---|
4310 | return NULL; |
---|
4311 | } else { |
---|
4312 | newModel->synchronizeModel(); // make sure everything that needs solver has it |
---|
4313 | return newModel; |
---|
4314 | } |
---|
4315 | } |
---|
4316 | /* |
---|
4317 | Do Integer Presolve - destroying current model |
---|
4318 | */ |
---|
4319 | bool |
---|
4320 | CbcModel::integerPresolveThisModel(OsiSolverInterface * originalSolver, |
---|
4321 | bool weak) |
---|
4322 | { |
---|
4323 | status_ = 0; |
---|
4324 | // solve LP |
---|
4325 | bool feasible = resolve(); |
---|
4326 | |
---|
4327 | bestObjective_=1.0e50; |
---|
4328 | numberSolutions_=0; |
---|
4329 | numberHeuristicSolutions_=0; |
---|
4330 | double cutoff = getCutoff() ; |
---|
4331 | double direction = solver_->getObjSense(); |
---|
4332 | if (cutoff < 1.0e20&&direction<0.0) |
---|
4333 | messageHandler()->message(CBC_CUTOFF_WARNING1, |
---|
4334 | messages()) |
---|
4335 | << cutoff << -cutoff << CoinMessageEol ; |
---|
4336 | if (cutoff > bestObjective_) |
---|
4337 | cutoff = bestObjective_ ; |
---|
4338 | setCutoff(cutoff) ; |
---|
4339 | int iColumn; |
---|
4340 | int numberColumns = getNumCols(); |
---|
4341 | int originalNumberColumns = numberColumns; |
---|
4342 | currentPassNumber_=0; |
---|
4343 | synchronizeModel(); // make sure everything that needs solver has it |
---|
4344 | // just point to solver_ |
---|
4345 | delete continuousSolver_; |
---|
4346 | continuousSolver_ = solver_; |
---|
4347 | // get a copy of original so we can fix bounds |
---|
4348 | OsiSolverInterface * cleanModel = originalSolver->clone(); |
---|
4349 | #ifdef CBC_DEBUG |
---|
4350 | std::string problemName; |
---|
4351 | cleanModel->getStrParam(OsiProbName,problemName); |
---|
4352 | printf("Problem name - %s\n",problemName.c_str()); |
---|
4353 | cleanModel->activateRowCutDebugger(problemName.c_str()); |
---|
4354 | const OsiRowCutDebugger * debugger = cleanModel->getRowCutDebugger(); |
---|
4355 | #endif |
---|
4356 | |
---|
4357 | // array which points from original columns to presolved |
---|
4358 | int * original = new int[numberColumns]; |
---|
4359 | // arrays giving bounds - only ones found by probing |
---|
4360 | // rest will be found by presolve |
---|
4361 | double * originalLower = new double[numberColumns]; |
---|
4362 | double * originalUpper = new double[numberColumns]; |
---|
4363 | { |
---|
4364 | const double * lower = getColLower(); |
---|
4365 | const double * upper = getColUpper(); |
---|
4366 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
---|
4367 | original[iColumn]=iColumn; |
---|
4368 | originalLower[iColumn] = lower[iColumn]; |
---|
4369 | originalUpper[iColumn] = upper[iColumn]; |
---|
4370 | } |
---|
4371 | } |
---|
4372 | findIntegers(true); |
---|
4373 | // save original integers |
---|
4374 | int * originalPriority = NULL; |
---|
4375 | int * originalIntegers = new int[numberIntegers_]; |
---|
4376 | int originalNumberIntegers = numberIntegers_; |
---|
4377 | memcpy(originalIntegers,integerVariable_,numberIntegers_*sizeof(int)); |
---|
4378 | |
---|
4379 | if (priority_) { |
---|
4380 | originalPriority = new int[numberIntegers_]; |
---|
4381 | memcpy(originalPriority,priority_,numberIntegers_*sizeof(int)); |
---|
4382 | delete [] priority_; |
---|
4383 | priority_=NULL; |
---|
4384 | } |
---|
4385 | int todo=20; |
---|
4386 | if (weak) |
---|
4387 | todo=1; |
---|
4388 | while (currentPassNumber_<todo) { |
---|
4389 | |
---|
4390 | currentPassNumber_++; |
---|
4391 | numberSolutions_=0; |
---|
4392 | // this will be set false to break out of loop with presolved problem |
---|
4393 | bool doIntegerPresolve=(currentPassNumber_!=20); |
---|
4394 | |
---|
4395 | // Current number of free integer variables |
---|
4396 | // Get increment in solutions |
---|
4397 | { |
---|
4398 | const double * objective = cleanModel->getObjCoefficients(); |
---|
4399 | const double * lower = cleanModel->getColLower(); |
---|
4400 | const double * upper = cleanModel->getColUpper(); |
---|
4401 | double maximumCost=0.0; |
---|
4402 | bool possibleMultiple=true; |
---|
4403 | int numberChanged=0; |
---|
4404 | for (iColumn=0;iColumn<originalNumberColumns;iColumn++) { |
---|
4405 | if (originalUpper[iColumn]>originalLower[iColumn]) { |
---|
4406 | if( cleanModel->isInteger(iColumn)) { |
---|
4407 | maximumCost = CoinMax(maximumCost,fabs(objective[iColumn])); |
---|
4408 | } else if (objective[iColumn]) { |
---|
4409 | possibleMultiple=false; |
---|
4410 | } |
---|
4411 | } |
---|
4412 | if (originalUpper[iColumn]<upper[iColumn]) { |
---|
4413 | #ifdef CBC_DEBUG |
---|
4414 | printf("Changing upper bound on %d from %g to %g\n", |
