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 | |
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8 | #include "CbcConfig.h" |
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9 | |
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10 | #include <string> |
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11 | //#define CBC_DEBUG 1 |
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12 | //#define CHECK_CUT_COUNTS |
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13 | //#define CHECK_NODE |
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14 | //#define CBC_CHECK_BASIS |
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15 | #define CBC_WEAK_STRONG |
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16 | #include <cassert> |
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17 | #include <cfloat> |
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18 | #define CUTS |
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19 | #include "OsiSolverInterface.hpp" |
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20 | #include "OsiChooseVariable.hpp" |
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21 | #include "OsiAuxInfo.hpp" |
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22 | #include "OsiSolverBranch.hpp" |
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23 | #include "CoinWarmStartBasis.hpp" |
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24 | #include "CoinTime.hpp" |
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25 | #include "CbcModel.hpp" |
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26 | #include "CbcNode.hpp" |
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27 | #include "CbcStatistics.hpp" |
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28 | #include "CbcStrategy.hpp" |
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29 | #include "CbcBranchActual.hpp" |
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30 | #include "CbcBranchDynamic.hpp" |
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31 | #include "OsiRowCut.hpp" |
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32 | #include "OsiRowCutDebugger.hpp" |
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33 | #include "OsiCuts.hpp" |
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34 | #include "CbcCountRowCut.hpp" |
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35 | #include "CbcFeasibilityBase.hpp" |
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36 | #include "CbcMessage.hpp" |
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37 | #ifdef COIN_HAS_CLP |
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38 | #include "OsiClpSolverInterface.hpp" |
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39 | #include "ClpSimplexOther.hpp" |
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40 | #endif |
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41 | using namespace std; |
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42 | #include "CglCutGenerator.hpp" |
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43 | // Default Constructor |
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44 | CbcNodeInfo::CbcNodeInfo () |
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45 | : |
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46 | numberPointingToThis_(0), |
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47 | parent_(NULL), |
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48 | owner_(NULL), |
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49 | numberCuts_(0), |
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50 | nodeNumber_(0), |
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51 | cuts_(NULL), |
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52 | numberRows_(0), |
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53 | numberBranchesLeft_(0) |
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54 | { |
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55 | #ifdef CHECK_NODE |
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56 | printf("CbcNodeInfo %x Constructor\n",this); |
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57 | #endif |
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58 | } |
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59 | // Constructor given parent |
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60 | CbcNodeInfo::CbcNodeInfo (CbcNodeInfo * parent) |
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61 | : |
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62 | numberPointingToThis_(2), |
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63 | parent_(parent), |
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64 | owner_(NULL), |
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65 | numberCuts_(0), |
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66 | nodeNumber_(0), |
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67 | cuts_(NULL), |
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68 | numberRows_(0), |
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69 | numberBranchesLeft_(2) |
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70 | { |
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71 | #ifdef CHECK_NODE |
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72 | printf("CbcNodeInfo %x Constructor from parent %x\n",this,parent_); |
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73 | #endif |
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74 | if (parent_) { |
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75 | numberRows_ = parent_->numberRows_+parent_->numberCuts_; |
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76 | //parent_->increment(); |
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77 | } |
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78 | } |
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79 | // Copy Constructor |
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80 | CbcNodeInfo::CbcNodeInfo (const CbcNodeInfo & rhs) |
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81 | : |
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82 | numberPointingToThis_(rhs.numberPointingToThis_), |
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83 | parent_(rhs.parent_), |
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84 | owner_(rhs.owner_), |
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85 | numberCuts_(rhs.numberCuts_), |
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86 | nodeNumber_(rhs.nodeNumber_), |
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87 | cuts_(NULL), |
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88 | numberRows_(rhs.numberRows_), |
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89 | numberBranchesLeft_(rhs.numberBranchesLeft_) |
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90 | { |
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91 | #ifdef CHECK_NODE |
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92 | printf("CbcNodeInfo %x Copy constructor\n",this); |
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93 | #endif |
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94 | if (numberCuts_) { |
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95 | cuts_ = new CbcCountRowCut * [numberCuts_]; |
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96 | int n=0; |
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97 | for (int i=0;i<numberCuts_;i++) { |
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98 | CbcCountRowCut * thisCut = rhs.cuts_[i]; |
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99 | if (thisCut) { |
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100 | // I think this is correct - new one should take priority |
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101 | thisCut->setInfo(this,n); |
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102 | thisCut->increment(numberBranchesLeft_); |
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103 | cuts_[n++] = thisCut; |
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104 | } |
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105 | } |
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106 | numberCuts_=n; |
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107 | } |
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108 | } |
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109 | // Constructor given parent and owner |
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110 | CbcNodeInfo::CbcNodeInfo (CbcNodeInfo * parent, CbcNode * owner) |
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111 | : |
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112 | numberPointingToThis_(2), |
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113 | parent_(parent), |
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114 | owner_(owner), |
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115 | numberCuts_(0), |
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116 | nodeNumber_(0), |
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117 | cuts_(NULL), |
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118 | numberRows_(0), |
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119 | numberBranchesLeft_(2) |
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120 | { |
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121 | #ifdef CHECK_NODE |
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122 | printf("CbcNodeInfo %x Constructor from parent %x\n",this,parent_); |
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123 | #endif |
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124 | if (parent_) { |
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125 | numberRows_ = parent_->numberRows_+parent_->numberCuts_; |
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126 | } |
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127 | } |
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128 | |
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129 | /** |
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130 | Take care to detach from the owning CbcNode and decrement the reference |
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131 | count in the parent. If this is the last nodeInfo object pointing to the |
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132 | parent, make a recursive call to delete the parent. |
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133 | */ |
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134 | CbcNodeInfo::~CbcNodeInfo() |
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135 | { |
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136 | #ifdef CHECK_NODE |
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137 | printf("CbcNodeInfo %x Destructor parent %x\n",this,parent_); |
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138 | #endif |
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139 | |
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140 | assert(!numberPointingToThis_); |
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141 | // But they may be some left (max nodes?) |
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142 | for (int i=0;i<numberCuts_;i++) { |
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143 | #ifndef GLOBAL_CUTS_JUST_POINTERS |
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144 | delete cuts_[i]; |
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145 | #else |
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146 | if (cuts_[i]->globallyValidAsInteger()!=2) |
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147 | delete cuts_[i]; |
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148 | #endif |
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149 | } |
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150 | delete [] cuts_; |
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151 | if (owner_) |
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152 | owner_->nullNodeInfo(); |
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153 | if (parent_) { |
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154 | int numberLinks = parent_->decrement(); |
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155 | if (!numberLinks) delete parent_; |
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156 | } |
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157 | } |
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158 | |
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159 | |
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160 | //#define ALLCUTS |
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161 | void |
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162 | CbcNodeInfo::decrementCuts(int change) |
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163 | { |
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164 | int i; |
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165 | // get rid of all remaining if negative |
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166 | int changeThis; |
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167 | if (change<0) |
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168 | changeThis = numberBranchesLeft_; |
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169 | else |
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170 | changeThis = change; |
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171 | // decrement cut counts |
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172 | for (i=0;i<numberCuts_;i++) { |
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173 | if (cuts_[i]) { |
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174 | int number = cuts_[i]->decrement(changeThis); |
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175 | if (!number) { |
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176 | //printf("info %x del cut %d %x\n",this,i,cuts_[i]); |
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177 | #ifndef GLOBAL_CUTS_JUST_POINTERS |
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178 | delete cuts_[i]; |
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179 | #else |
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180 | if (cuts_[i]->globallyValidAsInteger()!=2) |
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181 | delete cuts_[i]; |
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182 | #endif |
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183 | cuts_[i]=NULL; |
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184 | } |
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185 | } |
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186 | } |
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187 | } |
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188 | void |
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189 | CbcNodeInfo::decrementParentCuts(int change) |
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190 | { |
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191 | if (parent_) { |
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192 | // get rid of all remaining if negative |
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193 | int changeThis; |
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194 | if (change<0) |
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195 | changeThis = numberBranchesLeft_; |
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196 | else |
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197 | changeThis = change; |
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198 | int i; |
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199 | // Get over-estimate of space needed for basis |
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200 | CoinWarmStartBasis dummy; |
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201 | dummy.setSize(0,numberRows_+numberCuts_); |
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202 | buildRowBasis(dummy); |
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203 | /* everything is zero (i.e. free) so we can use to see |
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204 | if latest basis */ |
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205 | CbcNodeInfo * thisInfo = parent_; |
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206 | while (thisInfo) |
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207 | thisInfo = thisInfo->buildRowBasis(dummy); |
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208 | // decrement cut counts |
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209 | thisInfo = parent_; |
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210 | int numberRows=numberRows_; |
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211 | while (thisInfo) { |
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212 | for (i=thisInfo->numberCuts_-1;i>=0;i--) { |
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213 | CoinWarmStartBasis::Status status = dummy.getArtifStatus(--numberRows); |
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214 | #ifdef ALLCUTS |
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215 | status = CoinWarmStartBasis::isFree; |
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216 | #endif |
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217 | if (thisInfo->cuts_[i]) { |
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218 | int number=1; |
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219 | if (status!=CoinWarmStartBasis::basic) { |
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220 | // tight - drop 1 or 2 |
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221 | if (change<0) |
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222 | number = thisInfo->cuts_[i]->decrement(changeThis); |
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223 | else |
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224 | number = thisInfo->cuts_[i]->decrement(change); |
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225 | } |