---|
4415 | iColumn,upper[iColumn],originalUpper[iColumn]); |
---|
4416 | #endif |
---|
4417 | cleanModel->setColUpper(iColumn,originalUpper[iColumn]); |
---|
4418 | numberChanged++; |
---|
4419 | } |
---|
4420 | if (originalLower[iColumn]>lower[iColumn]) { |
---|
4421 | #ifdef CBC_DEBUG |
---|
4422 | printf("Changing lower bound on %d from %g to %g\n", |
---|
4423 | iColumn,lower[iColumn],originalLower[iColumn]); |
---|
4424 | #endif |
---|
4425 | cleanModel->setColLower(iColumn,originalLower[iColumn]); |
---|
4426 | numberChanged++; |
---|
4427 | } |
---|
4428 | } |
---|
4429 | // if first pass - always try |
---|
4430 | if (currentPassNumber_==1) |
---|
4431 | numberChanged += 1; |
---|
4432 | if (possibleMultiple) { |
---|
4433 | int increment=0; |
---|
4434 | double multiplier = 2520.0; |
---|
4435 | while (10.0*multiplier*maximumCost<1.0e8) |
---|
4436 | multiplier *= 10.0; |
---|
4437 | for (iColumn=0;iColumn<originalNumberColumns;iColumn++) { |
---|
4438 | if (originalUpper[iColumn]>originalLower[iColumn]) { |
---|
4439 | if( originalIntegers[iColumn]&&objective[iColumn]) { |
---|
4440 | double value = fabs(objective[iColumn])*multiplier; |
---|
4441 | int nearest = (int) floor(value+0.5); |
---|
4442 | if (fabs(value-floor(value+0.5))>1.0e-8) { |
---|
4443 | increment=0; |
---|
4444 | break; // no good |
---|
4445 | } else if (!increment) { |
---|
4446 | // first |
---|
4447 | increment=nearest; |
---|
4448 | } else { |
---|
4449 | increment = gcd(increment,nearest); |
---|
4450 | } |
---|
4451 | } |
---|
4452 | } |
---|
4453 | } |
---|
4454 | if (increment) { |
---|
4455 | double value = increment; |
---|
4456 | value /= multiplier; |
---|
4457 | if (value*0.999>dblParam_[CbcCutoffIncrement]) { |
---|
4458 | messageHandler()->message(CBC_INTEGERINCREMENT,messages()) |
---|
4459 | <<value |
---|
4460 | <<CoinMessageEol; |
---|
4461 | dblParam_[CbcCutoffIncrement]=value*0.999; |
---|
4462 | } |
---|
4463 | } |
---|
4464 | } |
---|
4465 | if (!numberChanged) { |
---|
4466 | doIntegerPresolve=false; // not doing any better |
---|
4467 | } |
---|
4468 | } |
---|
4469 | #ifdef CBC_DEBUG |
---|
4470 | if (debugger) |
---|
4471 | assert(debugger->onOptimalPath(*cleanModel)); |
---|
4472 | #endif |
---|
4473 | #ifdef COIN_USE_CLP |
---|
4474 | // do presolve - for now just clp but easy to get osi interface |
---|
4475 | OsiClpSolverInterface * clpSolver |
---|
4476 | = dynamic_cast<OsiClpSolverInterface *> (cleanModel); |
---|
4477 | if (clpSolver) { |
---|
4478 | ClpSimplex * clp = clpSolver->getModelPtr(); |
---|
4479 | ClpPresolve pinfo; |
---|
4480 | //printf("integerPresolve - temp switch off doubletons\n"); |
---|
4481 | //pinfo.setPresolveActions(4); |
---|
4482 | ClpSimplex * model2 = pinfo.presolvedModel(*clp,1.0e-8); |
---|
4483 | if (!model2) { |
---|
4484 | // presolve found to be infeasible |
---|
4485 | feasible=false; |
---|
4486 | } else { |
---|
4487 | // update original array |
---|
4488 | const int * originalColumns = pinfo.originalColumns(); |
---|
4489 | // just slot in new solver |
---|
4490 | OsiClpSolverInterface * temp = new OsiClpSolverInterface(model2,true); |
---|
4491 | numberColumns = temp->getNumCols(); |
---|
4492 | for (iColumn=0;iColumn<originalNumberColumns;iColumn++) |
---|
4493 | original[iColumn]=-1; |
---|
4494 | for (iColumn=0;iColumn<numberColumns;iColumn++) |
---|
4495 | original[originalColumns[iColumn]]=iColumn; |
---|
4496 | // copy parameters |
---|
4497 | temp->copyParameters(*solver_); |
---|
4498 | // and specialized ones |
---|
4499 | temp->setSpecialOptions(clpSolver->specialOptions()); |
---|
4500 | delete solver_; |
---|
4501 | solver_ = temp; |
---|
4502 | setCutoff(cutoff); |
---|
4503 | deleteObjects(); |
---|
4504 | if (!numberObjects_) { |
---|
4505 | // Nothing left |
---|
4506 | doIntegerPresolve=false; |
---|
4507 | weak=true; |
---|
4508 | break; |
---|
4509 | } |
---|
4510 | synchronizeModel(); // make sure everything that needs solver has it |
---|
4511 | // just point to solver_ |
---|
4512 | continuousSolver_ = solver_; |
---|
4513 | feasible=resolve(); |
---|
4514 | if (!feasible||!doIntegerPresolve||weak) break; |
---|
4515 | // see if we can get solution by heuristics |
---|
4516 | int found=-1; |
---|
4517 | int iHeuristic; |
---|
4518 | double * newSolution = new double [numberColumns]; |
---|
4519 | double heuristicValue=getCutoff(); |
---|
4520 | for (iHeuristic=0;iHeuristic<numberHeuristics_;iHeuristic++) { |
---|
4521 | double saveValue=heuristicValue; |
---|
4522 | int ifSol = heuristic_[iHeuristic]->solution(heuristicValue, |
---|
4523 | newSolution); |
---|
4524 | if (ifSol>0) { |
---|
4525 | // better solution found |
---|
4526 | found=iHeuristic; |
---|
4527 | } else if (ifSol<0) { |
---|
4528 | heuristicValue = saveValue; |
---|
4529 | } |
---|
4530 | } |
---|
4531 | if (found >= 0) { |
---|
4532 | // We probably already have a current solution, but just in case ... |
---|
4533 | int numberColumns = getNumCols() ; |
---|
4534 | if (!currentSolution_) |
---|
4535 | currentSolution_ = new double[numberColumns] ; |
---|
4536 | // better solution save |
---|
4537 | setBestSolution(CBC_ROUNDING,heuristicValue, |
---|
4538 | newSolution); |
---|
4539 | // update cutoff |
---|
4540 | cutoff = getCutoff(); |
---|
4541 | } |
---|
4542 | delete [] newSolution; |
---|
4543 | // Space for type of cuts |
---|
4544 | int maximumWhich=1000; |
---|
4545 | int * whichGenerator = new int[maximumWhich]; |
---|
4546 | // save number of rows |
---|
4547 | numberRowsAtContinuous_ = getNumRows(); |
---|
4548 | maximumNumberCuts_=0; |
---|
4549 | currentNumberCuts_=0; |
---|
4550 | delete [] addedCuts_; |
---|
4551 | addedCuts_ = NULL; |
---|
4552 | |
---|
4553 | // maximum depth for tree walkback |
---|
4554 | maximumDepth_=10; |
---|
4555 | delete [] walkback_; |
---|
4556 | walkback_ = new CbcNodeInfo * [maximumDepth_]; |
---|
4557 | |
---|
4558 | OsiCuts cuts; |
---|
4559 | int numberOldActiveCuts=0; |
---|
4560 | int numberNewCuts = 0; |
---|
4561 | feasible = solveWithCuts(cuts,maximumCutPassesAtRoot_, |
---|
4562 | NULL,numberOldActiveCuts,numberNewCuts, |
---|
4563 | maximumWhich, whichGenerator); |
---|
4564 | currentNumberCuts_=numberNewCuts; |
---|
4565 | delete [] whichGenerator; |
---|
4566 | delete [] walkback_; |
---|
4567 | walkback_ = NULL; |
---|
4568 | delete [] addedCuts_; |
---|
4569 | addedCuts_=NULL; |
---|
4570 | if (feasible) { |
---|
4571 | // fix anything in original which integer presolve fixed |
---|
4572 | // for now just integers |
---|
4573 | const double * lower = solver_->getColLower(); |
---|
4574 | const double * upper = solver_->getColUpper(); |
---|
4575 | int i; |
---|
4576 | for (i=0;i<originalNumberIntegers;i++) { |
---|
4577 | iColumn = originalIntegers[i]; |
---|
4578 | int jColumn = original[iColumn]; |
---|
4579 | if (jColumn >= 0) { |
---|
4580 | if (upper[jColumn]<originalUpper[iColumn]) |
---|
4581 | originalUpper[iColumn] = upper[jColumn]; |
---|
4582 | if (lower[jColumn]>originalLower[iColumn]) |
---|
4583 | originalLower[iColumn] = lower[jColumn]; |
---|
4584 | } |
---|
4585 | } |
---|
4586 | } |
---|
4587 | } |
---|
4588 | } |
---|
4589 | #endif |
---|
4590 | if (!feasible||!doIntegerPresolve) { |
---|
4591 | break; |
---|
4592 | } |
---|
4593 | } |
---|
4594 | //solver_->writeMps("xx"); |
---|
4595 | delete cleanModel; |
---|
4596 | // create new priorities and save list of original columns |
---|
4597 | if (originalPriority) { |
---|
4598 | priority_ = new int[numberIntegers_]; |
---|
4599 | int i; |
---|
4600 | int number=0; |
---|
4601 | // integer variables are in same order if they exist at all |
---|
4602 | for (i=0;i<originalNumberIntegers;i++) { |
---|
4603 | iColumn = originalIntegers[i]; |
---|
4604 | int newColumn=original[iColumn]; |
---|
4605 | if (newColumn >= 0) |
---|
4606 | priority_[number++]=originalPriority[i]; |
---|
4607 | } |
---|
4608 | assert (number==numberIntegers_); |
---|
4609 | delete [] originalPriority; |
---|
4610 | } |
---|
4611 | delete [] originalIntegers; |
---|
4612 | numberColumns = getNumCols(); |
---|
4613 | delete [] originalColumns_; |
---|
4614 | originalColumns_ = new int[numberColumns]; |
---|
4615 | numberColumns=0; |
---|
4616 | for (iColumn=0;iColumn<originalNumberColumns;iColumn++) { |
---|
4617 | int jColumn = original[iColumn]; |
---|
4618 | if (jColumn >= 0) |
---|
4619 | originalColumns_[numberColumns++]=iColumn; |
---|
4620 | } |
---|
4621 | delete [] original; |
---|
4622 | delete [] originalLower; |
---|
4623 | delete [] originalUpper; |
---|
4624 | |
---|
4625 | deleteObjects(); |
---|
4626 | synchronizeModel(); // make sure everything that needs solver has it |
---|
4627 | continuousSolver_=NULL; |
---|
4628 | currentNumberCuts_=0; |
---|
4629 | return feasible; |
---|
4630 | } |
---|
4631 | // Put back information into original model - after integerpresolve |
---|
4632 | void |
---|
4633 | CbcModel::originalModel(CbcModel * presolvedModel,bool weak) |
---|
4634 | { |
---|
4635 | solver_->copyParameters(*(presolvedModel->solver_)); |
---|
4636 | bestObjective_ = presolvedModel->bestObjective_; |
---|
4637 | delete [] bestSolution_; |
---|
4638 | findIntegers(true); |
---|