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226 | if (!number) { |
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227 | #ifndef GLOBAL_CUTS_JUST_POINTERS |
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228 | delete thisInfo->cuts_[i]; |
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229 | #else |
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230 | if (thisInfo->cuts_[i]->globallyValidAsInteger()!=2) |
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231 | delete thisInfo->cuts_[i]; |
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232 | #endif |
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233 | thisInfo->cuts_[i]=NULL; |
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234 | } |
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235 | } |
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236 | } |
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237 | thisInfo = thisInfo->parent_; |
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238 | } |
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239 | } |
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240 | } |
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241 | |
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242 | void |
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243 | CbcNodeInfo::incrementParentCuts(int change) |
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244 | { |
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245 | if (parent_) { |
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246 | int i; |
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247 | // Get over-estimate of space needed for basis |
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248 | CoinWarmStartBasis dummy; |
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249 | dummy.setSize(0,numberRows_+numberCuts_); |
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250 | /* everything is zero (i.e. free) so we can use to see |
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251 | if latest basis */ |
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252 | buildRowBasis(dummy); |
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253 | CbcNodeInfo * thisInfo = parent_; |
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254 | while (thisInfo) |
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255 | thisInfo = thisInfo->buildRowBasis(dummy); |
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256 | // increment cut counts |
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257 | thisInfo = parent_; |
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258 | int numberRows=numberRows_; |
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259 | while (thisInfo) { |
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260 | for (i=thisInfo->numberCuts_-1;i>=0;i--) { |
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261 | CoinWarmStartBasis::Status status = dummy.getArtifStatus(--numberRows); |
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262 | #ifdef ALLCUTS |
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263 | status = CoinWarmStartBasis::isFree; |
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264 | #endif |
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265 | if (thisInfo->cuts_[i]&&status!=CoinWarmStartBasis::basic) { |
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266 | thisInfo->cuts_[i]->increment(change); |
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267 | } |
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268 | } |
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269 | thisInfo = thisInfo->parent_; |
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270 | } |
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271 | } |
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272 | } |
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273 | |
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274 | /* |
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275 | Append cuts to the cuts_ array in a nodeInfo. The initial reference count |
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276 | is set to numberToBranchOn, which will normally be the number of arms |
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277 | defined for the CbcBranchingObject attached to the CbcNode that owns this |
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278 | CbcNodeInfo. |
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279 | */ |
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280 | void |
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281 | CbcNodeInfo::addCuts (OsiCuts & cuts, int numberToBranchOn, |
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282 | int * whichGenerator) |
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283 | { |
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284 | int numberCuts = cuts.sizeRowCuts(); |
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285 | if (numberCuts) { |
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286 | int i; |
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287 | if (!numberCuts_) { |
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288 | cuts_ = new CbcCountRowCut * [numberCuts]; |
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289 | } else { |
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290 | CbcCountRowCut ** temp = new CbcCountRowCut * [numberCuts+numberCuts_]; |
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291 | memcpy(temp,cuts_,numberCuts_*sizeof(CbcCountRowCut *)); |
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292 | delete [] cuts_; |
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293 | cuts_ = temp; |
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294 | } |
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295 | for (i=0;i<numberCuts;i++) { |
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296 | CbcCountRowCut * thisCut = new CbcCountRowCut(*cuts.rowCutPtr(i), |
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297 | this,numberCuts_); |
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298 | thisCut->increment(numberToBranchOn); |
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299 | cuts_[numberCuts_++] = thisCut; |
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300 | #ifdef CBC_DEBUG |
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301 | #if CBC_DEBUG>1 |
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302 | int n=thisCut->row().getNumElements(); |
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303 | printf("Cut %d has %d entries, rhs %g %g =>",i,n,thisCut->lb(), |
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304 | thisCut->ub()); |
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305 | int j; |
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306 | const int * index = thisCut->row().getIndices(); |
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307 | const double * element = thisCut->row().getElements(); |
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308 | for (j=0;j<n;j++) { |
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309 | printf(" (%d,%g)",index[j],element[j]); |
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310 | assert(fabs(element[j])>1.00e-12); |
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311 | } |
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312 | printf("\n"); |
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313 | #else |
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314 | int n=thisCut->row().getNumElements(); |
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315 | int j; |
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316 | const double * element = thisCut->row().getElements(); |
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317 | for (j=0;j<n;j++) { |
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318 | assert(fabs(element[j])>1.00e-12); |
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319 | } |
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320 | #endif |
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321 | #endif |
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322 | } |
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323 | } |
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324 | } |
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325 | |
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326 | void |
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327 | CbcNodeInfo::addCuts(int numberCuts, CbcCountRowCut ** cut, |
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328 | int numberToBranchOn) |
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329 | { |
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330 | if (numberCuts) { |
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331 | int i; |
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332 | if (!numberCuts_) { |
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333 | cuts_ = new CbcCountRowCut * [numberCuts]; |
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334 | } else { |
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335 | CbcCountRowCut ** temp = new CbcCountRowCut * [numberCuts+numberCuts_]; |
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336 | memcpy(temp,cuts_,numberCuts_*sizeof(CbcCountRowCut *)); |
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337 | delete [] cuts_; |
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338 | cuts_ = temp; |
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339 | } |
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340 | for (i=0;i<numberCuts;i++) { |
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341 | CbcCountRowCut * thisCut = cut[i]; |
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342 | thisCut->setInfo(this,numberCuts_); |
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343 | //printf("info %x cut %d %x\n",this,i,thisCut); |
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344 | thisCut->increment(numberToBranchOn); |
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345 | cuts_[numberCuts_++] = thisCut; |
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346 | #ifdef CBC_DEBUG |
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347 | int n=thisCut->row().getNumElements(); |
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348 | #if CBC_DEBUG>1 |
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349 | printf("Cut %d has %d entries, rhs %g %g =>",i,n,thisCut->lb(), |
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350 | thisCut->ub()); |
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351 | #endif |
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352 | int j; |
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353 | #if CBC_DEBUG>1 |
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354 | const int * index = thisCut->row().getIndices(); |
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355 | #endif |
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356 | const double * element = thisCut->row().getElements(); |
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357 | for (j=0;j<n;j++) { |
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358 | #if CBC_DEBUG>1 |
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359 | printf(" (%d,%g)",index[j],element[j]); |
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360 | #endif |
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361 | assert(fabs(element[j])>1.00e-12); |
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362 | } |
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363 | printf("\n"); |
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364 | #endif |
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365 | } |
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366 | } |
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367 | } |
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368 | |
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369 | // delete cuts |
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370 | void |
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371 | CbcNodeInfo::deleteCuts(int numberToDelete, CbcCountRowCut ** cuts) |
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372 | { |
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373 | int i; |
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374 | int j; |
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375 | int last=-1; |
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376 | for (i=0;i<numberToDelete;i++) { |
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377 | CbcCountRowCut * next = cuts[i]; |
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378 | for (j=last+1;j<numberCuts_;j++) { |
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379 | if (next==cuts_[j]) |
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380 | break; |
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381 | } |
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382 | if (j==numberCuts_) { |
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383 | // start from beginning |
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384 | for (j=0;j<last;j++) { |
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385 | if (next==cuts_[j]) |
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386 | break; |
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387 | } |
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388 | assert(j<last); |
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389 | } |
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390 | last=j; |
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391 | int number = cuts_[j]->decrement(); |
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392 | if (!number) { |
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393 | #ifndef GLOBAL_CUTS_JUST_POINTERS |
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394 | delete cuts_[j]; |
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395 | #else |
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396 | if (cuts_[j]->globallyValidAsInteger()!=2) |
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397 | delete cuts_[j]; |
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398 | #endif |
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399 | } |
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400 | cuts_[j]=NULL; |
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401 | } |
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402 | j=0; |
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403 | for (i=0;i<numberCuts_;i++) { |
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404 | if (cuts_[i]) |
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405 | cuts_[j++]=cuts_[i]; |
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406 | } |
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407 | numberCuts_ = j; |
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408 | } |
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409 | |
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410 | // delete cuts |
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411 | void |
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412 | CbcNodeInfo::deleteCuts(int numberToDelete, int * which) |
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413 | { |
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414 | int i; |
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415 | for (i=0;i<numberToDelete;i++) { |
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416 | int iCut=which[i]; |
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417 | int number = cuts_[iCut]->decrement(); |
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418 | if (!number) { |
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419 | #ifndef GLOBAL_CUTS_JUST_POINTERS |
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420 | delete cuts_[iCut]; |
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421 | #else |
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422 | if (cuts_[iCut]->globallyValidAsInteger()!=2) |
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423 | delete cuts_[iCut]; |
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424 | #endif |
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425 | } |
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426 | cuts_[iCut]=NULL; |
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427 | } |
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428 | int j=0; |
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429 | for (i=0;i<numberCuts_;i++) { |
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430 | if (cuts_[i]) |
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431 | cuts_[j++]=cuts_[i]; |
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432 | } |
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433 | numberCuts_ = j; |
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434 | } |
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435 | |
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436 | // Really delete a cut |
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437 | void |
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438 | CbcNodeInfo::deleteCut(int whichOne) |
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439 | { |
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440 | assert(whichOne<numberCuts_); |
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441 | cuts_[whichOne]=NULL; |
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442 | } |
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443 | |
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444 | CbcFullNodeInfo::CbcFullNodeInfo() : |
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445 | CbcNodeInfo(), |
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446 | basis_(), |