4639 | if (presolvedModel->bestSolution_) { |
---|
4640 | int numberColumns = getNumCols(); |
---|
4641 | int numberOtherColumns = presolvedModel->getNumCols(); |
---|
4642 | //bestSolution_ = new double[numberColumns]; |
---|
4643 | // set up map |
---|
4644 | int * back = new int[numberColumns]; |
---|
4645 | int i; |
---|
4646 | for (i=0;i<numberColumns;i++) |
---|
4647 | back[i]=-1; |
---|
4648 | for (i=0;i<numberOtherColumns;i++) |
---|
4649 | back[presolvedModel->originalColumns_[i]]=i; |
---|
4650 | int iColumn; |
---|
4651 | // set ones in presolved model to values |
---|
4652 | double * otherSolution = presolvedModel->bestSolution_; |
---|
4653 | //const double * lower = getColLower(); |
---|
4654 | for (i=0;i<numberIntegers_;i++) { |
---|
4655 | iColumn = integerVariable_[i]; |
---|
4656 | int jColumn = back[iColumn]; |
---|
4657 | //bestSolution_[iColumn]=lower[iColumn]; |
---|
4658 | if (jColumn >= 0) { |
---|
4659 | double value=floor(otherSolution[jColumn]+0.5); |
---|
4660 | solver_->setColLower(iColumn,value); |
---|
4661 | solver_->setColUpper(iColumn,value); |
---|
4662 | //bestSolution_[iColumn]=value; |
---|
4663 | } |
---|
4664 | } |
---|
4665 | delete [] back; |
---|
4666 | #if 0 |
---|
4667 | // ** looks as if presolve needs more intelligence |
---|
4668 | // do presolve - for now just clp but easy to get osi interface |
---|
4669 | OsiClpSolverInterface * clpSolver |
---|
4670 | = dynamic_cast<OsiClpSolverInterface *> (solver_); |
---|
4671 | assert (clpSolver); |
---|
4672 | ClpSimplex * clp = clpSolver->getModelPtr(); |
---|
4673 | Presolve pinfo; |
---|
4674 | ClpSimplex * model2 = pinfo.presolvedModel(*clp,1.0e-8); |
---|
4675 | model2->primal(1); |
---|
4676 | pinfo.postsolve(true); |
---|
4677 | const double * solution = solver_->getColSolution(); |
---|
4678 | for (i=0;i<numberIntegers_;i++) { |
---|
4679 | iColumn = integerVariable_[i]; |
---|
4680 | double value=floor(solution[iColumn]+0.5); |
---|
4681 | solver_->setColLower(iColumn,value); |
---|
4682 | solver_->setColUpper(iColumn,value); |
---|
4683 | } |
---|
4684 | #else |
---|
4685 | if (!weak) { |
---|
4686 | // for now give up |
---|
4687 | int save = numberCutGenerators_; |
---|
4688 | numberCutGenerators_=0; |
---|
4689 | bestObjective_=1.0e100; |
---|
4690 | branchAndBound(); |
---|
4691 | numberCutGenerators_=save; |
---|
4692 | } |
---|
4693 | #endif |
---|
4694 | if (bestSolution_) { |
---|
4695 | // solve problem |
---|
4696 | resolve(); |
---|
4697 | // should be feasible |
---|
4698 | int numberIntegerInfeasibilities; |
---|
4699 | int numberObjectInfeasibilities; |
---|
4700 | if (!currentSolution_) |
---|
4701 | currentSolution_ = new double[numberColumns] ; |
---|
4702 | assert(feasibleSolution(numberIntegerInfeasibilities, |
---|
4703 | numberObjectInfeasibilities)); |
---|
4704 | } |
---|
4705 | } else { |
---|
4706 | bestSolution_=NULL; |
---|
4707 | } |
---|
4708 | numberSolutions_=presolvedModel->numberSolutions_; |
---|
4709 | numberHeuristicSolutions_=presolvedModel->numberHeuristicSolutions_; |
---|
4710 | numberNodes_ = presolvedModel->numberNodes_; |
---|
4711 | numberIterations_ = presolvedModel->numberIterations_; |
---|
4712 | status_ = presolvedModel->status_; |
---|
4713 | synchronizeModel(); |
---|
4714 | } |
---|
4715 | // Pass in Message handler (not deleted at end) |
---|
4716 | void |
---|
4717 | CbcModel::passInMessageHandler(CoinMessageHandler * handler) |
---|
4718 | { |
---|
4719 | if (defaultHandler_) { |
---|
4720 | delete handler_; |
---|
4721 | handler_ = NULL; |
---|
4722 | } |
---|
4723 | defaultHandler_=false; |
---|
4724 | handler_=handler; |
---|
4725 | } |
---|
4726 | void |
---|
4727 | CbcModel::passInTreeHandler(CbcTree & tree) |
---|
4728 | { |
---|
4729 | delete tree_; |
---|
4730 | tree_ = tree.clone(); |
---|
4731 | } |
---|
4732 | // Make sure region there |
---|
4733 | void |
---|
4734 | CbcModel::reserveCurrentSolution() |
---|
4735 | { |
---|
4736 | int numberColumns = getNumCols() ; |
---|
4737 | if (!currentSolution_) |
---|
4738 | currentSolution_ = new double[numberColumns] ; |
---|
4739 | } |
---|
4740 | /* For passing in an CbcModel to do a sub Tree (with derived tree handlers). |
---|
4741 | Passed in model must exist for duration of branch and bound |
---|
4742 | */ |
---|
4743 | void |
---|
4744 | CbcModel::passInSubTreeModel(CbcModel & model) |
---|
4745 | { |
---|
4746 | subTreeModel_=&model; |
---|
4747 | } |
---|
4748 | // For retrieving a copy of subtree model with given OsiSolver or NULL |
---|
4749 | CbcModel * |
---|
4750 | CbcModel::subTreeModel(OsiSolverInterface * solver) const |
---|
4751 | { |
---|
4752 | const CbcModel * subModel=subTreeModel_; |
---|
4753 | if (!subModel) |
---|
4754 | subModel=this; |
---|
4755 | // Get new copy |
---|
4756 | CbcModel * newModel = new CbcModel(*subModel); |
---|
4757 | if (solver) |
---|
4758 | newModel->assignSolver(solver); |
---|
4759 | return newModel; |
---|
4760 | } |
---|
4761 | //############################################################################# |
---|
4762 | // Set/Get Application Data |
---|
4763 | // This is a pointer that the application can store into and retrieve |
---|
4764 | // from the solverInterface. |
---|
4765 | // This field is the application to optionally define and use. |
---|
4766 | //############################################################################# |
---|
4767 | |
---|
4768 | void CbcModel::setApplicationData(void * appData) |
---|
4769 | { |
---|
4770 | appData_ = appData; |
---|
4771 | } |
---|
4772 | //----------------------------------------------------------------------------- |
---|
4773 | void * CbcModel::getApplicationData() const |
---|
4774 | { |
---|
4775 | return appData_; |
---|
4776 | } |
---|
4777 | /* create a submodel from partially fixed problem |
---|
4778 | |
---|
4779 | The method creates a new clean model with given bounds. |
---|
4780 | */ |
---|
4781 | CbcModel * |
---|
4782 | CbcModel::cleanModel(const double * lower, const double * upper) |
---|
4783 | { |
---|
4784 | OsiSolverInterface * solver = continuousSolver_->clone(); |
---|
4785 | |
---|
4786 | int numberIntegers = numberIntegers_; |
---|
4787 | const int * integerVariable = integerVariable_; |
---|
4788 | |
---|
4789 | int i; |
---|
4790 | for (i=0;i<numberIntegers;i++) { |
---|
4791 | int iColumn=integerVariable[i]; |
---|
4792 | const CbcObject * object = object_[i]; |
---|
4793 | const CbcSimpleInteger * integerObject = |
---|
4794 | dynamic_cast<const CbcSimpleInteger *> (object); |
---|
4795 | assert(integerObject); |
---|
4796 | // get original bounds |
---|
4797 | double originalLower = integerObject->originalLowerBound(); |
---|
4798 | double originalUpper = integerObject->originalUpperBound(); |
---|
4799 | solver->setColLower(iColumn,CoinMax(lower[iColumn],originalLower)); |
---|
4800 | solver->setColUpper(iColumn,CoinMin(upper[iColumn],originalUpper)); |
---|
4801 | } |
---|
4802 | CbcModel * model = new CbcModel(*solver); |
---|
4803 | // off some messages |
---|
4804 | if (handler_->logLevel()<=1) { |
---|
4805 | model->messagesPointer()->setDetailMessage(3,9); |
---|
4806 | model->messagesPointer()->setDetailMessage(3,6); |
---|
4807 | model->messagesPointer()->setDetailMessage(3,4); |
---|
4808 | model->messagesPointer()->setDetailMessage(3,1); |
---|
4809 | model->messagesPointer()->setDetailMessage(3,13); |
---|
4810 | model->messagesPointer()->setDetailMessage(3,14); |
---|
4811 | model->messagesPointer()->setDetailMessage(3,3007); |
---|
4812 | } |
---|
4813 | // Cuts |
---|
4814 | for ( i = 0;i<numberCutGenerators_;i++) { |
---|
4815 | int howOften = generator_[i]->howOftenInSub(); |
---|
4816 | if (howOften>-100) { |
---|
4817 | CbcCutGenerator * generator = virginGenerator_[i]; |
---|
4818 | CglCutGenerator * cglGenerator = generator->generator(); |
---|
4819 | model->addCutGenerator(cglGenerator,howOften, |
---|
4820 | generator->cutGeneratorName(), |
---|
4821 | generator->normal(), |
---|
4822 | generator->atSolution(), |
---|
4823 | generator->whenInfeasible(), |
---|
4824 | -100, generator->whatDepthInSub(),-1); |
---|
4825 | } |
---|
4826 | } |
---|
4827 | double cutoff = getCutoff(); |
---|
4828 | model->setCutoff(cutoff); |
---|
4829 | return model; |
---|
4830 | } |
---|
4831 | /* Invoke the branch & cut algorithm on partially fixed problem |
---|
4832 | |
---|
4833 | The method uses a subModel created by cleanModel. The search |
---|
4834 | ends when the tree is exhausted or maximum nodes is reached. |
---|
4835 | |
---|
4836 | If better solution found then it is saved. |
---|
4837 | |
---|
4838 | Returns 0 if search completed and solution, 1 if not completed and solution, |
---|
4839 | 2 if completed and no solution, 3 if not completed and no solution. |
---|
4840 | |
---|
4841 | Normally okay to do subModel immediately followed by subBranchandBound |
---|
4842 | (== other form of subBranchAndBound) |
---|
4843 | but may need to get at model for advanced features. |
---|
4844 | |
---|
4845 | Deletes model |
---|
4846 | |
---|
4847 | */ |
---|
4848 | |
---|
4849 | int |
---|
4850 | CbcModel::subBranchAndBound(CbcModel * model, |
---|
4851 | CbcModel * presolvedModel, |
---|
4852 | int maximumNodes) |
---|
4853 | { |
---|