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447 | numberIntegers_(0), |
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448 | lower_(NULL), |
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449 | upper_(NULL) |
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450 | { |
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451 | } |
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452 | CbcFullNodeInfo::CbcFullNodeInfo(CbcModel * model, |
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453 | int numberRowsAtContinuous) : |
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454 | CbcNodeInfo() |
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455 | { |
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456 | OsiSolverInterface * solver = model->solver(); |
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457 | numberRows_ = numberRowsAtContinuous; |
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458 | numberIntegers_ = model->numberIntegers(); |
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459 | int numberColumns = model->getNumCols(); |
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460 | lower_ = new double [numberColumns]; |
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461 | upper_ = new double [numberColumns]; |
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462 | const double * lower = solver->getColLower(); |
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463 | const double * upper = solver->getColUpper(); |
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464 | int i; |
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465 | |
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466 | for (i=0;i<numberColumns;i++) { |
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467 | lower_[i]=lower[i]; |
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468 | upper_[i]=upper[i]; |
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469 | } |
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470 | |
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471 | basis_ = dynamic_cast<CoinWarmStartBasis*>(solver->getWarmStart()); |
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472 | } |
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473 | |
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474 | CbcFullNodeInfo::CbcFullNodeInfo(const CbcFullNodeInfo & rhs) : |
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475 | CbcNodeInfo(rhs) |
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476 | { |
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477 | basis_= dynamic_cast<CoinWarmStartBasis *>(rhs.basis_->clone()) ; |
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478 | numberIntegers_=rhs.numberIntegers_; |
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479 | lower_=NULL; |
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480 | upper_=NULL; |
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481 | if (rhs.lower_!=NULL) { |
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482 | int numberColumns = basis_->getNumStructural(); |
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483 | lower_ = new double [numberColumns]; |
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484 | upper_ = new double [numberColumns]; |
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485 | assert (upper_!=NULL); |
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486 | memcpy(lower_,rhs.lower_,numberColumns*sizeof(double)); |
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487 | memcpy(upper_,rhs.upper_,numberColumns*sizeof(double)); |
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488 | } |
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489 | } |
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490 | |
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491 | CbcNodeInfo * |
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492 | CbcFullNodeInfo::clone() const |
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493 | { |
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494 | return (new CbcFullNodeInfo(*this)); |
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495 | } |
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496 | |
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497 | CbcFullNodeInfo::~CbcFullNodeInfo () |
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498 | { |
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499 | delete basis_ ; |
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500 | delete [] lower_; |
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501 | delete [] upper_; |
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502 | } |
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503 | |
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504 | /* |
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505 | The basis supplied as a parameter is deleted and replaced with a new basis |
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506 | appropriate for the node, and lower and upper bounds on variables are |
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507 | reset according to the stored bounds arrays. Any cuts associated with this |
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508 | node are added to the list in addCuts, but not actually added to the |
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509 | constraint system in the model. |
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510 | |
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511 | Why pass in a basis at all? The short answer is ``We need the parameter to |
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512 | pass out a basis, so might as well use it to pass in the size.'' |
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513 | |
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514 | A longer answer is that in practice we take a memory allocation hit up in |
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515 | addCuts1 (the only place applyToModel is called) when we setSize() the |
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516 | basis that's passed in. It's immediately tossed here in favour of a clone |
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517 | of the basis attached to this nodeInfo. This can probably be fixed, given |
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518 | a bit of thought. |
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519 | */ |
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520 | |
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521 | void CbcFullNodeInfo::applyToModel (CbcModel *model, |
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522 | CoinWarmStartBasis *&basis, |
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523 | CbcCountRowCut **addCuts, |
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524 | int ¤tNumberCuts) const |
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525 | |
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526 | { OsiSolverInterface *solver = model->solver() ; |
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527 | |
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528 | // branch - do bounds |
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529 | int i; |
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530 | solver->setColLower(lower_); |
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531 | solver->setColUpper(upper_); |
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532 | int numberColumns = model->getNumCols(); |
---|
533 | // move basis - but make sure size stays |
---|
534 | // for bon-min - should not be needed int numberRows = model->getNumRows(); |
---|
535 | int numberRows=basis->getNumArtificial(); |
---|
536 | delete basis ; |
---|
537 | if (basis_) { |
---|
538 | basis = dynamic_cast<CoinWarmStartBasis *>(basis_->clone()) ; |
---|
539 | basis->resize(numberRows,numberColumns); |
---|
540 | } else { |
---|
541 | // We have a solver without a basis |
---|
542 | basis=NULL; |
---|
543 | } |
---|
544 | for (i=0;i<numberCuts_;i++) |
---|
545 | addCuts[currentNumberCuts+i]= cuts_[i]; |
---|
546 | currentNumberCuts += numberCuts_; |
---|
547 | assert(!parent_); |
---|
548 | return ; |
---|
549 | } |
---|
550 | |
---|
551 | /* Builds up row basis backwards (until original model). |
---|
552 | Returns NULL or previous one to apply . |
---|
553 | Depends on Free being 0 and impossible for cuts |
---|
554 | */ |
---|
555 | CbcNodeInfo * |
---|
556 | CbcFullNodeInfo::buildRowBasis(CoinWarmStartBasis & basis ) const |
---|
557 | { |
---|
558 | const unsigned int * saved = |
---|
559 | (const unsigned int *) basis_->getArtificialStatus(); |
---|
560 | unsigned int * now = |
---|
561 | (unsigned int *) basis.getArtificialStatus(); |
---|
562 | int number=basis_->getNumArtificial()>>4;; |
---|
563 | int i; |
---|
564 | for (i=0;i<number;i++) { |
---|
565 | if (!now[i]) |
---|
566 | now[i] = saved[i]; |
---|
567 | } |
---|
568 | return NULL; |
---|
569 | } |
---|
570 | |
---|
571 | // Default constructor |
---|
572 | CbcPartialNodeInfo::CbcPartialNodeInfo() |
---|
573 | |
---|
574 | : CbcNodeInfo(), |
---|
575 | basisDiff_(NULL), |
---|
576 | variables_(NULL), |
---|
577 | newBounds_(NULL), |
---|
578 | numberChangedBounds_(0) |
---|
579 | |
---|
580 | { /* this space intentionally left blank */ } |
---|
581 | |
---|
582 | // Constructor from current state |
---|
583 | CbcPartialNodeInfo::CbcPartialNodeInfo (CbcNodeInfo *parent, CbcNode *owner, |
---|
584 | int numberChangedBounds, |
---|
585 | const int *variables, |
---|
586 | const double *boundChanges, |
---|
587 | const CoinWarmStartDiff *basisDiff) |
---|
588 | : CbcNodeInfo(parent,owner) |
---|
589 | { |
---|
590 | basisDiff_ = basisDiff->clone() ; |
---|
591 | |
---|
592 | numberChangedBounds_ = numberChangedBounds; |
---|
593 | variables_ = new int [numberChangedBounds_]; |
---|
594 | newBounds_ = new double [numberChangedBounds_]; |
---|
595 | |
---|
596 | int i ; |
---|
597 | for (i=0;i<numberChangedBounds_;i++) { |
---|
598 | variables_[i]=variables[i]; |
---|
599 | newBounds_[i]=boundChanges[i]; |
---|
600 | } |
---|
601 | } |
---|
602 | |
---|
603 | CbcPartialNodeInfo::CbcPartialNodeInfo (const CbcPartialNodeInfo & rhs) |
---|
604 | |
---|
605 | : CbcNodeInfo(rhs.parent_) |
---|
606 | |
---|
607 | { basisDiff_ = rhs.basisDiff_->clone() ; |
---|
608 | |
---|
609 | numberChangedBounds_ = rhs.numberChangedBounds_; |
---|
610 | variables_ = new int [numberChangedBounds_]; |
---|
611 | newBounds_ = new double [numberChangedBounds_]; |
---|
612 | |
---|
613 | int i ; |
---|
614 | for (i=0;i<numberChangedBounds_;i++) { |
---|
615 | variables_[i]=rhs.variables_[i]; |
---|
616 | newBounds_[i]=rhs.newBounds_[i]; |
---|
617 | } |
---|
618 | } |
---|
619 | |
---|
620 | CbcNodeInfo * |
---|
621 | CbcPartialNodeInfo::clone() const |
---|
622 | { |
---|
623 | return (new CbcPartialNodeInfo(*this)); |
---|
624 | } |
---|
625 | |
---|
626 | |
---|
627 | CbcPartialNodeInfo::~CbcPartialNodeInfo () |
---|
628 | { |
---|
629 | delete basisDiff_ ; |
---|
630 | delete [] variables_; |
---|
631 | delete [] newBounds_; |
---|
632 | } |
---|
633 | |
---|
634 | |
---|
635 | /** |
---|
636 | The basis supplied as a parameter is incrementally modified, and lower and |
---|
637 | upper bounds on variables in the model are incrementally modified. Any |
---|
638 | cuts associated with this node are added to the list in addCuts. |
---|
639 | */ |
---|
640 | |
---|
641 | void CbcPartialNodeInfo::applyToModel (CbcModel *model, |
---|
642 | CoinWarmStartBasis *&basis, |
---|
643 | CbcCountRowCut **addCuts, |
---|
644 | int ¤tNumberCuts) const |
---|
645 | |
---|
646 | { OsiSolverInterface *solver = model->solver(); |
---|
647 | basis->applyDiff(basisDiff_) ; |
---|
648 | |
---|
649 | // branch - do bounds |
---|
650 | int i; |
---|
651 | for (i=0;i<numberChangedBounds_;i++) { |
---|
652 | int variable = variables_[i]; |
---|
653 | int k = variable&0x7fffffff; |
---|
654 | if ((variable&0x80000000)==0) { |
---|
655 | // lower bound changing |
---|
656 | #ifndef NDEBUG |
---|
657 | double oldValue = solver->getColLower()[k]; |
---|
658 | assert (newBounds_[i]>oldValue-1.0e-8); |
---|
659 | if (newBounds_[i]<oldValue+1.0e-8) |
---|
660 | printf("bad null lower change for column %d - bound %g\n",k,oldValue); |
---|
661 | #endif |
---|
662 | solver->setColLower(k,newBounds_[i]); |
---|
663 | } else { |
---|
664 | // upper bound changing |
---|
665 | #ifndef NDEBUG |
---|
666 | double oldValue = solver->getColUpper()[k]; |
---|
667 | assert (newBounds_[i]<oldValue+1.0e-8); |
---|
668 | if (newBounds_[i]>oldValue-1.0e-8) |
---|
669 | printf("bad null upper change for column %d - bound %g\n",k,oldValue); |
---|
670 | #endif |
---|
671 | solver->setColUpper(k,newBounds_[i]); |
---|
672 | } |
---|
673 | } |
---|
674 | for (i=0;i<numberCuts_;i++) { |
---|
675 | addCuts[currentNumberCuts+i]= cuts_[i]; |
---|
676 | if (cuts_[i]&&model->messageHandler()->logLevel()>4) { |
---|
677 | cuts_[i]->print(); |
---|
678 | } |
---|
679 | } |
---|
680 | |
---|
681 | currentNumberCuts += numberCuts_; |
---|
682 | return ; |
---|
683 | } |
---|
684 | |
---|
685 | /* Builds up row basis backwards (until original model). |
---|
686 | Returns NULL or previous one to apply . |
---|
687 | Depends on Free being 0 and impossible for cuts |
---|
688 | */ |
---|
689 | |
---|
690 | CbcNodeInfo * |
---|
691 | CbcPartialNodeInfo::buildRowBasis(CoinWarmStartBasis & basis ) const |
---|
692 | |
---|
693 | { basis.applyDiff(basisDiff_) ; |
---|
694 | |
---|
695 | return parent_ ; } |
---|
696 | |
---|
697 | |
---|
698 | CbcNode::CbcNode() : |
---|
699 | nodeInfo_(NULL), |
---|
700 | objectiveValue_(1.0e100), |
---|
701 | guessedObjectiveValue_(1.0e100), |
---|
702 | sumInfeasibilities_(0.0), |
---|
703 | branch_(NULL), |
---|
704 | depth_(-1), |
---|
705 | numberUnsatisfied_(0) |
---|
706 | { |
---|
707 | #ifdef CHECK_NODE |
---|
708 | printf("CbcNode %x Constructor\n",this); |
---|
709 | #endif |
---|
710 | } |
---|
711 | |
---|
712 | CbcNode::CbcNode(CbcModel * model, |
---|
713 | CbcNode * lastNode) : |
---|
714 | nodeInfo_(NULL), |
---|
715 | objectiveValue_(1.0e100), |
---|
716 | guessedObjectiveValue_(1.0e100), |
---|
717 | sumInfeasibilities_(0.0), |
---|
718 | branch_(NULL), |
---|
719 | depth_(-1), |
---|
720 | numberUnsatisfied_(0) |
---|
721 | { |
---|
722 | #ifdef CHECK_NODE |
---|
723 | printf("CbcNode %x Constructor from model\n",this); |
---|
724 | #endif |
---|
725 | model->setObjectiveValue(this,lastNode); |
---|
726 | |
---|
727 | if (lastNode) |
---|
728 | if (lastNode->nodeInfo_) |
---|
729 | lastNode->nodeInfo_->increment(); |
---|
730 | } |
---|
731 | |
---|
732 | #define CBC_NEW_CREATEINFO |
---|
733 | #ifdef CBC_NEW_CREATEINFO |
---|
734 | |
---|
735 | /* |
---|
736 | New createInfo, with basis manipulation hidden inside mergeBasis. Allows |
---|
737 | solvers to override and carry over all information from one basis to |
---|
738 | another. |
---|
739 | */ |
---|
740 | |
---|
741 | void |
---|
742 | CbcNode::createInfo (CbcModel *model, |
---|
743 | CbcNode *lastNode, |
---|
744 | const CoinWarmStartBasis *lastws, |
---|
745 | const double *lastLower, const double *lastUpper, |
---|
746 | int numberOldActiveCuts, int numberNewCuts) |
---|
747 | |
---|
748 | { OsiSolverInterface *solver = model->solver(); |
---|
749 | CbcStrategy *strategy = model->strategy(); |
---|
750 | /* |
---|
751 | The root --- no parent. Create full basis and bounds information. |
---|
752 | */ |
---|
753 | if (!lastNode) |
---|
754 | { |
---|
755 | if (!strategy) |
---|
756 | nodeInfo_=new CbcFullNodeInfo(model,solver->getNumRows()); |
---|
757 | else |
---|
758 | nodeInfo_ = strategy->fullNodeInfo(model,solver->getNumRows()); |
---|
759 | } else { |
---|
760 | /* |
---|
761 | Not the root. Create an edit from the parent's basis & bound information. |
---|
762 | This is not quite as straightforward as it seems. We need to reintroduce |
---|
763 | cuts we may have dropped out of the basis, in the correct position, because |
---|
764 | this whole process is strictly positional. Start by grabbing the current |
---|
765 | basis. |
---|
766 | */ |
---|
767 | const CoinWarmStartBasis *ws = |
---|
768 | dynamic_cast<const CoinWarmStartBasis*>(solver->getWarmStart()); |
---|
769 | assert(ws!=NULL); // make sure not volume |
---|
770 | //int numberArtificials = lastws->getNumArtificial(); |
---|
771 | int numberColumns = solver->getNumCols(); |
---|
772 | int numberRowsAtContinuous = model->numberRowsAtContinuous(); |
---|
773 | int currentNumberCuts = model->currentNumberCuts(); |
---|
774 | # ifdef CBC_CHECK_BASIS |
---|
775 | std::cout |
---|
776 | << "Before expansion: orig " << numberRowsAtContinuous |
---|
777 | << ", old " << numberOldActiveCuts |
---|
778 | << ", new " << numberNewCuts |
---|
779 | << ", current " << currentNumberCuts << "." << std::endl ; |
---|
780 | ws->print(); |
---|
781 | # endif |
---|
782 | /* |
---|
783 | Clone the basis and resize it to hold the structural constraints, plus |
---|
784 | all the cuts: old cuts, both active and inactive (currentNumberCuts), |
---|
785 | and new cuts (numberNewCuts). This will become the expanded basis. |
---|
786 | */ |
---|
787 | CoinWarmStartBasis *expanded = |
---|
788 | dynamic_cast<CoinWarmStartBasis *>(ws->clone()) ; |
---|
789 | int iCompact = numberRowsAtContinuous+numberOldActiveCuts+numberNewCuts ; |
---|
790 | // int nPartial = numberRowsAtContinuous+currentNumberCuts; |
---|
791 | int iFull = numberRowsAtContinuous+currentNumberCuts+numberNewCuts; |
---|
792 | // int maxBasisLength = ((iFull+15)>>4)+((numberColumns+15)>>4); |
---|
793 | // printf("l %d full %d\n",maxBasisLength,iFull); |
---|
794 | expanded->resize(iFull,numberColumns); |
---|
795 | # ifdef CBC_CHECK_BASIS |
---|
796 | std::cout |
---|
797 | << "\tFull basis " << iFull << " rows, " |
---|
798 | << numberColumns << " columns; compact " |
---|
799 | << iCompact << " rows." << std::endl ; |
---|
800 | # endif |
---|
801 | /* |
---|
802 | Now flesh out the expanded basis. The clone already has the |
---|
803 | correct status information for the variables and for the structural |
---|
804 | (numberRowsAtContinuous) constraints. Any indices beyond nPartial must be |
---|
805 | cuts created while processing this node --- they can be copied en bloc |
---|
806 | into the correct position in the expanded basis. The space reserved for |
---|
807 | xferRows is a gross overestimate. |
---|
808 | */ |
---|
809 | CoinWarmStartBasis::XferVec xferRows ; |
---|
810 | xferRows.reserve(iFull-numberRowsAtContinuous+1) ; |
---|
811 | if (numberNewCuts) { |
---|
812 | xferRows.push_back( |
---|
813 | CoinWarmStartBasis::XferEntry(iCompact-numberNewCuts, |
---|
814 | iFull-numberNewCuts,numberNewCuts)) ; |
---|
815 | } |
---|
816 | /* |
---|
817 | From nPartial down, record the entries we want to copy from the current |
---|
818 | basis (the entries for the active cuts; non-zero in the list returned |
---|
819 | by addedCuts). Fill the expanded basis with entries showing a status of |
---|
820 | basic for the deactivated (loose) cuts. |
---|
821 | */ |
---|
822 | CbcCountRowCut **cut = model->addedCuts(); |
---|
823 | iFull -= (numberNewCuts+1) ; |
---|
824 | iCompact -= (numberNewCuts+1) ; |
---|
825 | int runLen = 0 ; |
---|
826 | CoinWarmStartBasis::XferEntry entry(-1,-1,-1) ; |
---|
827 | while (iFull >= numberRowsAtContinuous) { |
---|
828 | for ( ; iFull >= numberRowsAtContinuous && |
---|
829 | cut[iFull-numberRowsAtContinuous] ; iFull--) |
---|
830 | runLen++ ; |
---|
831 | if (runLen) { |
---|
832 | iCompact -= runLen ; |
---|
833 | entry.first = iCompact+1 ; |
---|
834 | entry.second = iFull+1 ; |
---|
835 | entry.third = runLen ; |
---|
836 | runLen = 0 ; |
---|
837 | xferRows.push_back(entry) ; |
---|
838 | } |
---|
839 | for ( ; iFull >= numberRowsAtContinuous && |
---|
840 | !cut[iFull-numberRowsAtContinuous] ; iFull--) |
---|
841 | expanded->setArtifStatus(iFull,CoinWarmStartBasis::basic); |
---|
842 | } |
---|
843 | /* |
---|
844 | Finally, call mergeBasis to copy over entries from the current basis to |
---|
845 | the expanded basis. Since we cloned the expanded basis from the active basis |
---|
846 | and haven't changed the number of variables, only row status entries need |
---|
847 | to be copied. |
---|
848 | */ |
---|
849 | expanded->mergeBasis(ws,&xferRows,0) ; |
---|
850 | |
---|
851 | #ifdef CBC_CHECK_BASIS |
---|
852 | std::cout << "Expanded basis:" << std::endl ; |
---|
853 | expanded->print() ; |
---|
854 | std::cout << "Diffing against:" << std::endl ; |
---|
855 | lastws->print() ; |
---|
856 | #endif |
---|
857 | |
---|
858 | /* |
---|
859 | Now that we have two bases in proper positional correspondence, creating |
---|
860 | the actual diff is dead easy. |
---|
861 | |
---|
862 | Note that we're going to compare the expanded basis here to the stripped |
---|
863 | basis (lastws) produced by addCuts. It doesn't affect the correctness (the |
---|
864 | diff process has no knowledge of the meaning of an entry) but it does |
---|
865 | mean that we'll always generate a whack of diff entries because the expanded |
---|
866 | basis is considerably larger than the stripped basis. |
---|
867 | */ |
---|
868 | CoinWarmStartDiff *basisDiff = expanded->generateDiff(lastws) ; |
---|
869 | /* |
---|
870 | Diff the bound vectors. It's assumed the number of structural variables |
---|
871 | is not changing. For branching objects that change bounds on integer |
---|
872 | variables, we should see at least one bound change as a consequence |
---|
873 | of applying the branch that generated this subproblem from its parent. |
---|
874 | This need not hold for other types of branching objects (hyperplane |
---|
875 | branches, for example). |
---|
876 | */ |
---|
877 | const double * lower = solver->getColLower(); |
---|
878 | const double * upper = solver->getColUpper(); |
---|
879 | |
---|
880 | double *boundChanges = new double [2*numberColumns] ; |
---|
881 | int *variables = new int [2*numberColumns] ; |
---|
882 | int numberChangedBounds=0; |
---|
883 | |
---|
884 | int i; |
---|
885 | for (i=0;i<numberColumns;i++) { |
---|
886 | if (lower[i]!=lastLower[i]) { |
---|
887 | variables[numberChangedBounds]=i; |
---|
888 | boundChanges[numberChangedBounds++]=lower[i]; |
---|
889 | } |
---|
890 | if (upper[i]!=lastUpper[i]) { |
---|
891 | variables[numberChangedBounds]=i|0x80000000; |
---|
892 | boundChanges[numberChangedBounds++]=upper[i]; |
---|
893 | } |
---|
894 | #ifdef CBC_DEBUG |
---|
895 | if (lower[i] != lastLower[i]) { |
---|
896 | std::cout |
---|
897 | << "lower on " << i << " changed from " |
---|
898 | << lastLower[i] << " to " << lower[i] << std::endl ; |
---|
899 | } |
---|
900 | if (upper[i] != lastUpper[i]) { |
---|
901 | std::cout |
---|
902 | << "upper on " << i << " changed from " |
---|
903 | << lastUpper[i] << " to " << upper[i] << std::endl ; |
---|
904 | } |
---|
905 | #endif |
---|
906 | } |
---|
907 | #ifdef CBC_DEBUG |
---|
908 | std::cout << numberChangedBounds << " changed bounds." << std::endl ; |
---|
909 | #endif |
---|
910 | //if (lastNode->branchingObject()->boundBranch()) |
---|
911 | //assert (numberChangedBounds); |
---|
912 | /* |
---|
913 | Hand the lot over to the CbcPartialNodeInfo constructor, then clean up and |
---|
914 | return. |
---|
915 | */ |
---|
916 | if (!strategy) |
---|
917 | nodeInfo_ = |
---|
918 | new CbcPartialNodeInfo(lastNode->nodeInfo_,this,numberChangedBounds, |
---|
919 | variables,boundChanges,basisDiff) ; |
---|
920 | else |
---|
921 | nodeInfo_ = |
---|
922 | strategy->partialNodeInfo(model,lastNode->nodeInfo_,this, |
---|
923 | numberChangedBounds,variables,boundChanges, |
---|
924 | basisDiff) ; |
---|
925 | delete basisDiff ; |
---|
926 | delete [] boundChanges; |
---|
927 | delete [] variables; |
---|
928 | delete expanded ; |
---|
929 | delete ws; |
---|
930 | } |
---|
931 | // Set node number |
---|
932 | nodeInfo_->setNodeNumber(model->getNodeCount2()); |
---|
933 | } |
---|
934 | |
---|
935 | #else // CBC_NEW_CREATEINFO |
---|
936 | |
---|
937 | /* |
---|
938 | Original createInfo, with bare manipulation of basis vectors. Fails if solver |
---|
939 | maintains additional information in basis. |
---|
940 | */ |
---|
941 | |
---|
942 | void |
---|
943 | CbcNode::createInfo (CbcModel *model, |
---|
944 | CbcNode *lastNode, |
---|
945 | const CoinWarmStartBasis *lastws, |
---|
946 | const double *lastLower, const double *lastUpper, |
---|
947 | int numberOldActiveCuts,int numberNewCuts) |
---|
948 | { OsiSolverInterface * solver = model->solver(); |
---|
949 | CbcStrategy * strategy = model->strategy(); |
---|
950 | /* |
---|
951 | The root --- no parent. Create full basis and bounds information. |
---|
952 | */ |
---|
953 | if (!lastNode) |
---|
954 | { |
---|
955 | if (!strategy) |
---|
956 | nodeInfo_=new CbcFullNodeInfo(model,solver->getNumRows()); |
---|
957 | else |
---|
958 | nodeInfo_ = strategy->fullNodeInfo(model,solver->getNumRows()); |
---|
959 | } |
---|
960 | /* |
---|
961 | Not the root. Create an edit from the parent's basis & bound information. |
---|
962 | This is not quite as straightforward as it seems. We need to reintroduce |
---|
963 | cuts we may have dropped out of the basis, in the correct position, because |
---|
964 | this whole process is strictly positional. Start by grabbing the current |
---|
965 | basis. |
---|
966 | */ |
---|
967 | else |
---|
968 | { const CoinWarmStartBasis* ws = |
---|
969 | dynamic_cast<const CoinWarmStartBasis*>(solver->getWarmStart()); |
---|
970 | assert(ws!=NULL); // make sure not volume |
---|
971 | //int numberArtificials = lastws->getNumArtificial(); |
---|
972 | int numberColumns = solver->getNumCols(); |
---|
973 | |
---|
974 | const double * lower = solver->getColLower(); |
---|
975 | const double * upper = solver->getColUpper(); |
---|
976 | |
---|
977 | int i; |
---|
978 | /* |
---|
979 | Create a clone and resize it to hold all the structural constraints, plus |
---|
980 | all the cuts: old cuts, both active and inactive (currentNumberCuts), and |
---|
981 | new cuts (numberNewCuts). |
---|
982 | |
---|
983 | TODO: You'd think that the set of constraints (logicals) in the expanded |
---|
984 | basis should match the set represented in lastws. At least, that's |
---|
985 | what I thought. But at the point I first looked hard at this bit of |
---|
986 | code, it turned out that lastws was the stripped basis produced at |
---|
987 | the end of addCuts(), rather than the raw basis handed back by |
---|
988 | addCuts1(). The expanded basis here is equivalent to the raw basis of |
---|
989 | addCuts1(). I said ``whoa, that's not good, I must have introduced a |
---|
990 | bug'' and went back to John's code to see where I'd gone wrong. |
---|
991 | And discovered the same `error' in his code. |
---|
992 | |
---|
993 | After a bit of thought, my conclusion is that correctness is not |
---|
994 | affected by whether lastws is the stripped or raw basis. The diffs |
---|
995 | have no semantics --- just a set of changes that need to be made |
---|
996 | to convert lastws into expanded. I think the only effect is that we |
---|
997 | store a lot more diffs (everything in expanded that's not covered by |
---|
998 | the stripped basis). But I need to give this more thought. There |
---|
999 | may well be some subtle error cases. |
---|
1000 | |
---|
1001 | In the mean time, I've twiddled addCuts() to set lastws to the raw |
---|
1002 | basis. Makes me (Lou) less nervous to compare apples to apples. |
---|
1003 | */ |
---|
1004 | CoinWarmStartBasis *expanded = |
---|
1005 | dynamic_cast<CoinWarmStartBasis *>(ws->clone()) ; |
---|
1006 | int numberRowsAtContinuous = model->numberRowsAtContinuous(); |
---|
1007 | int iFull = numberRowsAtContinuous+model->currentNumberCuts()+ |
---|
1008 | numberNewCuts; |
---|
1009 | //int numberArtificialsNow = iFull; |
---|
1010 | //int maxBasisLength = ((iFull+15)>>4)+((numberColumns+15)>>4); |
---|
1011 | //printf("l %d full %d\n",maxBasisLength,iFull); |
---|
1012 | if (expanded) |
---|
1013 | expanded->resize(iFull,numberColumns); |
---|
1014 | #ifdef CBC_CHECK_BASIS |
---|
1015 | printf("Before expansion: orig %d, old %d, new %d, current %d\n", |
---|
1016 | numberRowsAtContinuous,numberOldActiveCuts,numberNewCuts, |
---|
1017 | model->currentNumberCuts()) ; |
---|
1018 | ws->print(); |
---|
1019 | #endif |
---|
1020 | /* |
---|
1021 | Now fill in the expanded basis. Any indices beyond nPartial must |
---|
1022 | be cuts created while processing this node --- they can be copied directly |
---|
1023 | into the expanded basis. From nPartial down, pull the status of active cuts |
---|
1024 | from ws, interleaving with a B entry for the deactivated (loose) cuts. |
---|
1025 | */ |
---|
1026 | int numberDropped = model->currentNumberCuts()-numberOldActiveCuts; |
---|
1027 | int iCompact=iFull-numberDropped; |
---|
1028 | CbcCountRowCut ** cut = model->addedCuts(); |
---|
1029 | int nPartial = model->currentNumberCuts()+numberRowsAtContinuous; |
---|
1030 | iFull--; |
---|
1031 | for (;iFull>=nPartial;iFull--) { |
---|
1032 | CoinWarmStartBasis::Status status = ws->getArtifStatus(--iCompact); |
---|
1033 | //assert (status != CoinWarmStartBasis::basic); // may be permanent cut |
---|
1034 | expanded->setArtifStatus(iFull,status); |
---|
1035 | } |
---|
1036 | for (;iFull>=numberRowsAtContinuous;iFull--) { |
---|
1037 | if (cut[iFull-numberRowsAtContinuous]) { |
---|
1038 | CoinWarmStartBasis::Status status = ws->getArtifStatus(--iCompact); |
---|
1039 | // If no cut generator being used then we may have basic variables |
---|
1040 | //if (model->getMaximumCutPasses()&& |
---|
1041 | // status == CoinWarmStartBasis::basic) |
---|
1042 | //printf("cut basic\n"); |
---|
1043 | expanded->setArtifStatus(iFull,status); |
---|
1044 | } else { |
---|
1045 | expanded->setArtifStatus(iFull,CoinWarmStartBasis::basic); |
---|
1046 | } |
---|
1047 | } |
---|
1048 | #ifdef CBC_CHECK_BASIS |
---|
1049 | printf("Expanded basis\n"); |
---|
1050 | expanded->print() ; |
---|
1051 | printf("Diffing against\n") ; |
---|
1052 | lastws->print() ; |
---|
1053 | #endif |
---|
1054 | /* |
---|
1055 | Now that we have two bases in proper positional correspondence, creating |
---|
1056 | the actual diff is dead easy. |
---|
1057 | */ |
---|
1058 | |
---|
1059 | CoinWarmStartDiff *basisDiff = expanded->generateDiff(lastws) ; |
---|
1060 | /* |
---|
1061 | Diff the bound vectors. It's assumed the number of structural variables is |
---|
1062 | not changing. Assuming that branching objects all involve integer variables, |
---|
1063 | we should see at least one bound change as a consequence of processing this |
---|
1064 | subproblem. Different types of branching objects could break this assertion. |
---|
1065 | Not true at all - we have not applied current branch - JJF. |
---|
1066 | */ |
---|
1067 | double *boundChanges = new double [2*numberColumns] ; |
---|
1068 | int *variables = new int [2*numberColumns] ; |
---|
1069 | int numberChangedBounds=0; |
---|
1070 | for (i=0;i<numberColumns;i++) { |
---|
1071 | if (lower[i]!=lastLower[i]) { |
---|
1072 | variables[numberChangedBounds]=i; |
---|
1073 | boundChanges[numberChangedBounds++]=lower[i]; |
---|
1074 | } |
---|
1075 | if (upper[i]!=lastUpper[i]) { |
---|
1076 | variables[numberChangedBounds]=i|0x80000000; |
---|
1077 | boundChanges[numberChangedBounds++]=upper[i]; |
---|
1078 | } |
---|
1079 | #ifdef CBC_DEBUG |
---|
1080 | if (lower[i]!=lastLower[i]) |
---|
1081 | printf("lower on %d changed from %g to %g\n", |
---|
1082 | i,lastLower[i],lower[i]); |
---|
1083 | if (upper[i]!=lastUpper[i]) |
---|
1084 | printf("upper on %d changed from %g to %g\n", |
---|
1085 | i,lastUpper[i],upper[i]); |
---|
1086 | #endif |
---|
1087 | } |
---|
1088 | #ifdef CBC_DEBUG |
---|
1089 | printf("%d changed bounds\n",numberChangedBounds) ; |
---|
1090 | #endif |
---|
1091 | //if (lastNode->branchingObject()->boundBranch()) |
---|
1092 | //assert (numberChangedBounds); |
---|
1093 | /* |
---|
1094 | Hand the lot over to the CbcPartialNodeInfo constructor, then clean up and |
---|
1095 | return. |
---|
1096 | */ |
---|
1097 | if (!strategy) |
---|
1098 | nodeInfo_ = |
---|
1099 | new CbcPartialNodeInfo(lastNode->nodeInfo_,this,numberChangedBounds, |
---|
1100 | variables,boundChanges,basisDiff) ; |
---|
1101 | else |
---|
1102 | nodeInfo_ = strategy->partialNodeInfo(model, lastNode->nodeInfo_,this,numberChangedBounds, |
---|
1103 | variables,boundChanges,basisDiff) ; |
---|
1104 | delete basisDiff ; |
---|
1105 | delete [] boundChanges; |
---|
1106 | delete [] variables; |
---|
1107 | delete expanded ; |
---|
1108 | delete ws; |
---|
1109 | } |
---|
1110 | // Set node number |
---|
1111 | nodeInfo_->setNodeNumber(model->getNodeCount2()); |
---|
1112 | } |
---|
1113 | |
---|
1114 | #endif // CBC_NEW_CREATEINFO |
---|
1115 | |
---|
1116 | /* |
---|
1117 | The routine scans through the object list of the model looking for objects |
---|
1118 | that indicate infeasibility. It tests each object using strong branching |
---|
1119 | and selects the one with the least objective degradation. A corresponding |
---|
1120 | branching object is left attached to lastNode. |
---|
1121 | |
---|
1122 | If strong branching is disabled, a candidate object is chosen essentially |
---|
1123 | at random (whatever object ends up in pos'n 0 of the candidate array). |
---|
1124 | |
---|
1125 | If a branching candidate is found to be monotone, bounds are set to fix the |
---|
1126 | variable and the routine immediately returns (the caller is expected to |
---|
1127 | reoptimize). |
---|
1128 | |
---|
1129 | If a branching candidate is found to result in infeasibility in both |
---|
1130 | directions, the routine immediately returns an indication of infeasibility. |
---|
1131 | |
---|
1132 | Returns: 0 both branch directions are feasible |
---|
1133 | -1 branching variable is monotone |
---|
1134 | -2 infeasible |
---|
1135 | |
---|
1136 | Original comments: |
---|
1137 | Here could go cuts etc etc |
---|
1138 | For now just fix on objective from strong branching. |
---|
1139 | */ |
---|
1140 | |
---|
1141 | int CbcNode::chooseBranch (CbcModel *model, CbcNode *lastNode,int numberPassesLeft) |
---|
1142 | |
---|
1143 | { if (lastNode) |
---|
1144 | depth_ = lastNode->depth_+1; |
---|
1145 | else |
---|
1146 | depth_ = 0; |
---|
1147 | delete branch_; |
---|
1148 | branch_=NULL; |
---|
1149 | OsiSolverInterface * solver = model->solver(); |
---|
1150 | double saveObjectiveValue = solver->getObjValue(); |
---|
1151 | double objectiveValue = CoinMax(solver->getObjSense()*saveObjectiveValue,objectiveValue_); |
---|
1152 | const double * lower = solver->getColLower(); |
---|
1153 | const double * upper = solver->getColUpper(); |
---|
1154 | // See what user thinks |
---|
1155 | int anyAction=model->problemFeasibility()->feasible(model,0); |
---|
1156 | if (anyAction) { |
---|
1157 | // will return -2 if infeasible , 0 if treat as integer |
---|
1158 | return anyAction-1; |
---|
1159 | } |
---|
1160 | double integerTolerance = |
---|
1161 | model->getDblParam(CbcModel::CbcIntegerTolerance); |
---|
1162 | // point to useful information |
---|
1163 | OsiBranchingInformation usefulInfo = model->usefulInformation(); |
---|
1164 | // and modify |
---|
1165 | usefulInfo.depth_=depth_; |
---|
1166 | int i; |
---|
1167 | bool beforeSolution = model->getSolutionCount()==0; |
---|
1168 | int numberStrong=model->numberStrong(); |
---|
1169 | // switch off strong if hotstart |
---|
1170 | if (model->hotstartSolution()) |
---|
1171 | numberStrong=0; |
---|
1172 | int numberStrongDone=0; |
---|
1173 | int numberUnfinished=0; |
---|
1174 | int numberStrongInfeasible=0; |
---|
1175 | int numberStrongIterations=0; |
---|
1176 | int saveNumberStrong=numberStrong; |
---|
1177 | int numberObjects = model->numberObjects(); |
---|
1178 | bool checkFeasibility = numberObjects>model->numberIntegers(); |
---|
1179 | int maximumStrong = CoinMax(CoinMin(model->numberStrong(),numberObjects),1); |
---|