4854 | int i; |
---|
4855 | double cutoff=model->getCutoff(); |
---|
4856 | CbcModel * model2; |
---|
4857 | if (presolvedModel) |
---|
4858 | model2=presolvedModel; |
---|
4859 | else |
---|
4860 | model2=model; |
---|
4861 | // Do complete search |
---|
4862 | |
---|
4863 | for (i=0;i<numberHeuristics_;i++) { |
---|
4864 | model2->addHeuristic(heuristic_[i]); |
---|
4865 | model2->heuristic(i)->resetModel(model2); |
---|
4866 | } |
---|
4867 | // Definition of node choice |
---|
4868 | model2->setNodeComparison(nodeCompare_->clone()); |
---|
4869 | //model2->solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry); |
---|
4870 | model2->messageHandler()->setLogLevel(CoinMax(0,handler_->logLevel()-1)); |
---|
4871 | //model2->solver()->messageHandler()->setLogLevel(2); |
---|
4872 | model2->setMaximumCutPassesAtRoot(maximumCutPassesAtRoot_); |
---|
4873 | model2->setPrintFrequency(50); |
---|
4874 | model2->setIntParam(CbcModel::CbcMaxNumNode,maximumNodes); |
---|
4875 | model2->branchAndBound(); |
---|
4876 | delete model2->nodeComparison(); |
---|
4877 | if (model2->getMinimizationObjValue()>cutoff) { |
---|
4878 | // no good |
---|
4879 | if (model!=model2) |
---|
4880 | delete model2; |
---|
4881 | delete model; |
---|
4882 | return 2; |
---|
4883 | } |
---|
4884 | if (model!=model2) { |
---|
4885 | // get back solution |
---|
4886 | model->originalModel(model2,false); |
---|
4887 | delete model2; |
---|
4888 | } |
---|
4889 | int status; |
---|
4890 | if (model->getMinimizationObjValue()<cutoff&&model->bestSolution()) { |
---|
4891 | double objValue = model->getObjValue(); |
---|
4892 | const double * solution = model->bestSolution(); |
---|
4893 | setBestSolution(CBC_TREE_SOL,objValue,solution); |
---|
4894 | status = 0; |
---|
4895 | } else { |
---|
4896 | status=2; |
---|
4897 | } |
---|
4898 | if (model->status()) |
---|
4899 | status ++ ; // not finished search |
---|
4900 | delete model; |
---|
4901 | return status; |
---|
4902 | } |
---|
4903 | /* Invoke the branch & cut algorithm on partially fixed problem |
---|
4904 | |
---|
4905 | The method creates a new model with given bounds, presolves it |
---|
4906 | then proceeds to explore the branch & cut search tree. The search |
---|
4907 | ends when the tree is exhausted or maximum nodes is reached. |
---|
4908 | Returns 0 if search completed and solution, 1 if not completed and solution, |
---|
4909 | 2 if completed and no solution, 3 if not completed and no solution. |
---|
4910 | */ |
---|
4911 | int |
---|
4912 | CbcModel::subBranchAndBound(const double * lower, const double * upper, |
---|
4913 | int maximumNodes) |
---|
4914 | { |
---|
4915 | OsiSolverInterface * solver = continuousSolver_->clone(); |
---|
4916 | |
---|
4917 | int numberIntegers = numberIntegers_; |
---|
4918 | const int * integerVariable = integerVariable_; |
---|
4919 | |
---|
4920 | int i; |
---|
4921 | for (i=0;i<numberIntegers;i++) { |
---|
4922 | int iColumn=integerVariable[i]; |
---|
4923 | const CbcObject * object = object_[i]; |
---|
4924 | const CbcSimpleInteger * integerObject = |
---|
4925 | dynamic_cast<const CbcSimpleInteger *> (object); |
---|
4926 | assert(integerObject); |
---|
4927 | // get original bounds |
---|
4928 | double originalLower = integerObject->originalLowerBound(); |
---|
4929 | double originalUpper = integerObject->originalUpperBound(); |
---|
4930 | solver->setColLower(iColumn,CoinMax(lower[iColumn],originalLower)); |
---|
4931 | solver->setColUpper(iColumn,CoinMin(upper[iColumn],originalUpper)); |
---|
4932 | } |
---|
4933 | CbcModel model(*solver); |
---|
4934 | // off some messages |
---|
4935 | if (handler_->logLevel()<=1) { |
---|
4936 | model.messagesPointer()->setDetailMessage(3,9); |
---|
4937 | model.messagesPointer()->setDetailMessage(3,6); |
---|
4938 | model.messagesPointer()->setDetailMessage(3,4); |
---|
4939 | model.messagesPointer()->setDetailMessage(3,1); |
---|
4940 | model.messagesPointer()->setDetailMessage(3,3007); |
---|
4941 | } |
---|
4942 | double cutoff = getCutoff(); |
---|
4943 | model.setCutoff(cutoff); |
---|
4944 | // integer presolve |
---|
4945 | CbcModel * model2 = model.integerPresolve(false); |
---|
4946 | if (!model2||!model2->getNumRows()) { |
---|
4947 | delete model2; |
---|
4948 | delete solver; |
---|
4949 | return 2; |
---|
4950 | } |
---|
4951 | if (handler_->logLevel()>1) |
---|
4952 | printf("Reduced model has %d rows and %d columns\n", |
---|
4953 | model2->getNumRows(),model2->getNumCols()); |
---|
4954 | // Do complete search |
---|
4955 | |
---|
4956 | // Cuts |
---|
4957 | for ( i = 0;i<numberCutGenerators_;i++) { |
---|