1180 | int numberColumns = model->getNumCols(); |
---|
1181 | double * saveUpper = new double[numberColumns]; |
---|
1182 | double * saveLower = new double[numberColumns]; |
---|
1183 | |
---|
1184 | // Save solution in case heuristics need good solution later |
---|
1185 | |
---|
1186 | double * saveSolution = new double[numberColumns]; |
---|
1187 | memcpy(saveSolution,solver->getColSolution(),numberColumns*sizeof(double)); |
---|
1188 | model->reserveCurrentSolution(saveSolution); |
---|
1189 | /* |
---|
1190 | Get a branching decision object. Use the default decision criteria unless |
---|
1191 | the user has loaded a decision method into the model. |
---|
1192 | */ |
---|
1193 | CbcBranchDecision *decision = model->branchingMethod(); |
---|
1194 | CbcDynamicPseudoCostBranchingObject * dynamicBranchingObject = |
---|
1195 | dynamic_cast<CbcDynamicPseudoCostBranchingObject *>(decision); |
---|
1196 | if (!decision||dynamicBranchingObject) |
---|
1197 | decision = new CbcBranchDefaultDecision(); |
---|
1198 | decision->initialize(model); |
---|
1199 | CbcStrongInfo * choice = new CbcStrongInfo[maximumStrong]; |
---|
1200 | for (i=0;i<numberColumns;i++) { |
---|
1201 | saveLower[i] = lower[i]; |
---|
1202 | saveUpper[i] = upper[i]; |
---|
1203 | } |
---|
1204 | // May go round twice if strong branching fixes all local candidates |
---|
1205 | bool finished=false; |
---|
1206 | double estimatedDegradation=0.0; |
---|
1207 | while(!finished) { |
---|
1208 | finished=true; |
---|
1209 | // Some objects may compute an estimate of best solution from here |
---|
1210 | estimatedDegradation=0.0; |
---|
1211 | //int numberIntegerInfeasibilities=0; // without odd ones |
---|
1212 | numberStrongDone=0; |
---|
1213 | numberUnfinished=0; |
---|
1214 | numberStrongInfeasible=0; |
---|
1215 | numberStrongIterations=0; |
---|
1216 | |
---|
1217 | // We may go round this loop twice (only if we think we have solution) |
---|
1218 | for (int iPass=0;iPass<2;iPass++) { |
---|
1219 | |
---|
1220 | // compute current state |
---|
1221 | //int numberObjectInfeasibilities; // just odd ones |
---|
1222 | //model->feasibleSolution( |
---|
1223 | // numberIntegerInfeasibilities, |
---|
1224 | // numberObjectInfeasibilities); |
---|
1225 | const double * hotstartSolution = model->hotstartSolution(); |
---|
1226 | const int * hotstartPriorities = model->hotstartPriorities(); |
---|
1227 | |
---|
1228 | // Some objects may compute an estimate of best solution from here |
---|
1229 | estimatedDegradation=0.0; |
---|
1230 | numberUnsatisfied_ = 0; |
---|
1231 | // initialize sum of "infeasibilities" |
---|
1232 | sumInfeasibilities_ = 0.0; |
---|
1233 | int bestPriority=COIN_INT_MAX; |
---|
1234 | /* |
---|
1235 | Scan for branching objects that indicate infeasibility. Choose the best |
---|
1236 | maximumStrong candidates, using priority as the first criteria, then |
---|
1237 | integer infeasibility. |
---|
1238 | |
---|
1239 | The algorithm is to fill the choice array with a set of good candidates (by |
---|
1240 | infeasibility) with priority bestPriority. Finding a candidate with |
---|
1241 | priority better (less) than bestPriority flushes the choice array. (This |
---|
1242 | serves as initialization when the first candidate is found.) |
---|
1243 | |
---|
1244 | A new candidate is added to choices only if its infeasibility exceeds the |
---|
1245 | current max infeasibility (mostAway). When a candidate is added, it |
---|
1246 | replaces the candidate with the smallest infeasibility (tracked by |
---|
1247 | iSmallest). |
---|
1248 | */ |
---|
1249 | int iSmallest = 0; |
---|
1250 | double mostAway = 1.0e-100; |
---|
1251 | for (i = 0 ; i < maximumStrong ; i++) |
---|
1252 | choice[i].possibleBranch = NULL ; |
---|
1253 | numberStrong=0; |
---|
1254 | bool canDoOneHot=false; |
---|
1255 | for (i=0;i<numberObjects;i++) { |
---|
1256 | OsiObject * object = model->modifiableObject(i); |
---|
1257 | int preferredWay; |
---|
1258 | double infeasibility = object->infeasibility(&usefulInfo,preferredWay); |
---|
1259 | int priorityLevel = object->priority(); |
---|
1260 | if (hotstartSolution) { |
---|
1261 | // we are doing hot start |
---|
1262 | const CbcSimpleInteger * thisOne = dynamic_cast <const CbcSimpleInteger *> (object); |
---|
1263 | if (thisOne) { |
---|
1264 | int iColumn = thisOne->columnNumber(); |
---|
1265 | bool canDoThisHot=true; |
---|
1266 | double targetValue = hotstartSolution[iColumn]; |
---|
1267 | if (saveUpper[iColumn]>saveLower[iColumn]) { |
---|
1268 | double value = saveSolution[iColumn]; |
---|
1269 | if (hotstartPriorities) |
---|
1270 | priorityLevel=hotstartPriorities[iColumn]; |
---|
1271 | //double originalLower = thisOne->originalLower(); |
---|
1272 | //double originalUpper = thisOne->originalUpper(); |
---|
1273 | // switch off if not possible |
---|
1274 | if (targetValue>=saveLower[iColumn]&&targetValue<=saveUpper[iColumn]) { |
---|
1275 | /* priority outranks rest always if negative |
---|
1276 | otherwise can be downgraded if at correct level. |
---|
1277 | Infeasibility may be increased to choose 1.0 values first. |
---|
1278 | choose one near wanted value |
---|
1279 | */ |
---|
1280 | if (fabs(value-targetValue)>integerTolerance) { |
---|
1281 | infeasibility = 1.0-fabs(value-targetValue); |
---|
1282 | if (targetValue==1.0) |
---|
1283 | infeasibility += 1.0; |
---|
1284 | if (value>targetValue) { |
---|
1285 | preferredWay=-1; |
---|
1286 | } else { |
---|
1287 | preferredWay=1; |
---|
1288 | } |
---|
1289 | priorityLevel = CoinAbs(priorityLevel); |
---|
1290 | } else if (priorityLevel<0) { |
---|
1291 | priorityLevel = CoinAbs(priorityLevel); |
---|
1292 | if (targetValue==saveLower[iColumn]) { |
---|
1293 | infeasibility = integerTolerance+1.0e-12; |
---|
1294 | preferredWay=-1; |
---|
1295 | } else if (targetValue==saveUpper[iColumn]) { |
---|
1296 | infeasibility = integerTolerance+1.0e-12; |
---|
1297 | preferredWay=1; |
---|
1298 | } else { |
---|
1299 | // can't |
---|
1300 | priorityLevel += 10000000; |
---|
1301 | canDoThisHot=false; |
---|
1302 | } |
---|
1303 | } else { |
---|
1304 | priorityLevel += 10000000; |
---|
1305 | canDoThisHot=false; |
---|
1306 | } |
---|
1307 | } else { |
---|
1308 | // switch off if not possible |
---|
1309 | canDoThisHot=false; |
---|
1310 | } |
---|
1311 | if (canDoThisHot) |
---|
1312 | canDoOneHot=true; |
---|
1313 | } else if (targetValue<saveLower[iColumn]||targetValue>saveUpper[iColumn]) { |
---|
1314 | } |
---|
1315 | } else { |
---|
1316 | priorityLevel += 10000000; |
---|
1317 | } |
---|
1318 | } |
---|
1319 | if (infeasibility) { |
---|
1320 | // Increase estimated degradation to solution |
---|
1321 | estimatedDegradation += CoinMin(object->upEstimate(),object->downEstimate()); |
---|
1322 | numberUnsatisfied_++; |
---|
1323 | sumInfeasibilities_ += infeasibility; |
---|
1324 | // Better priority? Flush choices. |
---|
1325 | if (priorityLevel<bestPriority) { |
---|
1326 | int j; |
---|
1327 | iSmallest=0; |
---|
1328 | for (j=0;j<maximumStrong;j++) { |
---|
1329 | choice[j].upMovement=0.0; |
---|
1330 | delete choice[j].possibleBranch; |
---|
1331 | choice[j].possibleBranch=NULL; |
---|
1332 | } |
---|
1333 | bestPriority = priorityLevel; |
---|
1334 | mostAway=1.0e-100; |
---|
1335 | numberStrong=0; |
---|
1336 | } else if (priorityLevel>bestPriority) { |
---|
1337 | continue; |
---|
1338 | } |
---|
1339 | // Check for suitability based on infeasibility. |
---|
1340 | if (infeasibility>mostAway) { |
---|
1341 | //add to list |
---|
1342 | choice[iSmallest].upMovement=infeasibility; |
---|
1343 | delete choice[iSmallest].possibleBranch; |
---|
1344 | CbcSimpleInteger * obj = |
---|
1345 | dynamic_cast <CbcSimpleInteger *>(object) ; |
---|
1346 | if (obj) { |
---|
1347 | choice[iSmallest].possibleBranch=obj->createBranch(solver,&usefulInfo,preferredWay); |
---|
1348 | } else { |
---|
1349 | CbcObject * obj = |
---|
1350 | dynamic_cast <CbcObject *>(object) ; |
---|
1351 | assert (obj); |
---|
1352 | choice[iSmallest].possibleBranch=obj->createBranch(preferredWay); |
---|
1353 | } |
---|
1354 | numberStrong = CoinMax(numberStrong,iSmallest+1); |
---|
1355 | // Save which object it was |
---|
1356 | choice[iSmallest].objectNumber=i; |
---|
1357 | int j; |
---|
1358 | iSmallest=-1; |
---|
1359 | mostAway = 1.0e50; |
---|
1360 | for (j=0;j<maximumStrong;j++) { |
---|
1361 | if (choice[j].upMovement<mostAway) { |
---|
1362 | mostAway=choice[j].upMovement; |
---|
1363 | iSmallest=j; |
---|
1364 | } |
---|
1365 | } |
---|
1366 | } |
---|
1367 | } |
---|
1368 | } |
---|
1369 | if (!canDoOneHot&&hotstartSolution) { |
---|
1370 | // switch off as not possible |
---|
1371 | hotstartSolution=NULL; |
---|
1372 | model->setHotstartSolution(NULL,NULL); |
---|
1373 | } |
---|
1374 | if (numberUnsatisfied_) { |
---|
1375 | // some infeasibilities - go to next steps |
---|
1376 | break; |
---|
1377 | } else if (!iPass) { |
---|
1378 | // looks like a solution - get paranoid |
---|
1379 | bool roundAgain=false; |
---|
1380 | // get basis |
---|
1381 | CoinWarmStartBasis * ws = dynamic_cast<CoinWarmStartBasis*>(solver->getWarmStart()); |
---|
1382 | if (!ws) |
---|
1383 | break; |
---|
1384 | for (i=0;i<numberColumns;i++) { |
---|
1385 | double value = saveSolution[i]; |
---|
1386 | if (value<lower[i]) { |
---|
1387 | saveSolution[i]=lower[i]; |
---|
1388 | roundAgain=true; |
---|
1389 | ws->setStructStatus(i,CoinWarmStartBasis::atLowerBound); |
---|
1390 | } else if (value>upper[i]) { |
---|
1391 | saveSolution[i]=upper[i]; |
---|
1392 | roundAgain=true; |
---|
1393 | ws->setStructStatus(i,CoinWarmStartBasis::atUpperBound); |
---|
1394 | } |
---|
1395 | } |
---|
1396 | if (roundAgain&&saveNumberStrong) { |
---|
1397 | // restore basis |
---|
1398 | solver->setWarmStart(ws); |
---|
1399 | delete ws; |
---|
1400 | solver->resolve(); |
---|
1401 | memcpy(saveSolution,solver->getColSolution(),numberColumns*sizeof(double)); |
---|
1402 | model->reserveCurrentSolution(saveSolution); |
---|
1403 | if (!solver->isProvenOptimal()) { |
---|
1404 | // infeasible |
---|
1405 | anyAction=-2; |
---|
1406 | break; |
---|
1407 | } |
---|
1408 | } else { |
---|
1409 | delete ws; |
---|
1410 | break; |
---|
1411 | } |
---|
1412 | } |
---|
1413 | } |
---|
1414 | /* Some solvers can do the strong branching calculations faster if |
---|
1415 | they do them all at once. At present only Clp does for ordinary |
---|
1416 | integers but I think this coding would be easy to modify |
---|
1417 | */ |
---|
1418 | bool allNormal=true; // to say if we can do fast strong branching |
---|
1419 | // Say which one will be best |
---|
1420 | int bestChoice=0; |
---|
1421 | double worstInfeasibility=0.0; |
---|
1422 | for (i=0;i<numberStrong;i++) { |
---|
1423 | choice[i].numIntInfeasUp = numberUnsatisfied_; |
---|
1424 | choice[i].numIntInfeasDown = numberUnsatisfied_; |
---|
1425 | choice[i].fix=0; // say not fixed |
---|
1426 | if (!dynamic_cast <const CbcSimpleInteger *> (model->object(choice[i].objectNumber))) |
---|
1427 | allNormal=false; // Something odd so lets skip clever fast branching |
---|
1428 | if ( !model->object(choice[i].objectNumber)->boundBranch()) |
---|
1429 | numberStrong=0; // switch off |
---|
1430 | if ( choice[i].possibleBranch->numberBranches()>2) |
---|
1431 | numberStrong=0; // switch off |
---|
1432 | // Do best choice in case switched off |
---|
1433 | if (choice[i].upMovement>worstInfeasibility) { |
---|
1434 | worstInfeasibility=choice[i].upMovement; |
---|
1435 | bestChoice=i; |
---|
1436 | } |
---|
1437 | } |
---|
1438 | // If we have hit max time don't do strong branching |
---|
1439 | bool hitMaxTime = ( CoinCpuTime()-model->getDblParam(CbcModel::CbcStartSeconds) > |
---|
1440 | model->getDblParam(CbcModel::CbcMaximumSeconds)); |
---|
1441 | // also give up if we are looping round too much |
---|
1442 | if (hitMaxTime||numberPassesLeft<=0) |
---|
1443 | numberStrong=0; |
---|
1444 | /* |
---|
1445 | Is strong branching enabled? If so, set up and do it. Otherwise, we'll |
---|
1446 | fall through to simple branching. |
---|
1447 | |
---|
1448 | Setup for strong branching involves saving the current basis (for restoration |
---|
1449 | afterwards) and setting up for hot starts. |
---|
1450 | */ |
---|
1451 | if (numberStrong&&saveNumberStrong) { |
---|
1452 | |
---|
1453 | bool solveAll=false; // set true to say look at all even if some fixed (experiment) |
---|
1454 | solveAll=true; |
---|
1455 | // worth trying if too many times |
---|
1456 | // Save basis |
---|
1457 | CoinWarmStart * ws = solver->getWarmStart(); |
---|
1458 | // save limit |
---|
1459 | int saveLimit; |
---|
1460 | solver->getIntParam(OsiMaxNumIterationHotStart,saveLimit); |
---|
1461 | if (beforeSolution&&saveLimit<100) |
---|
1462 | solver->setIntParam(OsiMaxNumIterationHotStart,100); // go to end |
---|
1463 | # ifdef COIN_HAS_CLP |
---|
1464 | /* If we are doing all strong branching in one go then we create new arrays |
---|
1465 | to store information. If clp NULL then doing old way. |
---|
1466 | Going down - |
---|
1467 | outputSolution[2*i] is final solution. |
---|
1468 | outputStuff[2*i] is status (0 - finished, 1 infeas, other unknown |
---|
1469 | outputStuff[2*i+numberStrong] is number iterations |
---|
1470 | On entry newUpper[i] is new upper bound, on exit obj change |
---|
1471 | Going up - |
---|
1472 | outputSolution[2*i+1] is final solution. |
---|
1473 | outputStuff[2*i+1] is status (0 - finished, 1 infeas, other unknown |
---|
1474 | outputStuff[2*i+1+numberStrong] is number iterations |
---|
1475 | On entry newLower[i] is new lower bound, on exit obj change |
---|
1476 | */ |
---|
1477 | OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (solver); |
---|
1478 | ClpSimplex * clp=NULL; |
---|
1479 | double * newLower = NULL; |
---|
1480 | double * newUpper = NULL; |
---|
1481 | double ** outputSolution=NULL; |
---|
1482 | int * outputStuff=NULL; |
---|
1483 | // Go back to normal way if user wants it |
---|
1484 | if (osiclp&&(osiclp->specialOptions()&16)!=0&&osiclp->specialOptions()>0) |
---|
1485 | allNormal=false; |
---|
1486 | if (osiclp&&!allNormal) { |
---|
1487 | // say do fast |
---|
1488 | int easy=1; |
---|
1489 | osiclp->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo,&easy) ; |
---|
1490 | } |
---|
1491 | if (osiclp&& allNormal) { |
---|
1492 | clp = osiclp->getModelPtr(); |
---|
1493 | // Clp - do a different way |
---|
1494 | newLower = new double[numberStrong]; |
---|
1495 | newUpper = new double[numberStrong]; |
---|
1496 | outputSolution = new double * [2*numberStrong]; |
---|
1497 | outputStuff = new int [4*numberStrong]; |
---|
1498 | int * which = new int[numberStrong]; |
---|
1499 | int startFinishOptions; |
---|
1500 | int specialOptions = osiclp->specialOptions(); |
---|
1501 | int clpOptions = clp->specialOptions(); |
---|
1502 | int returnCode=0; |
---|
1503 | #define CRUNCH |
---|
1504 | #ifdef CRUNCH |
---|
1505 | // Crunch down problem |
---|
1506 | int numberRows = clp->numberRows(); |
---|
1507 | // Use dual region |
---|
1508 | double * rhs = clp->dualRowSolution(); |
---|
1509 | int * whichRow = new int[3*numberRows]; |
---|
1510 | int * whichColumn = new int[2*numberColumns]; |
---|
1511 | int nBound; |
---|
1512 | ClpSimplex * small = ((ClpSimplexOther *) clp)->crunch(rhs,whichRow,whichColumn,nBound,true); |
---|
1513 | if (!small) { |
---|
1514 | anyAction=-2; |
---|
1515 | //printf("XXXX Inf by inspection\n"); |
---|
1516 | delete [] whichColumn; |
---|
1517 | whichColumn=NULL; |
---|
1518 | delete [] whichRow; |
---|
1519 | whichRow=NULL; |
---|
1520 | break; |
---|
1521 | } else { |
---|
1522 | clp = small; |
---|
1523 | } |
---|
1524 | #else |
---|
1525 | int saveLogLevel = clp->logLevel(); |
---|
1526 | int saveMaxIts = clp->maximumIterations(); |
---|
1527 | #endif |
---|
1528 | clp->setLogLevel(0); |
---|
1529 | if((specialOptions&1)==0) { |
---|
1530 | startFinishOptions=0; |
---|
1531 | clp->setSpecialOptions(clpOptions|(64|1024)); |
---|
1532 | } else { |
---|
1533 | startFinishOptions=1+2+4; |
---|
1534 | //startFinishOptions=1+4; // for moment re-factorize |
---|
1535 | if((specialOptions&4)==0) |
---|
1536 | clp->setSpecialOptions(clpOptions|(64|128|512|1024|4096)); |
---|
1537 | else |
---|
1538 | clp->setSpecialOptions(clpOptions|(64|128|512|1024|2048|4096)); |
---|
1539 | } |
---|
1540 | // User may want to clean up before strong branching |
---|
1541 | if ((clp->specialOptions()&32)!=0) { |
---|
1542 | clp->primal(1); |
---|
1543 | if (clp->numberIterations()) |
---|
1544 | model->messageHandler()->message(CBC_ITERATE_STRONG,*model->messagesPointer()) |
---|
1545 | << clp->numberIterations() |
---|
1546 | <<CoinMessageEol; |
---|
1547 | } |
---|
1548 | clp->setMaximumIterations(saveLimit); |
---|
1549 | #ifdef CRUNCH |
---|
1550 | int * backColumn = whichColumn+numberColumns; |
---|
1551 | #endif |
---|
1552 | for (i=0;i<numberStrong;i++) { |
---|
1553 | int iObject = choice[i].objectNumber; |
---|
1554 | const OsiObject * object = model->object(iObject); |
---|
1555 | const CbcSimpleInteger * simple = dynamic_cast <const CbcSimpleInteger *> (object); |
---|
1556 | int iSequence = simple->columnNumber(); |
---|
1557 | newLower[i]= ceil(saveSolution[iSequence]); |
---|
1558 | newUpper[i]= floor(saveSolution[iSequence]); |
---|
1559 | #ifdef CRUNCH |
---|
1560 | iSequence = backColumn[iSequence]; |
---|
1561 | assert (iSequence>=0); |
---|
1562 | #endif |
---|
1563 | which[i]=iSequence; |
---|
1564 | outputSolution[2*i]= new double [numberColumns]; |
---|
1565 | outputSolution[2*i+1]= new double [numberColumns]; |
---|
1566 | } |
---|
1567 | //clp->writeMps("bad"); |
---|
1568 | returnCode=clp->strongBranching(numberStrong,which, |
---|
1569 | newLower, newUpper,outputSolution, |
---|
1570 | outputStuff,outputStuff+2*numberStrong,!solveAll,false, |
---|
1571 | startFinishOptions); |
---|
1572 | #ifndef CRUNCH |
---|
1573 | clp->setSpecialOptions(clpOptions); // restore |
---|
1574 | clp->setMaximumIterations(saveMaxIts); |
---|
1575 | clp->setLogLevel(saveLogLevel); |
---|
1576 | #endif |
---|
1577 | if (returnCode==-2) { |