4958 | int howOften = generator_[i]->howOftenInSub(); |
---|
4959 | if (howOften>-100) { |
---|
4960 | CbcCutGenerator * generator = virginGenerator_[i]; |
---|
4961 | CglCutGenerator * cglGenerator = generator->generator(); |
---|
4962 | model2->addCutGenerator(cglGenerator,howOften, |
---|
4963 | generator->cutGeneratorName(), |
---|
4964 | generator->normal(), |
---|
4965 | generator->atSolution(), |
---|
4966 | generator->whenInfeasible(), |
---|
4967 | -100, generator->whatDepthInSub(),-1); |
---|
4968 | } |
---|
4969 | } |
---|
4970 | for (i=0;i<numberHeuristics_;i++) { |
---|
4971 | model2->addHeuristic(heuristic_[i]); |
---|
4972 | model2->heuristic(i)->resetModel(model2); |
---|
4973 | } |
---|
4974 | // Definition of node choice |
---|
4975 | model2->setNodeComparison(nodeCompare_->clone()); |
---|
4976 | //model2->solver()->setHintParam(OsiDoReducePrint,true,OsiHintTry); |
---|
4977 | model2->messageHandler()->setLogLevel(CoinMax(0,handler_->logLevel()-1)); |
---|
4978 | //model2->solver()->messageHandler()->setLogLevel(2); |
---|
4979 | model2->setMaximumCutPassesAtRoot(maximumCutPassesAtRoot_); |
---|
4980 | model2->setPrintFrequency(50); |
---|
4981 | model2->setIntParam(CbcModel::CbcMaxNumNode,maximumNodes); |
---|
4982 | model2->branchAndBound(); |
---|
4983 | delete model2->nodeComparison(); |
---|
4984 | if (model2->getMinimizationObjValue()>cutoff) { |
---|
4985 | // no good |
---|
4986 | delete model2; |
---|
4987 | delete solver; |
---|
4988 | return 2; |
---|
4989 | } |
---|
4990 | // get back solution |
---|
4991 | model.originalModel(model2,false); |
---|
4992 | delete model2; |
---|
4993 | int status; |
---|
4994 | if (model.getMinimizationObjValue()<cutoff&&model.bestSolution()) { |
---|
4995 | double objValue = model.getObjValue(); |
---|
4996 | const double * solution = model.bestSolution(); |
---|
4997 | setBestSolution(CBC_TREE_SOL,objValue,solution); |
---|
4998 | status = 0; |
---|
4999 | } else { |
---|
5000 | status=2; |
---|
5001 | } |
---|
5002 | if (model.status()) |
---|
5003 | status ++ ; // not finished search |
---|
5004 | delete solver; |
---|
5005 | return status; |
---|
5006 | } |
---|
5007 | // Set a pointer to a row cut which will be added instead of normal branching. |
---|
5008 | void |
---|
5009 | CbcModel::setNextRowCut(const OsiRowCut & cut) |
---|
5010 | { |
---|
5011 | nextRowCut_=new OsiRowCut(cut); |
---|
5012 | } |
---|
5013 | /* Process root node and return a strengthened model |
---|
5014 | |
---|
5015 | The method assumes that initialSolve() has been called to solve the |
---|
5016 | LP relaxation. It processes the root node and then returns a pointer |
---|
5017 | to the strengthened model (or NULL if infeasible) |
---|
5018 | */ |
---|
5019 | OsiSolverInterface * |
---|
5020 | CbcModel::strengthenedModel() |
---|
5021 | { |
---|
5022 | /* |
---|
5023 | Assume we're done, and see if we're proven wrong. |
---|
5024 | */ |
---|
5025 | /* |
---|
5026 | Scan the variables, noting the integer variables. Create an |
---|
5027 | CbcSimpleInteger object for each integer variable. |
---|
5028 | */ |
---|
5029 | findIntegers(false) ; |
---|
5030 | /* |
---|
5031 | Ensure that objects on the lists of CbcObjects, heuristics, and cut |
---|
5032 | generators attached to this model all refer to this model. |
---|
5033 | */ |
---|
5034 | synchronizeModel() ; |
---|
5035 | |
---|
5036 | // Set so we can tell we are in initial phase in resolve |
---|
5037 | continuousObjective_ = -COIN_DBL_MAX ; |
---|
5038 | /* |
---|
5039 | Solve the relaxation. |
---|
5040 | |
---|
5041 | Apparently there are circumstances where this will be non-trivial --- i.e., |
---|
5042 | we've done something since initialSolve that's trashed the solution to the |
---|
5043 | continuous relaxation. |
---|
5044 | */ |
---|
5045 | bool feasible = resolve() ; |
---|
5046 | /* |
---|
5047 | If the linear relaxation of the root is infeasible, bail out now. Otherwise, |
---|
5048 | continue with processing the root node. |
---|
5049 | */ |
---|
5050 | if (!feasible) |
---|
5051 | { handler_->message(CBC_INFEAS,messages_)<< CoinMessageEol ; |
---|
5052 | return NULL; } |
---|
5053 | // Save objective (just so user can access it) |
---|
5054 | originalContinuousObjective_ = solver_->getObjValue(); |
---|
5055 | |
---|
5056 | /* |
---|
5057 | Begin setup to process a feasible root node. |
---|
5058 | */ |
---|
5059 | bestObjective_ = CoinMin(bestObjective_,1.0e50) ; |
---|
5060 | numberSolutions_ = 0 ; |
---|
5061 | numberHeuristicSolutions_ = 0 ; |
---|
5062 | // Everything is minimization |
---|
5063 | double cutoff=getCutoff() ; |