---|
1578 | // bad factorization!!! |
---|
1579 | // Doing normal way |
---|
1580 | // Mark hot start |
---|
1581 | solver->markHotStart(); |
---|
1582 | clp = NULL; |
---|
1583 | } else { |
---|
1584 | #ifdef CRUNCH |
---|
1585 | // extract solution |
---|
1586 | //bool checkSol=true; |
---|
1587 | for (i=0;i<numberStrong;i++) { |
---|
1588 | int iObject = choice[i].objectNumber; |
---|
1589 | const OsiObject * object = model->object(iObject); |
---|
1590 | const CbcSimpleInteger * simple = dynamic_cast <const CbcSimpleInteger *> (object); |
---|
1591 | int iSequence = simple->columnNumber(); |
---|
1592 | which[i]=iSequence; |
---|
1593 | double * sol = outputSolution[2*i]; |
---|
1594 | double * sol2 = outputSolution[2*i+1]; |
---|
1595 | //bool x=true; |
---|
1596 | //bool x2=true; |
---|
1597 | for (int iColumn=numberColumns-1;iColumn>=0;iColumn--) { |
---|
1598 | int jColumn = backColumn[iColumn]; |
---|
1599 | if (jColumn>=0) { |
---|
1600 | sol[iColumn]=sol[jColumn]; |
---|
1601 | sol2[iColumn]=sol2[jColumn]; |
---|
1602 | } else { |
---|
1603 | sol[iColumn]=saveSolution[iColumn]; |
---|
1604 | sol2[iColumn]=saveSolution[iColumn]; |
---|
1605 | } |
---|
1606 | } |
---|
1607 | } |
---|
1608 | #endif |
---|
1609 | } |
---|
1610 | #ifdef CRUNCH |
---|
1611 | delete [] whichColumn; |
---|
1612 | delete [] whichRow; |
---|
1613 | delete small; |
---|
1614 | #endif |
---|
1615 | delete [] which; |
---|
1616 | } else { |
---|
1617 | // Doing normal way |
---|
1618 | // Mark hot start |
---|
1619 | solver->markHotStart(); |
---|
1620 | } |
---|
1621 | # else /* COIN_HAS_CLP */ |
---|
1622 | |
---|
1623 | OsiSolverInterface *clp = NULL ; |
---|
1624 | double **outputSolution = NULL ; |
---|
1625 | int *outputStuff = NULL ; |
---|
1626 | double * newLower = NULL ; |
---|
1627 | double * newUpper = NULL ; |
---|
1628 | |
---|
1629 | solver->markHotStart(); |
---|
1630 | |
---|
1631 | # endif /* COIN_HAS_CLP */ |
---|
1632 | /* |
---|
1633 | Open a loop to do the strong branching LPs. For each candidate variable, |
---|
1634 | solve an LP with the variable forced down, then up. If a direction turns |
---|
1635 | out to be infeasible or monotonic (i.e., over the dual objective cutoff), |
---|
1636 | force the objective change to be big (1.0e100). If we determine the problem |
---|
1637 | is infeasible, or find a monotone variable, escape the loop. |
---|
1638 | |
---|
1639 | TODO: The `restore bounds' part might be better encapsulated as an |
---|
1640 | unbranch() method. Branching objects more exotic than simple integers |
---|
1641 | or cliques might not restrict themselves to variable bounds. |
---|
1642 | |
---|
1643 | TODO: Virtuous solvers invalidate the current solution (or give bogus |
---|
1644 | results :-) when the bounds are changed out from under them. So we |
---|
1645 | need to do all the work associated with finding a new solution before |
---|
1646 | restoring the bounds. |
---|
1647 | */ |
---|
1648 | for (i = 0 ; i < numberStrong ; i++) |
---|
1649 | { double objectiveChange ; |
---|
1650 | double newObjectiveValue=1.0e100; |
---|
1651 | // status is 0 finished, 1 infeasible and other |
---|
1652 | int iStatus; |
---|
1653 | /* |
---|
1654 | Try the down direction first. (Specify the initial branching alternative as |
---|
1655 | down with a call to way(-1). Each subsequent call to branch() performs the |
---|
1656 | specified branch and advances the branch object state to the next branch |
---|
1657 | alternative.) |
---|
1658 | */ |
---|
1659 | if (!clp) { |
---|
1660 | choice[i].possibleBranch->way(-1) ; |
---|
1661 | choice[i].possibleBranch->branch() ; |
---|
1662 | bool feasible=true; |
---|
1663 | if (checkFeasibility) { |
---|
1664 | // check branching did not make infeasible |
---|
1665 | int iColumn; |
---|
1666 | int numberColumns = solver->getNumCols(); |
---|
1667 | const double * columnLower = solver->getColLower(); |
---|
1668 | const double * columnUpper = solver->getColUpper(); |
---|
1669 | for (iColumn= 0;iColumn<numberColumns;iColumn++) { |
---|
1670 | if (columnLower[iColumn]>columnUpper[iColumn]+1.0e-5) |
---|
1671 | feasible=false; |
---|
1672 | } |
---|
1673 | } |
---|
1674 | if (feasible) { |
---|
1675 | solver->solveFromHotStart() ; |
---|
1676 | numberStrongDone++; |
---|
1677 | numberStrongIterations += solver->getIterationCount(); |
---|
1678 | /* |
---|
1679 | We now have an estimate of objective degradation that we can use for strong |
---|
1680 | branching. If we're over the cutoff, the variable is monotone up. |
---|
1681 | If we actually made it to optimality, check for a solution, and if we have |
---|
1682 | a good one, call setBestSolution to process it. Note that this may reduce the |
---|
1683 | cutoff, so we check again to see if we can declare this variable monotone. |
---|
1684 | */ |
---|
1685 | if (solver->isProvenOptimal()) |
---|
1686 | iStatus=0; // optimal |
---|
1687 | else if (solver->isIterationLimitReached() |
---|
1688 | &&!solver->isDualObjectiveLimitReached()) |
---|
1689 | iStatus=2; // unknown |
---|
1690 | else |
---|
1691 | iStatus=1; // infeasible |
---|
1692 | newObjectiveValue = solver->getObjSense()*solver->getObjValue(); |
---|
1693 | choice[i].numItersDown = solver->getIterationCount(); |
---|
1694 | } else { |
---|
1695 | iStatus=1; // infeasible |
---|
1696 | newObjectiveValue = 1.0e100; |
---|
1697 | choice[i].numItersDown = 0; |
---|
1698 | } |
---|
1699 | } else { |
---|
1700 | iStatus = outputStuff[2*i]; |
---|
1701 | choice[i].numItersDown = outputStuff[2*numberStrong+2*i]; |
---|
1702 | numberStrongDone++; |
---|
1703 | numberStrongIterations += choice[i].numItersDown; |
---|
1704 | newObjectiveValue = objectiveValue+newUpper[i]; |
---|
1705 | solver->setColSolution(outputSolution[2*i]); |
---|
1706 | } |
---|
1707 | objectiveChange = CoinMax(newObjectiveValue - objectiveValue_,0.0); |
---|
1708 | if (!iStatus) { |
---|
1709 | choice[i].finishedDown = true ; |
---|
1710 | if (newObjectiveValue>=model->getCutoff()) { |
---|
1711 | objectiveChange = 1.0e100; // say infeasible |
---|
1712 | numberStrongInfeasible++; |
---|
1713 | } else { |
---|
1714 | // See if integer solution |
---|
1715 | if (model->feasibleSolution(choice[i].numIntInfeasDown, |
---|
1716 | choice[i].numObjInfeasDown) |
---|
1717 | &&model->problemFeasibility()->feasible(model,-1)>=0) { |
---|
1718 | model->setBestSolution(CBC_STRONGSOL, |
---|
1719 | newObjectiveValue, |
---|
1720 | solver->getColSolution()) ; |
---|
1721 | // only needed for odd solvers |
---|
1722 | newObjectiveValue = solver->getObjSense()*solver->getObjValue(); |
---|
1723 | objectiveChange = CoinMax(newObjectiveValue-objectiveValue_,0.0) ; |
---|
1724 | model->setLastHeuristic(NULL); |
---|
1725 | model->incrementUsed(solver->getColSolution()); |
---|
1726 | if (newObjectiveValue >= model->getCutoff()) { // *new* cutoff |
---|
1727 | objectiveChange = 1.0e100 ; |
---|
1728 | numberStrongInfeasible++; |
---|
1729 | } |
---|
1730 | } |
---|
1731 | } |
---|
1732 | } else if (iStatus==1) { |
---|
1733 | objectiveChange = 1.0e100 ; |
---|
1734 | numberStrongInfeasible++; |
---|
1735 | } else { |
---|
1736 | // Can't say much as we did not finish |
---|
1737 | choice[i].finishedDown = false ; |
---|
1738 | numberUnfinished++; |
---|
1739 | } |
---|
1740 | choice[i].downMovement = objectiveChange ; |
---|
1741 | |
---|
1742 | // restore bounds |
---|
1743 | if (!clp) |
---|
1744 | { for (int j=0;j<numberColumns;j++) { |
---|
1745 | if (saveLower[j] != lower[j]) |
---|
1746 | solver->setColLower(j,saveLower[j]); |
---|
1747 | if (saveUpper[j] != upper[j]) |
---|
1748 | solver->setColUpper(j,saveUpper[j]); |
---|
1749 | } |
---|
1750 | } |
---|
1751 | //printf("Down on %d, status is %d, obj %g its %d cost %g finished %d inf %d infobj %d\n", |
---|
1752 | // choice[i].objectNumber,iStatus,newObjectiveValue,choice[i].numItersDown, |
---|
1753 | // choice[i].downMovement,choice[i].finishedDown,choice[i].numIntInfeasDown, |
---|
1754 | // choice[i].numObjInfeasDown); |
---|
1755 | |
---|
1756 | // repeat the whole exercise, forcing the variable up |
---|
1757 | if (!clp) { |
---|
1758 | bool feasible=true; |
---|
1759 | // If odd branching then maybe just one possibility |
---|
1760 | if(choice[i].possibleBranch->numberBranchesLeft()>0) { |
---|
1761 | choice[i].possibleBranch->branch(); |
---|
1762 | if (checkFeasibility) { |
---|
1763 | // check branching did not make infeasible |
---|
1764 | int iColumn; |
---|
1765 | int numberColumns = solver->getNumCols(); |
---|
1766 | const double * columnLower = solver->getColLower(); |
---|
1767 | const double * columnUpper = solver->getColUpper(); |
---|
1768 | for (iColumn= 0;iColumn<numberColumns;iColumn++) { |
---|
1769 | if (columnLower[iColumn]>columnUpper[iColumn]+1.0e-5) |
---|
1770 | feasible=false; |
---|
1771 | } |
---|
1772 | } |
---|
1773 | } else { |
---|
1774 | // second branch infeasible |
---|
1775 | feasible=false; |
---|
1776 | } |
---|
1777 | if (feasible) { |
---|
1778 | solver->solveFromHotStart() ; |
---|
1779 | numberStrongDone++; |
---|
1780 | numberStrongIterations += solver->getIterationCount(); |
---|
1781 | /* |
---|
1782 | We now have an estimate of objective degradation that we can use for strong |
---|
1783 | branching. If we're over the cutoff, the variable is monotone up. |
---|
1784 | If we actually made it to optimality, check for a solution, and if we have |
---|
1785 | a good one, call setBestSolution to process it. Note that this may reduce the |
---|
1786 | cutoff, so we check again to see if we can declare this variable monotone. |
---|
1787 | */ |
---|
1788 | if (solver->isProvenOptimal()) |
---|
1789 | iStatus=0; // optimal |
---|
1790 | else if (solver->isIterationLimitReached() |
---|
1791 | &&!solver->isDualObjectiveLimitReached()) |
---|
1792 | iStatus=2; // unknown |
---|
1793 | else |
---|
1794 | iStatus=1; // infeasible |
---|
1795 | newObjectiveValue = solver->getObjSense()*solver->getObjValue(); |
---|
1796 | choice[i].numItersUp = solver->getIterationCount(); |
---|
1797 | } else { |
---|
1798 | iStatus=1; // infeasible |
---|
1799 | newObjectiveValue = 1.0e100; |
---|
1800 | choice[i].numItersDown = 0; |
---|
1801 | } |
---|
1802 | } else { |
---|
1803 | iStatus = outputStuff[2*i+1]; |
---|
1804 | choice[i].numItersUp = outputStuff[2*numberStrong+2*i+1]; |
---|
1805 | numberStrongDone++; |
---|
1806 | numberStrongIterations += choice[i].numItersUp; |
---|
1807 | newObjectiveValue = objectiveValue+newLower[i]; |
---|
1808 | solver->setColSolution(outputSolution[2*i+1]); |
---|
1809 | } |
---|
1810 | objectiveChange = CoinMax(newObjectiveValue - objectiveValue_,0.0); |
---|
1811 | if (!iStatus) { |
---|
1812 | choice[i].finishedUp = true ; |
---|
1813 | if (newObjectiveValue>=model->getCutoff()) { |
---|
1814 | objectiveChange = 1.0e100; // say infeasible |
---|
1815 | numberStrongInfeasible++; |
---|
1816 | } else { |
---|
1817 | // See if integer solution |
---|
1818 | if (model->feasibleSolution(choice[i].numIntInfeasUp, |
---|
1819 | choice[i].numObjInfeasUp) |
---|
1820 | &&model->problemFeasibility()->feasible(model,-1)>=0) { |
---|
1821 | model->setBestSolution(CBC_STRONGSOL, |
---|
1822 | newObjectiveValue, |
---|
1823 | solver->getColSolution()) ; |
---|
1824 | // only needed for odd solvers |
---|
1825 | newObjectiveValue = solver->getObjSense()*solver->getObjValue(); |
---|
1826 | objectiveChange = CoinMax(newObjectiveValue-objectiveValue_,0.0) ; |
---|
1827 | model->setLastHeuristic(NULL); |
---|
1828 | model->incrementUsed(solver->getColSolution()); |
---|
1829 | if (newObjectiveValue >= model->getCutoff()) { // *new* cutoff |
---|
1830 | objectiveChange = 1.0e100 ; |
---|
1831 | numberStrongInfeasible++; |
---|
1832 | } |
---|
1833 | } |
---|
1834 | } |
---|
1835 | } else if (iStatus==1) { |
---|
1836 | objectiveChange = 1.0e100 ; |
---|
1837 | numberStrongInfeasible++; |
---|
1838 | } else { |
---|
1839 | // Can't say much as we did not finish |
---|
1840 | choice[i].finishedUp = false ; |
---|
1841 | numberUnfinished++; |
---|
1842 | } |
---|
1843 | choice[i].upMovement = objectiveChange ; |
---|
1844 | |
---|
1845 | // restore bounds |
---|
1846 | if (!clp) |
---|
1847 | { for (int j=0;j<numberColumns;j++) { |
---|
1848 | if (saveLower[j] != lower[j]) |
---|
1849 | solver->setColLower(j,saveLower[j]); |
---|
1850 | if (saveUpper[j] != upper[j]) |
---|
1851 | solver->setColUpper(j,saveUpper[j]); |
---|
1852 | } |
---|
1853 | } |
---|
1854 | |
---|
1855 | //printf("Up on %d, status is %d, obj %g its %d cost %g finished %d inf %d infobj %d\n", |
---|
1856 | // choice[i].objectNumber,iStatus,newObjectiveValue,choice[i].numItersUp, |
---|
1857 | // choice[i].upMovement,choice[i].finishedUp,choice[i].numIntInfeasUp, |
---|
1858 | // choice[i].numObjInfeasUp); |
---|
1859 | |
---|
1860 | /* |
---|
1861 | End of evaluation for this candidate variable. Possibilities are: |
---|
1862 | * Both sides below cutoff; this variable is a candidate for branching. |
---|
1863 | * Both sides infeasible or above the objective cutoff: no further action |
---|
1864 | here. Break from the evaluation loop and assume the node will be purged |
---|
1865 | by the caller. |
---|
1866 | * One side below cutoff: Install the branch (i.e., fix the variable). Break |
---|
1867 | from the evaluation loop and assume the node will be reoptimised by the |
---|
1868 | caller. |
---|
1869 | */ |
---|
1870 | // reset |
---|
1871 | choice[i].possibleBranch->resetNumberBranchesLeft(); |
---|
1872 | if (choice[i].upMovement<1.0e100) { |
---|
1873 | if(choice[i].downMovement<1.0e100) { |
---|
1874 | // feasible - no action |
---|
1875 | } else { |
---|
1876 | // up feasible, down infeasible |
---|
1877 | anyAction=-1; |
---|
1878 | //printf("Down infeasible for choice %d sequence %d\n",i, |
---|
1879 | // model->object(choice[i].objectNumber)->columnNumber()); |
---|
1880 | if (!solveAll) { |
---|
1881 | choice[i].possibleBranch->way(1); |
---|
1882 | choice[i].possibleBranch->branch(); |
---|
1883 | break; |
---|
1884 | } else { |
---|
1885 | choice[i].fix=1; |
---|
1886 | } |
---|
1887 | } |
---|
1888 | } else { |
---|
1889 | if(choice[i].downMovement<1.0e100) { |
---|
1890 | // down feasible, up infeasible |
---|
1891 | anyAction=-1; |
---|
1892 | //printf("Up infeasible for choice %d sequence %d\n",i, |
---|
1893 | // model->object(choice[i].objectNumber)->columnNumber()); |
---|
1894 | if (!solveAll) { |
---|
1895 | choice[i].possibleBranch->way(-1); |
---|
1896 | choice[i].possibleBranch->branch(); |
---|
1897 | break; |
---|
1898 | } else { |
---|
1899 | choice[i].fix=-1; |
---|
1900 | } |
---|
1901 | } else { |
---|
1902 | // neither side feasible |
---|
1903 | anyAction=-2; |
---|
1904 | //printf("Both infeasible for choice %d sequence %d\n",i, |
---|
1905 | // model->object(choice[i].objectNumber)->columnNumber()); |
---|
1906 | break; |
---|
1907 | } |
---|
1908 | } |
---|
1909 | bool hitMaxTime = ( CoinCpuTime()-model->getDblParam(CbcModel::CbcStartSeconds) > |
---|
1910 | model->getDblParam(CbcModel::CbcMaximumSeconds)); |
---|
1911 | if (hitMaxTime) { |
---|
1912 | numberStrong=i+1; |
---|
1913 | break; |
---|
1914 | } |
---|
1915 | } |
---|
1916 | if (!clp) { |
---|
1917 | // Delete the snapshot |
---|
1918 | solver->unmarkHotStart(); |
---|
1919 | } else { |
---|
1920 | delete [] newLower; |
---|
1921 | delete [] newUpper; |
---|
1922 | delete [] outputStuff; |
---|
1923 | int i; |
---|
1924 | for (i=0;i<2*numberStrong;i++) |
---|
1925 | delete [] outputSolution[i]; |
---|
1926 | delete [] outputSolution; |
---|
1927 | } |
---|
1928 | solver->setIntParam(OsiMaxNumIterationHotStart,saveLimit); |
---|
1929 | // restore basis |
---|
1930 | solver->setWarmStart(ws); |
---|
1931 | // Unless infeasible we will carry on |
---|
1932 | // But we could fix anyway |
---|
1933 | if (anyAction==-1&&solveAll) { |
---|
1934 | // apply and take off |
---|
1935 | for (i = 0 ; i < numberStrong ; i++) { |
---|
1936 | if (choice[i].fix) { |
---|
1937 | choice[i].possibleBranch->way(choice[i].fix) ; |
---|
1938 | choice[i].possibleBranch->branch() ; |
---|
1939 | } |
---|
1940 | } |
---|
1941 | bool feasible=true; |
---|
1942 | if (checkFeasibility) { |
---|
1943 | // check branching did not make infeasible |
---|
1944 | int iColumn; |
---|
1945 | int numberColumns = solver->getNumCols(); |
---|
1946 | const double * columnLower = solver->getColLower(); |
---|
1947 | const double * columnUpper = solver->getColUpper(); |
---|
1948 | for (iColumn= 0;iColumn<numberColumns;iColumn++) { |
---|
1949 | if (columnLower[iColumn]>columnUpper[iColumn]+1.0e-5) |
---|
1950 | feasible=false; |
---|
1951 | } |
---|
1952 | } |
---|
1953 | if (feasible) { |
---|
1954 | // can do quick optimality check |
---|
1955 | int easy=2; |
---|
1956 | solver->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo,&easy) ; |
---|
1957 | solver->resolve() ; |
---|
1958 | solver->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo,NULL) ; |
---|
1959 | feasible = solver->isProvenOptimal(); |
---|
1960 | } |
---|
1961 | if (feasible) { |
---|
1962 | memcpy(saveSolution,solver->getColSolution(),numberColumns*sizeof(double)); |
---|
1963 | model->reserveCurrentSolution(saveSolution); |
---|
1964 | memcpy(saveLower,solver->getColLower(),numberColumns*sizeof(double)); |
---|
1965 | memcpy(saveUpper,solver->getColUpper(),numberColumns*sizeof(double)); |
---|
1966 | // Clean up all candidates whih are fixed |
---|
1967 | int numberLeft=0; |
---|
1968 | for (i = 0 ; i < numberStrong ; i++) { |
---|
1969 | CbcStrongInfo thisChoice = choice[i]; |
---|
1970 | choice[i].possibleBranch=NULL; |
---|
1971 | const OsiObject * object = model->object(thisChoice.objectNumber); |
---|
1972 | int preferredWay; |
---|
1973 | double infeasibility = object->infeasibility(&usefulInfo,preferredWay); |
---|
1974 | if (!infeasibility) { |
---|
1975 | // take out |
---|
1976 | delete thisChoice.possibleBranch; |
---|
1977 | } else { |
---|
1978 | choice[numberLeft++]=thisChoice; |
---|
1979 | } |
---|
1980 | } |
---|
1981 | numberStrong=numberLeft; |
---|
1982 | for (;i<maximumStrong;i++) { |