---|
5064 | double direction = solver_->getObjSense() ; |
---|
5065 | if (cutoff < 1.0e20&&direction<0.0) |
---|
5066 | messageHandler()->message(CBC_CUTOFF_WARNING1, |
---|
5067 | messages()) |
---|
5068 | << cutoff << -cutoff << CoinMessageEol ; |
---|
5069 | if (cutoff > bestObjective_) |
---|
5070 | cutoff = bestObjective_ ; |
---|
5071 | setCutoff(cutoff) ; |
---|
5072 | /* |
---|
5073 | We probably already have a current solution, but just in case ... |
---|
5074 | */ |
---|
5075 | int numberColumns = getNumCols() ; |
---|
5076 | if (!currentSolution_) |
---|
5077 | currentSolution_ = new double[numberColumns] ; |
---|
5078 | /* |
---|
5079 | Create a copy of the solver, thus capturing the original (root node) |
---|
5080 | constraint system (aka the continuous system). |
---|
5081 | */ |
---|
5082 | continuousSolver_ = solver_->clone() ; |
---|
5083 | numberRowsAtContinuous_ = getNumRows() ; |
---|
5084 | /* |
---|
5085 | Check the objective to see if we can deduce a nontrivial increment. If |
---|
5086 | it's better than the current value for CbcCutoffIncrement, it'll be |
---|
5087 | installed. |
---|
5088 | */ |
---|
5089 | analyzeObjective() ; |
---|
5090 | /* |
---|
5091 | Set up for cut generation. addedCuts_ holds the cuts which are relevant for |
---|
5092 | the active subproblem. whichGenerator will be used to record the generator |
---|
5093 | that produced a given cut. |
---|
5094 | */ |
---|
5095 | int maximumWhich = 1000 ; |
---|
5096 | int * whichGenerator = new int[maximumWhich] ; |
---|
5097 | maximumNumberCuts_ = 0 ; |
---|
5098 | currentNumberCuts_ = 0 ; |
---|
5099 | delete [] addedCuts_ ; |
---|
5100 | addedCuts_ = NULL ; |
---|
5101 | /* |
---|
5102 | Generate cuts at the root node and reoptimise. solveWithCuts does the heavy |
---|
5103 | lifting. It will iterate a generate/reoptimise loop (including reduced cost |
---|
5104 | fixing) until no cuts are generated, the change in objective falls off, or |
---|
5105 | the limit on the number of rounds of cut generation is exceeded. |
---|
5106 | |
---|
5107 | At the end of all this, any cuts will be recorded in cuts and also |
---|
5108 | installed in the solver's constraint system. We'll have reoptimised, and |
---|
5109 | removed any slack cuts (numberOldActiveCuts and numberNewCuts have been |
---|
5110 | adjusted accordingly). |
---|
5111 | |
---|
5112 | Tell cut generators they can be a bit more aggressive at root node |
---|
5113 | |
---|
5114 | */ |
---|
5115 | int iCutGenerator; |
---|
5116 | for (iCutGenerator = 0;iCutGenerator<numberCutGenerators_;iCutGenerator++) { |
---|
5117 | CglCutGenerator * generator = generator_[iCutGenerator]->generator(); |
---|
5118 | generator->setAggressiveness(generator->getAggressiveness()+100); |
---|
5119 | } |
---|
5120 | OsiCuts cuts ; |
---|
5121 | int numberOldActiveCuts = 0 ; |
---|
5122 | int numberNewCuts = 0 ; |
---|
5123 | { int iObject ; |
---|
5124 | int preferredWay ; |
---|
5125 | int numberUnsatisfied = 0 ; |
---|
5126 | double integerTolerance = getIntegerTolerance() ; |
---|
5127 | |
---|
5128 | memcpy(currentSolution_,solver_->getColSolution(), |
---|
5129 | numberColumns*sizeof(double)) ; |
---|
5130 | |
---|
5131 | for (iObject = 0 ; iObject < numberObjects_ ; iObject++) |
---|
5132 | { double infeasibility = |
---|
5133 | object_[iObject]->infeasibility(preferredWay) ; |
---|
5134 | if (infeasibility > integerTolerance) numberUnsatisfied++ ; } |
---|
5135 | if (numberUnsatisfied) |
---|
5136 | { feasible = solveWithCuts(cuts,maximumCutPassesAtRoot_, |
---|
5137 | NULL,numberOldActiveCuts,numberNewCuts, |
---|
5138 | maximumWhich, whichGenerator) ; } } |
---|
5139 | /* |
---|
5140 | We've taken the continuous relaxation as far as we can. |
---|
5141 | */ |
---|
5142 | |
---|
5143 | OsiSolverInterface * newSolver=NULL; |
---|
5144 | if (feasible) { |
---|
5145 | // make copy of current solver |
---|
5146 | newSolver = solver_->clone(); |
---|
5147 | } |
---|
5148 | /* |
---|
5149 | Clean up dangling objects. continuousSolver_ may already be toast. |
---|
5150 | */ |
---|
5151 | delete [] whichGenerator ; |
---|
5152 | delete [] walkback_ ; |
---|
5153 | walkback_ = NULL ; |
---|
5154 | delete [] addedCuts_ ; |
---|
5155 | addedCuts_ = NULL ; |
---|
5156 | if (continuousSolver_) |
---|
5157 | { delete continuousSolver_ ; |
---|
5158 | continuousSolver_ = NULL ; } |
---|
5159 | /* |
---|
5160 | Destroy global cuts by replacing with an empty OsiCuts object. |
---|
5161 | */ |
---|
5162 | globalCuts_= OsiCuts() ; |
---|
5163 | |
---|
5164 | return newSolver; |
---|
5165 | } |
---|
5166 | |
---|
5167 | |
---|