---|
1983 | delete choice[i].possibleBranch; |
---|
1984 | choice[i].possibleBranch=NULL; |
---|
1985 | } |
---|
1986 | // If all fixed then round again |
---|
1987 | if (!numberLeft) { |
---|
1988 | finished=false; |
---|
1989 | numberStrong=0; |
---|
1990 | saveNumberStrong=0; |
---|
1991 | maximumStrong=1; |
---|
1992 | } else { |
---|
1993 | anyAction=0; |
---|
1994 | } |
---|
1995 | // If these two uncommented then different action |
---|
1996 | anyAction=-1; |
---|
1997 | finished=true; |
---|
1998 | //printf("some fixed but continuing %d left\n",numberLeft); |
---|
1999 | } else { |
---|
2000 | anyAction=-2; // say infeasible |
---|
2001 | } |
---|
2002 | } |
---|
2003 | delete ws; |
---|
2004 | int numberNodes = model->getNodeCount(); |
---|
2005 | // update number of strong iterations etc |
---|
2006 | model->incrementStrongInfo(numberStrongDone,numberStrongIterations, |
---|
2007 | anyAction==-2 ? 0:numberStrongInfeasible,anyAction==-2); |
---|
2008 | |
---|
2009 | /* |
---|
2010 | anyAction >= 0 indicates that strong branching didn't produce any monotone |
---|
2011 | variables. Sift through the candidates for the best one. |
---|
2012 | |
---|
2013 | QUERY: Setting numberNodes looks to be a distributed noop. numberNodes is |
---|
2014 | local to this code block. Perhaps should be numberNodes_ from model? |
---|
2015 | Unclear what this calculation is doing. |
---|
2016 | */ |
---|
2017 | if (anyAction>=0) { |
---|
2018 | |
---|
2019 | // get average cost per iteration and assume stopped ones |
---|
2020 | // would stop after 50% more iterations at average cost??? !!! ??? |
---|
2021 | double averageCostPerIteration=0.0; |
---|
2022 | double totalNumberIterations=1.0; |
---|
2023 | int smallestNumberInfeasibilities=COIN_INT_MAX; |
---|
2024 | for (i=0;i<numberStrong;i++) { |
---|
2025 | totalNumberIterations += choice[i].numItersDown + |
---|
2026 | choice[i].numItersUp ; |
---|
2027 | averageCostPerIteration += choice[i].downMovement + |
---|
2028 | choice[i].upMovement; |
---|
2029 | smallestNumberInfeasibilities= |
---|
2030 | CoinMin(CoinMin(choice[i].numIntInfeasDown , |
---|
2031 | choice[i].numIntInfeasUp ), |
---|
2032 | smallestNumberInfeasibilities); |
---|
2033 | } |
---|
2034 | //if (smallestNumberInfeasibilities>=numberIntegerInfeasibilities) |
---|
2035 | //numberNodes=1000000; // switch off search for better solution |
---|
2036 | numberNodes=1000000; // switch off anyway |
---|
2037 | averageCostPerIteration /= totalNumberIterations; |
---|
2038 | // all feasible - choose best bet |
---|
2039 | |
---|
2040 | // New method does all at once so it can be more sophisticated |
---|
2041 | // in deciding how to balance actions. |
---|
2042 | // But it does need arrays |
---|
2043 | double * changeUp = new double [numberStrong]; |
---|
2044 | int * numberInfeasibilitiesUp = new int [numberStrong]; |
---|
2045 | double * changeDown = new double [numberStrong]; |
---|
2046 | int * numberInfeasibilitiesDown = new int [numberStrong]; |
---|
2047 | CbcBranchingObject ** objects = new CbcBranchingObject * [ numberStrong]; |
---|
2048 | for (i = 0 ; i < numberStrong ; i++) { |
---|
2049 | int iColumn = choice[i].possibleBranch->variable() ; |
---|
2050 | model->messageHandler()->message(CBC_STRONG,*model->messagesPointer()) |
---|
2051 | << i << iColumn |
---|
2052 | <<choice[i].downMovement<<choice[i].numIntInfeasDown |
---|
2053 | <<choice[i].upMovement<<choice[i].numIntInfeasUp |
---|
2054 | <<choice[i].possibleBranch->value() |
---|
2055 | <<CoinMessageEol; |
---|
2056 | changeUp[i]=choice[i].upMovement; |
---|
2057 | numberInfeasibilitiesUp[i] = choice[i].numIntInfeasUp; |
---|
2058 | changeDown[i]=choice[i].downMovement; |
---|
2059 | numberInfeasibilitiesDown[i] = choice[i].numIntInfeasDown; |
---|
2060 | objects[i] = choice[i].possibleBranch; |
---|
2061 | } |
---|
2062 | int whichObject = decision->bestBranch(objects,numberStrong,numberUnsatisfied_, |
---|
2063 | changeUp,numberInfeasibilitiesUp, |
---|
2064 | changeDown,numberInfeasibilitiesDown, |
---|
2065 | objectiveValue_); |
---|
2066 | // move branching object and make sure it will not be deleted |
---|
2067 | if (whichObject>=0) { |
---|
2068 | branch_ = objects[whichObject]; |
---|
2069 | if (model->messageHandler()->logLevel()>3) |
---|
2070 | printf("Choosing column %d\n",choice[whichObject].possibleBranch->variable()) ; |
---|
2071 | choice[whichObject].possibleBranch=NULL; |
---|
2072 | } |
---|
2073 | delete [] changeUp; |
---|
2074 | delete [] numberInfeasibilitiesUp; |
---|
2075 | delete [] changeDown; |
---|
2076 | delete [] numberInfeasibilitiesDown; |
---|
2077 | delete [] objects; |
---|
2078 | } |
---|
2079 | # ifdef COIN_HAS_CLP |
---|
2080 | if (osiclp&&!allNormal) { |
---|
2081 | // back to normal |
---|
2082 | osiclp->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo,NULL) ; |
---|
2083 | } |
---|
2084 | # endif |
---|
2085 | } |
---|
2086 | /* |
---|
2087 | Simple branching. Probably just one, but we may have got here |
---|
2088 | because of an odd branch e.g. a cut |
---|
2089 | */ |
---|
2090 | else { |
---|
2091 | // not strong |
---|
2092 | // C) create branching object |
---|
2093 | branch_ = choice[bestChoice].possibleBranch; |
---|
2094 | choice[bestChoice].possibleBranch=NULL; |
---|
2095 | } |
---|
2096 | } |
---|
2097 | // Set guessed solution value |
---|
2098 | guessedObjectiveValue_ = objectiveValue_+estimatedDegradation; |
---|
2099 | /* |
---|
2100 | Cleanup, then we're outta here. |
---|
2101 | */ |
---|
2102 | if (!model->branchingMethod()||dynamicBranchingObject) |
---|
2103 | delete decision; |
---|
2104 | |
---|
2105 | for (i=0;i<maximumStrong;i++) |
---|
2106 | delete choice[i].possibleBranch; |
---|
2107 | delete [] choice; |
---|
2108 | delete [] saveLower; |
---|
2109 | delete [] saveUpper; |
---|
2110 | |
---|
2111 | // restore solution |
---|
2112 | solver->setColSolution(saveSolution); |
---|
2113 | delete [] saveSolution; |
---|
2114 | return anyAction; |
---|
2115 | } |
---|
2116 | |
---|
2117 | /* |
---|
2118 | Version for dynamic pseudo costs. |
---|
2119 | |
---|
2120 | **** For now just return if anything odd |
---|
2121 | later allow even if odd |
---|
2122 | |
---|
2123 | The routine scans through the object list of the model looking for objects |
---|
2124 | that indicate infeasibility. It tests each object using strong branching |
---|
2125 | and selects the one with the least objective degradation. A corresponding |
---|
2126 | branching object is left attached to lastNode. |
---|
2127 | This version gives preference in evaluation to variables which |
---|
2128 | have not been evaluated many times. It also uses numberStrong |
---|
2129 | to say give up if last few tries have not changed incumbent. |
---|
2130 | See Achterberg, Koch and Martin. |
---|
2131 | |
---|
2132 | If strong branching is disabled, a candidate object is chosen essentially |
---|
2133 | at random (whatever object ends up in pos'n 0 of the candidate array). |
---|
2134 | |
---|
2135 | If a branching candidate is found to be monotone, bounds are set to fix the |
---|
2136 | variable and the routine immediately returns (the caller is expected to |
---|
2137 | reoptimize). |
---|
2138 | |
---|
2139 | If a branching candidate is found to result in infeasibility in both |
---|
2140 | directions, the routine immediately returns an indication of infeasibility. |
---|
2141 | |
---|
2142 | Returns: 0 both branch directions are feasible |
---|
2143 | -1 branching variable is monotone |
---|
2144 | -2 infeasible |
---|
2145 | -3 Use another method |
---|
2146 | |
---|
2147 | For now just fix on objective from strong branching. |
---|
2148 | */ |
---|
2149 | |
---|
2150 | int CbcNode::chooseDynamicBranch (CbcModel *model, CbcNode *lastNode, |
---|
2151 | OsiSolverBranch * & branches,int numberPassesLeft) |
---|
2152 | |
---|
2153 | { if (lastNode) |
---|
2154 | depth_ = lastNode->depth_+1; |
---|
2155 | else |
---|
2156 | depth_ = 0; |
---|
2157 | delete branch_; |
---|
2158 | branch_=NULL; |
---|
2159 | OsiSolverInterface * solver = model->solver(); |
---|
2160 | // get information on solver type |
---|
2161 | const OsiAuxInfo * auxInfo = solver->getAuxiliaryInfo(); |
---|
2162 | const OsiBabSolver * auxiliaryInfo = dynamic_cast<const OsiBabSolver *> (auxInfo); |
---|
2163 | if (!auxiliaryInfo) { |
---|
2164 | // use one from CbcModel |
---|
2165 | auxiliaryInfo = model->solverCharacteristics(); |
---|
2166 | } |
---|
2167 | // point to useful information |
---|
2168 | OsiBranchingInformation usefulInfo = model->usefulInformation(); |
---|
2169 | // and modify |
---|
2170 | usefulInfo.depth_=depth_; |
---|
2171 | assert (auxiliaryInfo); |
---|
2172 | //assert(objectiveValue_ == solver->getObjSense()*solver->getObjValue()); |
---|
2173 | double cutoff =model->getCutoff(); |
---|
2174 | double distanceToCutoff=cutoff-objectiveValue_; |
---|
2175 | const double * lower = solver->getColLower(); |
---|
2176 | const double * upper = solver->getColUpper(); |
---|
2177 | // See what user thinks |
---|
2178 | int anyAction=model->problemFeasibility()->feasible(model,0); |
---|
2179 | if (anyAction) { |
---|
2180 | // will return -2 if infeasible , 0 if treat as integer |
---|
2181 | return anyAction-1; |
---|
2182 | } |
---|
2183 | int i; |
---|
2184 | int saveStateOfSearch = model->stateOfSearch(); |
---|
2185 | int numberStrong=model->numberStrong(); |
---|
2186 | if (!auxiliaryInfo->warmStart()) |
---|
2187 | numberStrong=0; |
---|
2188 | // But make more likely to get out after some times |
---|
2189 | int changeStrategy=numberStrong; |
---|
2190 | double changeFactor=1.0; |
---|
2191 | // Use minimum of this and one stored in objects |
---|
2192 | //int numberBeforeTrust = model->numberBeforeTrust(); |
---|
2193 | int numberObjects = model->numberObjects(); |
---|
2194 | bool checkFeasibility = numberObjects>model->numberIntegers(); |
---|
2195 | // For now return if not simple |
---|
2196 | if (checkFeasibility) |
---|
2197 | return -3; |
---|
2198 | // Return if doing hot start (in BAB sense) |
---|
2199 | if (model->hotstartSolution()) |
---|
2200 | return -3; |
---|
2201 | #define RANGING |
---|
2202 | #ifdef RANGING |
---|
2203 | // Pass number |
---|
2204 | int kPass=0; |
---|
2205 | int numberRows = solver->getNumRows(); |
---|
2206 | #endif |
---|
2207 | int numberColumns = model->getNumCols(); |
---|
2208 | double * saveUpper = new double[numberColumns]; |
---|
2209 | double * saveLower = new double[numberColumns]; |
---|
2210 | |
---|
2211 | // Save solution in case heuristics need good solution later |
---|
2212 | |
---|
2213 | double * saveSolution = new double[numberColumns]; |
---|
2214 | memcpy(saveSolution,solver->getColSolution(),numberColumns*sizeof(double)); |
---|
2215 | model->reserveCurrentSolution(saveSolution); |
---|
2216 | /* |
---|
2217 | Get a branching decision object. Use the default dynamic decision criteria unless |
---|
2218 | the user has loaded a decision method into the model. |
---|
2219 | */ |
---|
2220 | CbcBranchDecision *decision = model->branchingMethod(); |
---|
2221 | if (!decision) |
---|
2222 | decision = new CbcBranchDynamicDecision(); |
---|
2223 | int numberMini=0; |
---|
2224 | int xPen=0; |
---|
2225 | int xMark=0; |
---|
2226 | for (i=0;i<numberColumns;i++) { |
---|
2227 | saveLower[i] = lower[i]; |
---|
2228 | saveUpper[i] = upper[i]; |
---|
2229 | } |
---|
2230 | // Get arrays to sort |
---|
2231 | double * sort = new double[numberObjects]; |
---|
2232 | int * whichObject = new int[numberObjects]; |
---|
2233 | int * objectMark = new int[2*numberObjects+1]; |
---|
2234 | // Arrays with movements |
---|
2235 | double * upEstimate = new double[numberObjects]; |
---|
2236 | double * downEstimate = new double[numberObjects]; |
---|
2237 | CbcStrongInfo * fixObject = new CbcStrongInfo[numberObjects]; |
---|
2238 | double estimatedDegradation=0.0; |
---|
2239 | int numberNodes=model->getNodeCount(); |
---|
2240 | int saveLogLevel = model->logLevel(); |
---|
2241 | if ((numberNodes%500)==0&&false) { |
---|
2242 | model->setLogLevel(6); |
---|
2243 | // Get average up and down costs |
---|
2244 | double averageUp=0.0; |
---|
2245 | double averageDown=0.0; |
---|
2246 | int numberUp=0; |
---|
2247 | int numberDown=0; |
---|
2248 | int i; |
---|
2249 | for ( i=0;i<numberObjects;i++) { |
---|
2250 | OsiObject * object = model->modifiableObject(i); |
---|
2251 | CbcSimpleIntegerDynamicPseudoCost * dynamicObject = |
---|
2252 | dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ; |
---|
2253 | assert(dynamicObject); |
---|
2254 | int numberUp2=0; |
---|
2255 | int numberDown2=0; |
---|
2256 | double up=0.0; |
---|
2257 | double down=0.0; |
---|
2258 | if (dynamicObject->numberTimesUp()) { |
---|
2259 | numberUp++; |
---|
2260 | averageUp += dynamicObject->upDynamicPseudoCost(); |
---|
2261 | numberUp2 += dynamicObject->numberTimesUp(); |
---|
2262 | up = dynamicObject->upDynamicPseudoCost(); |
---|
2263 | } |
---|
2264 | if (dynamicObject->numberTimesDown()) { |
---|
2265 | numberDown++; |
---|
2266 | averageDown += dynamicObject->downDynamicPseudoCost(); |
---|
2267 | numberDown2 += dynamicObject->numberTimesDown(); |
---|
2268 | down = dynamicObject->downDynamicPseudoCost(); |
---|
2269 | } |
---|
2270 | if (numberUp2||numberDown2) |
---|
2271 | printf("col %d - up %d times cost %g, - down %d times cost %g\n", |
---|
2272 | dynamicObject->columnNumber(),numberUp2,up,numberDown2,down); |
---|
2273 | } |
---|
2274 | if (numberUp) |
---|
2275 | averageUp /= (double) numberUp; |
---|
2276 | else |
---|
2277 | averageUp=1.0; |
---|
2278 | if (numberDown) |
---|
2279 | averageDown /= (double) numberDown; |
---|
2280 | else |
---|
2281 | averageDown=1.0; |
---|
2282 | printf("total - up %d vars average %g, - down %d vars average %g\n", |
---|
2283 | numberUp,averageUp,numberDown,averageDown); |
---|
2284 | } |
---|
2285 | int numberBeforeTrust = model->numberBeforeTrust(); |
---|
2286 | int numberPenalties = model->numberPenalties(); |
---|
2287 | if (numberBeforeTrust>=1000000) { |
---|
2288 | numberBeforeTrust = numberBeforeTrust % 1000000; |
---|
2289 | numberPenalties=0; |
---|
2290 | } else if (numberBeforeTrust<0) { |
---|
2291 | numberPenalties=numberColumns; |
---|
2292 | numberBeforeTrust=0; |
---|
2293 | } |
---|
2294 | // May go round twice if strong branching fixes all local candidates |
---|
2295 | bool finished=false; |
---|
2296 | int numberToFix=0; |
---|
2297 | # ifdef COIN_HAS_CLP |
---|
2298 | OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (solver); |
---|
2299 | int saveClpOptions=0; |
---|
2300 | if (osiclp) { |
---|
2301 | // for faster hot start |
---|
2302 | saveClpOptions = osiclp->specialOptions(); |
---|
2303 | osiclp->setSpecialOptions(saveClpOptions|8192); |
---|
2304 | } |
---|
2305 | # else |
---|
2306 | OsiSolverInterface *osiclp = 0 ; |
---|
2307 | # endif |
---|
2308 | const CglTreeProbingInfo * probingInfo = model->probingInfo(); |
---|
2309 | int saveSearchStrategy2 = model->searchStrategy(); |
---|
2310 | if (saveSearchStrategy2<999) { |
---|
2311 | // Get average up and down costs |
---|
2312 | double averageUp=0.0; |
---|
2313 | double averageDown=0.0; |
---|
2314 | { |
---|
2315 | int numberUp=0; |
---|
2316 | int numberDown=0; |
---|
2317 | int i; |
---|
2318 | for ( i=0;i<numberObjects;i++) { |
---|
2319 | OsiObject * object = model->modifiableObject(i); |
---|
2320 | CbcSimpleIntegerDynamicPseudoCost * dynamicObject = |
---|
2321 | dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ; |
---|
2322 | assert(dynamicObject); |
---|
2323 | if (dynamicObject->numberTimesUp()) { |
---|
2324 | numberUp++; |
---|
2325 | averageUp += dynamicObject->upDynamicPseudoCost(); |
---|
2326 | } |
---|
2327 | if (dynamicObject->numberTimesDown()) { |
---|
2328 | numberDown++; |
---|
2329 | averageDown += dynamicObject->downDynamicPseudoCost(); |
---|
2330 | } |
---|
2331 | } |
---|
2332 | if (numberUp) |
---|
2333 | averageUp /= (double) numberUp; |
---|
2334 | else |
---|
2335 | averageUp=1.0; |
---|
2336 | if (numberDown) |
---|
2337 | averageDown /= (double) numberDown; |
---|
2338 | else |
---|
2339 | averageDown=1.0; |
---|
2340 | for ( i=0;i<numberObjects;i++) { |
---|
2341 | OsiObject * object = model->modifiableObject(i); |
---|
2342 | CbcSimpleIntegerDynamicPseudoCost * dynamicObject = |
---|
2343 | dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ; |
---|
2344 | assert(dynamicObject); |
---|
2345 | if (!dynamicObject->numberTimesUp()) |
---|
2346 | dynamicObject->setUpDynamicPseudoCost(averageUp); |
---|
2347 | if (!dynamicObject->numberTimesDown()) |
---|
2348 | dynamicObject->setDownDynamicPseudoCost(averageDown); |
---|
2349 | } |
---|
2350 | } |
---|
2351 | } else if (saveSearchStrategy2<1999) { |
---|
2352 | // pseudo shadow prices |
---|
2353 | model->pseudoShadow(NULL,NULL); |
---|
2354 | } else if (saveSearchStrategy2<2999) { |
---|
2355 | // leave old ones |
---|
2356 | } else if (saveSearchStrategy2<3999) { |
---|
2357 | // pseudo shadow prices at root |
---|
2358 | if (!numberNodes) |
---|
2359 | model->pseudoShadow(NULL,NULL); |
---|
2360 | } else { |
---|
2361 | abort(); |
---|
2362 | } |
---|
2363 | if (saveSearchStrategy2>=0) |
---|
2364 | saveSearchStrategy2 = saveSearchStrategy2 % 1000; |
---|
2365 | if (saveSearchStrategy2==999) |
---|
2366 | saveSearchStrategy2=-1; |
---|
2367 | int px[4]={-1,-1,-1,-1}; |
---|
2368 | int saveSearchStrategy = saveSearchStrategy2<99 ? saveSearchStrategy2 : saveSearchStrategy2-100; |
---|
2369 | bool newWay = saveSearchStrategy2>98; |
---|
2370 | int numberNotTrusted=0; |
---|
2371 | int numberStrongDone=0; |
---|
2372 | int numberUnfinished=0; |
---|
2373 | int numberStrongInfeasible=0; |
---|
2374 | int numberStrongIterations=0; |
---|
2375 | while(!finished) { |
---|
2376 | finished=true; |
---|
2377 | decision->initialize(model); |
---|
2378 | // Some objects may compute an estimate of best solution from here |
---|
2379 | estimatedDegradation=0.0; |
---|
2380 | numberToFix=0; |
---|
2381 | int numberIntegerInfeasibilities=0; // without odd ones |
---|
2382 | int numberToDo=0; |
---|
2383 | int iBestNot=-1; |
---|
2384 | int iBestGot=-1; |
---|
2385 | double best=0.0; |
---|
2386 | numberNotTrusted=0; |
---|
2387 | numberStrongDone=0; |
---|
2388 | numberUnfinished=0; |
---|
2389 | numberStrongInfeasible=0; |
---|
2390 | numberStrongIterations=0; |
---|
2391 | int * which = objectMark+numberObjects+1; |
---|
2392 | int neededPenalties; |
---|
2393 | int branchingMethod=-1; |
---|
2394 | // We may go round this loop three times (only if we think we have solution) |
---|
2395 | for (int iPass=0;iPass<3;iPass++) { |
---|
2396 | |
---|
2397 | // compute current state |
---|
2398 | int numberObjectInfeasibilities; // just odd ones |
---|
2399 | model->feasibleSolution( |
---|
2400 | numberIntegerInfeasibilities, |
---|
2401 | numberObjectInfeasibilities); |
---|
2402 | |
---|
2403 | // Some objects may compute an estimate of best solution from here |
---|
2404 | estimatedDegradation=0.0; |
---|
2405 | numberUnsatisfied_ = 0; |
---|
2406 | // initialize sum of "infeasibilities" |
---|
2407 | sumInfeasibilities_ = 0.0; |
---|
2408 | int bestPriority=COIN_INT_MAX; |
---|
2409 | int number01 = 0; |
---|
2410 | const fixEntry * entry = NULL; |
---|
2411 | const int * toZero = NULL; |
---|
2412 | const int * toOne = NULL; |
---|
2413 | const int * backward = NULL; |
---|
2414 | int numberUnsatisProbed=0; |
---|
2415 | int numberUnsatisNotProbed=0; // 0-1 |
---|
2416 | if (probingInfo) { |
---|
2417 | number01 = probingInfo->numberIntegers(); |
---|
2418 | entry = probingInfo->fixEntries(); |
---|
2419 | toZero = probingInfo->toZero(); |
---|
2420 | toOne = probingInfo->toOne(); |
---|
2421 | backward = probingInfo->backward(); |
---|
2422 | if (!toZero[number01]) { |
---|
2423 | // no info |
---|
2424 | probingInfo=NULL; |
---|
2425 | } |
---|
2426 | } |
---|
2427 | /* |
---|
2428 | Scan for branching objects that indicate infeasibility. Choose candidates |
---|
2429 | using priority as the first criteria, then integer infeasibility. |
---|
2430 | |
---|
2431 | The algorithm is to fill the array with a set of good candidates (by |
---|
2432 | infeasibility) with priority bestPriority. Finding a candidate with |
---|
2433 | priority better (less) than bestPriority flushes the choice array. (This |
---|
2434 | serves as initialization when the first candidate is found.) |
---|
2435 | |
---|
2436 | */ |
---|
2437 | numberToDo=0; |
---|
2438 | neededPenalties=0; |
---|
2439 | iBestNot=-1; |
---|
2440 | double bestNot=0.0; |
---|
2441 | iBestGot=-1; |
---|
2442 | best=0.0; |
---|
2443 | #define PRINT_STUFF -1 |
---|
2444 | for (i=0;i<numberObjects;i++) { |
---|
2445 | OsiObject * object = model->modifiableObject(i); |
---|
2446 | CbcSimpleIntegerDynamicPseudoCost * dynamicObject = |
---|
2447 | dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ; |
---|
2448 | assert(dynamicObject); |
---|
2449 | int preferredWay; |
---|
2450 | double infeasibility = object->infeasibility(&usefulInfo,preferredWay); |
---|
2451 | int priorityLevel = object->priority(); |
---|
2452 | #define ZERO_ONE 0 |
---|
2453 | #define ZERO_FAKE 1.0e20; |
---|
2454 | #if ZERO_ONE==1 |
---|
2455 | // branch on 0-1 first (temp) |
---|
2456 | if (fabs(saveSolution[dynamicObject->columnNumber()])<1.0) |
---|
2457 | priorityLevel--; |
---|
2458 | #endif |
---|
2459 | #if ZERO_ONE==2 |
---|
2460 | if (fabs(saveSolution[dynamicObject->columnNumber()])<1.0) |
---|
2461 | infeasibility *= ZERO_FAKE; |
---|
2462 | #endif |
---|
2463 | if (infeasibility) { |
---|
2464 | // check branching method |
---|
2465 | if (branchingMethod!=dynamicObject->method()) { |
---|
2466 | if (branchingMethod==-1) |
---|
2467 | branchingMethod = dynamicObject->method(); |
---|
2468 | else |
---|
2469 | branchingMethod = 100; |
---|
2470 | } |
---|
2471 | int iColumn = dynamicObject->columnNumber(); |
---|
2472 | if (probingInfo) { |
---|
2473 | int iSeq = backward[iColumn]; |
---|
2474 | if (iSeq>=0) { |
---|
2475 | if (toZero[iSeq+1]>toZero[iSeq]) { |
---|
2476 | numberUnsatisProbed++; |
---|
2477 | } else { |
---|
2478 | numberUnsatisNotProbed++; |
---|
2479 | } |
---|
2480 | } |
---|
2481 | } |
---|
2482 | //double gap = saveUpper[iColumn]-saveLower[iColumn]; |
---|
2483 | // Give precedence to ones with gap of 1.0 |
---|
2484 | //assert(gap>0.0); |
---|
2485 | //infeasibility /= CoinMin(gap,100.0); |
---|
2486 | if (!depth_&&false) { |
---|
2487 | // try closest to 0.5 |
---|
2488 | double part =saveSolution[iColumn]-floor(saveSolution[iColumn]); |
---|
2489 | infeasibility = fabs(0.5-part); |
---|
2490 | } |
---|
2491 | bool gotDown=false; |
---|
2492 | int numberThisDown = dynamicObject->numberTimesDown(); |
---|
2493 | if (numberThisDown>=numberBeforeTrust) |
---|
2494 | gotDown=true; |
---|
2495 | bool gotUp=false; |
---|
2496 | int numberThisUp = dynamicObject->numberTimesUp(); |
---|
2497 | if (numberThisUp>=numberBeforeTrust) |
---|
2498 | gotUp=true; |
---|
2499 | if ((numberNodes%PRINT_STUFF)==0&&PRINT_STUFF>0) |
---|
2500 | printf("%d down %d %g up %d %g - infeas %g\n", |
---|
2501 | i,numberThisDown,object->downEstimate(),numberThisUp,object->upEstimate(), |
---|
2502 | infeasibility); |
---|
2503 | // Increase estimated degradation to solution |
---|
2504 | estimatedDegradation += CoinMin(object->upEstimate(),object->downEstimate()); |
---|
2505 | downEstimate[i]=object->downEstimate(); |
---|
2506 | upEstimate[i]=object->upEstimate(); |
---|
2507 | numberUnsatisfied_++; |
---|
2508 | sumInfeasibilities_ += infeasibility; |
---|
2509 | // Better priority? Flush choices. |
---|
2510 | if (priorityLevel<bestPriority) { |
---|
2511 | numberToDo=0; |
---|
2512 | bestPriority = priorityLevel; |
---|
2513 | iBestGot=-1; |
---|
2514 | best=0.0; |
---|
2515 | numberNotTrusted=0; |
---|
2516 | } else if (priorityLevel>bestPriority) { |
---|
2517 | continue; |
---|
2518 | } |
---|
2519 | if (!gotUp||!gotDown) |
---|
2520 | numberNotTrusted++; |
---|
2521 | // Check for suitability based on infeasibility. |
---|
2522 | if ((gotDown&&gotUp)&&numberStrong>0) { |
---|
2523 | sort[numberToDo]=-infeasibility; |
---|
2524 | if (infeasibility>best) { |
---|
2525 | best=infeasibility; |
---|
2526 | iBestGot=numberToDo; |
---|
2527 | } |
---|
2528 | } else { |
---|
2529 | objectMark[neededPenalties]=numberToDo; |
---|
2530 | which[neededPenalties++]=dynamicObject->columnNumber(); |
---|
2531 | int iColumn = dynamicObject->columnNumber(); |
---|
2532 | double part =saveSolution[iColumn]-floor(saveSolution[iColumn]); |
---|
2533 | sort[numberToDo]=-10.0*infeasibility; |
---|
2534 | if (!(numberThisUp+numberThisDown)) |
---|
2535 | sort[numberToDo] *= 100.0; // make even more likely |
---|
2536 | if (1.0-fabs(part-0.5)>bestNot) { |
---|
2537 | iBestNot=numberToDo; |
---|
2538 | bestNot = 1.0-fabs(part-0.5); |
---|
2539 | } |
---|
2540 | } |
---|
2541 | whichObject[numberToDo++]=i; |
---|
2542 | } else { |
---|
2543 | // for debug |
---|
2544 | downEstimate[i]=-1.0; |
---|
2545 | upEstimate[i]=-1.0; |
---|
2546 | } |
---|
2547 | } |
---|
2548 | if (numberUnsatisfied_) { |
---|
2549 | if (probingInfo&&false) |
---|
2550 | printf("nunsat %d, %d probed, %d other 0-1\n",numberUnsatisfied_, |
---|
2551 | numberUnsatisProbed,numberUnsatisNotProbed); |
---|
2552 | // some infeasibilities - go to next steps |
---|
2553 | break; |
---|
2554 | } else if (!iPass) { |
---|
2555 | // may just need resolve |
---|
2556 | solver->resolve(); |
---|
2557 | memcpy(saveSolution,solver->getColSolution(),numberColumns*sizeof(double)); |
---|
2558 | model->reserveCurrentSolution(saveSolution); |
---|
2559 | if (!solver->isProvenOptimal()) { |
---|
2560 | // infeasible |
---|
2561 | anyAction=-2; |
---|
2562 | break; |
---|
2563 | } |
---|
2564 | } else if (iPass==1) { |
---|
2565 | // looks like a solution - get paranoid |
---|
2566 | bool roundAgain=false; |
---|
2567 | // get basis |
---|
2568 | CoinWarmStartBasis * ws = dynamic_cast<CoinWarmStartBasis*>(solver->getWarmStart()); |
---|
2569 | if (!ws) |
---|
2570 | break; |
---|
2571 | double tolerance; |
---|
2572 | solver->getDblParam(OsiPrimalTolerance,tolerance); |
---|
2573 | for (i=0;i<numberColumns;i++) { |
---|
2574 | double value = saveSolution[i]; |
---|
2575 | if (value<lower[i]-tolerance) { |
---|
2576 | saveSolution[i]=lower[i]; |
---|
2577 | roundAgain=true; |
---|
2578 | ws->setStructStatus(i,CoinWarmStartBasis::atLowerBound); |
---|
2579 | } else if (value>upper[i]+tolerance) { |
---|
2580 | saveSolution[i]=upper[i]; |
---|
2581 | roundAgain=true; |
---|
2582 | ws->setStructStatus(i,CoinWarmStartBasis::atUpperBound); |
---|
2583 | } |
---|
2584 | } |
---|
2585 | if (roundAgain) { |
---|
2586 | // restore basis |
---|
2587 | solver->setWarmStart(ws); |
---|
2588 | solver->setColSolution(saveSolution); |
---|
2589 | delete ws; |
---|
2590 | bool takeHint; |
---|
2591 | OsiHintStrength strength; |
---|
2592 | solver->getHintParam(OsiDoDualInResolve,takeHint,strength); |
---|
2593 | solver->setHintParam(OsiDoDualInResolve,false,OsiHintDo) ; |
---|
2594 | solver->resolve(); |
---|
2595 | solver->setHintParam(OsiDoDualInResolve,takeHint,strength) ; |
---|
2596 | memcpy(saveSolution,solver->getColSolution(),numberColumns*sizeof(double)); |
---|
2597 | model->reserveCurrentSolution(saveSolution); |
---|
2598 | if (!solver->isProvenOptimal()) { |
---|
2599 | // infeasible |
---|
2600 | anyAction=-2; |
---|
2601 | break; |
---|
2602 | } |
---|
2603 | } else { |
---|
2604 | delete ws; |
---|
2605 | break; |
---|
2606 | } |
---|
2607 | } |
---|
2608 | } |
---|
2609 | if (anyAction==-2) { |
---|
2610 | break; |
---|
2611 | } |
---|
2612 | bool solveAll=false; // set true to say look at all even if some fixed (experiment) |
---|
2613 | solveAll=true; |
---|
2614 | // skip if solution |
---|
2615 | if (!numberUnsatisfied_) |
---|
2616 | break; |
---|
2617 | //bool skipAll = (numberBeforeTrust>20&&numberNodes>20000&&numberNotTrusted==0); |
---|
2618 | bool skipAll = numberNotTrusted==0||numberToDo==1; |
---|
2619 | bool doneHotStart=false; |
---|
2620 | int searchStrategy = saveSearchStrategy>=0 ? (saveSearchStrategy%10) : -1; |
---|
2621 | #ifndef CBC_WEAK_STRONG |
---|
2622 | if (((numberNodes%20)==0&&searchStrategy!=2)||(model->specialOptions()&8)!=0) |
---|
2623 | skipAll=false; |
---|
2624 | #endif |
---|
2625 | if (!newWay) { |
---|
2626 | // 10 up always use %10, 20 up as 10 and allow penalties |
---|
2627 | // But adjust depending on ratio of iterations |
---|
2628 | if (searchStrategy>0&&saveSearchStrategy<10) { |
---|
2629 | if (numberBeforeTrust>=5&&numberBeforeTrust<=10) { |
---|
2630 | if (searchStrategy!=2) { |
---|
2631 | if (depth_>5) { |
---|
2632 | int numberIterations = model->getIterationCount(); |
---|
2633 | int numberStrongIterations = model->numberStrongIterations(); |
---|
2634 | if (numberStrongIterations>numberIterations+10000) { |
---|
2635 | searchStrategy=2; |
---|
2636 | //skipAll=true; |
---|
2637 | } else if (numberStrongIterations*4+1000<numberIterations||depth_<5) { |
---|
2638 | searchStrategy=3; |
---|
2639 | skipAll=false; |
---|
2640 | } |
---|
2641 | } else { |
---|
2642 | searchStrategy=3; |
---|
2643 | skipAll=false; |
---|
2644 | } |
---|
2645 | } else { |
---|
2646 | //skipAll=true; |
---|
2647 | } |
---|
2648 | } |
---|
2649 | } |
---|
2650 | } else { |
---|
2651 | // But adjust depending on ratio of iterations |
---|
2652 | if (saveSearchStrategy<0) { |
---|
2653 | // unset |
---|
2654 | if ((numberNodes%20)==0||(model->specialOptions()&8)!=0) { |
---|
2655 | // Do numberStrong |
---|
2656 | searchStrategy=3; |
---|
2657 | } else if (depth_<5) { |
---|
2658 | // Do numberStrong |
---|
2659 | searchStrategy=2; |
---|
2660 | } else { |
---|
2661 | int numberIterations = model->getIterationCount(); |
---|
2662 | int numberStrongIterations = model->numberStrongIterations(); |
---|
2663 | int numberRows = solver->getNumRows(); |
---|
2664 | if (numberStrongIterations>numberIterations+CoinMin(10000,10*numberRows)) { |
---|
2665 | // off |
---|
2666 | searchStrategy=0; |
---|
2667 | } else if (numberStrongIterations*4+1000<numberIterations) { |
---|
2668 | // Do numberStrong if not trusted |
---|
2669 | searchStrategy=2; |
---|
2670 | } else { |
---|
2671 | searchStrategy=1; |
---|
2672 | } |
---|
2673 | } |
---|
2674 | } |
---|
2675 | if (searchStrategy<3&&(!numberNotTrusted||!searchStrategy)) |
---|
2676 | skipAll=true; |
---|
2677 | else |
---|
2678 | skipAll=false; |
---|
2679 | } |
---|
2680 | // worth trying if too many times |
---|
2681 | // Save basis |
---|
2682 | CoinWarmStart * ws = NULL; |
---|
2683 | // save limit |
---|
2684 | int saveLimit=0; |
---|
2685 | solver->getIntParam(OsiMaxNumIterationHotStart,saveLimit); |
---|
2686 | if (!skipAll) { |
---|
2687 | ws = solver->getWarmStart(); |
---|
2688 | int limit=100; |
---|
2689 | #if 0 |
---|
2690 | int averageBranchIterations = model->getIterationCount()/(model->getNodeCount()+1); |
---|
2691 | if (numberNodes) |
---|
2692 | limit = CoinMin(CoinMax(limit,2*averageBranchIterations),500); |
---|
2693 | else |
---|
2694 | limit = 500; |
---|
2695 | #endif |
---|
2696 | if ((!saveStateOfSearch||searchStrategy>3)&&saveLimit<limit&&saveLimit==100) |
---|
2697 | solver->setIntParam(OsiMaxNumIterationHotStart,limit); |
---|
2698 | } |
---|
2699 | // Say which one will be best |
---|
2700 | int whichChoice=0; |
---|
2701 | int bestChoice; |
---|
2702 | if (iBestGot>=0) |
---|
2703 | bestChoice=iBestGot; |
---|
2704 | else |
---|
2705 | bestChoice=iBestNot; |
---|
2706 | assert (bestChoice>=0); |
---|
2707 | // If we have hit max time don't do strong branching |
---|
2708 | bool hitMaxTime = ( CoinCpuTime()-model->getDblParam(CbcModel::CbcStartSeconds) > |
---|
2709 | model->getDblParam(CbcModel::CbcMaximumSeconds)); |
---|
2710 | // also give up if we are looping round too much |
---|
2711 | if (hitMaxTime||numberPassesLeft<=0||(!numberNotTrusted&&false)||branchingMethod==11) { |
---|
2712 | int iObject = whichObject[bestChoice]; |
---|
2713 | OsiObject * object = model->modifiableObject(iObject); |
---|
2714 | int preferredWay; |
---|
2715 | object->infeasibility(&usefulInfo,preferredWay); |
---|
2716 | CbcSimpleInteger * obj = |
---|
2717 | dynamic_cast <CbcSimpleInteger *>(object) ; |
---|
2718 | if (obj) { |
---|
2719 | branch_=obj->createBranch(solver,&usefulInfo,preferredWay); |
---|
2720 | } else { |
---|
2721 | CbcObject * obj = |
---|
2722 | dynamic_cast <CbcObject *>(object) ; |
---|
2723 | assert (obj); |
---|
2724 | branch_=obj->createBranch(preferredWay); |
---|
2725 | } |
---|
2726 | { |
---|
2727 | CbcBranchingObject * branchObj = |
---|
2728 | dynamic_cast <CbcBranchingObject *>(branch_) ; |
---|
2729 | assert (branchObj); |
---|
2730 | branchObj->way(preferredWay); |
---|
2731 | } |
---|
2732 | delete ws; |
---|
2733 | ws=NULL; |
---|
2734 | break; |
---|
2735 | } else { |
---|
2736 | // say do fast |
---|
2737 | int easy=1; |
---|
2738 | if (!skipAll) |
---|
2739 | solver->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo,&easy) ; |
---|
2740 | int iDo; |
---|
2741 | #ifdef RANGING |
---|
2742 | if ((skipAll&&numberBeforeTrust&&saveSearchStrategy<20)||saveSearchStrategy<10) |
---|
2743 | numberPenalties=0; |
---|
2744 | { |
---|
2745 | // off penalties if too much |
---|
2746 | double needed = neededPenalties; |
---|
2747 | needed *= numberRows; |
---|
2748 | if (needed>1.0e6&&numberNodes&&saveSearchStrategy<20) { |
---|
2749 | numberPenalties=0; |
---|
2750 | neededPenalties=0; |
---|
2751 | } |
---|
2752 | } |
---|
2753 | # ifdef COIN_HAS_CLP |
---|
2754 | if (osiclp&&numberPenalties&&neededPenalties) { |
---|
2755 | xPen += neededPenalties; |
---|
2756 | which--; |
---|
2757 | which[0]=neededPenalties; |
---|
2758 | osiclp->passInRanges(which); |
---|
2759 | // Mark hot start and get ranges |
---|
2760 | if (kPass) { |
---|
2761 | // until can work out why solution can go funny |
---|
2762 | int save = osiclp->specialOptions(); |
---|
2763 | osiclp->setSpecialOptions(save|256); |
---|
2764 | solver->markHotStart(); |
---|
2765 | osiclp->setSpecialOptions(save); |
---|
2766 | } else { |
---|
2767 | solver->markHotStart(); |
---|
2768 | } |
---|
2769 | assert (auxiliaryInfo->warmStart()); |
---|
2770 | doneHotStart=true; |
---|
2771 | xMark++; |
---|
2772 | kPass++; |
---|
2773 | osiclp->passInRanges(NULL); |
---|
2774 | const double * downCost=osiclp->upRange(); |
---|
2775 | const double * upCost=osiclp->downRange(); |
---|
2776 | //printf("numberTodo %d needed %d numberpenalties %d\n",numberToDo,neededPenalties,numberPenalties); |
---|
2777 | double invTrust = 1.0/((double) numberBeforeTrust); |
---|
2778 | for (int i=0;i<neededPenalties;i++) { |
---|
2779 | int j = objectMark[i]; |
---|
2780 | int iObject = whichObject[j]; |
---|
2781 | OsiObject * object = model->modifiableObject(iObject); |
---|
2782 | CbcSimpleIntegerDynamicPseudoCost * dynamicObject = |
---|
2783 | dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ; |
---|
2784 | int iSequence=dynamicObject->columnNumber(); |
---|
2785 | double value = saveSolution[iSequence]; |
---|
2786 | value -= floor(value); |
---|
2787 | double upPenalty = CoinMin(upCost[i],1.0e110)*(1.0-value); |
---|
2788 | double downPenalty = CoinMin(downCost[i],1.0e110)*value; |
---|
2789 | if (!numberBeforeTrust) { |
---|
2790 | // override |
---|
2791 | downEstimate[iObject]=downPenalty; |
---|
2792 | upEstimate[iObject]=upPenalty; |
---|
2793 | } else { |
---|
2794 | int numberThisDown = dynamicObject->numberTimesDown(); |
---|
2795 | if (numberThisDown<numberBeforeTrust) { |
---|
2796 | double fraction = ((double) numberThisDown)*invTrust; |
---|
2797 | downEstimate[iObject] = fraction*downEstimate[iObject]+(1.0-fraction)*downPenalty; |
---|
2798 | } |
---|
2799 | int numberThisUp = dynamicObject->numberTimesUp(); |
---|
2800 | if (numberThisUp<numberBeforeTrust) { |
---|
2801 | double fraction = ((double) numberThisUp)*invTrust; |
---|
2802 | upEstimate[iObject] = fraction*upEstimate[iObject]+(1.0-fraction)*upPenalty; |
---|
2803 | } |
---|
2804 | } |
---|
2805 | sort[j] = - CoinMin(downEstimate[iObject],upEstimate[iObject]); |
---|
2806 | #ifdef CBC_WEAK_STRONG |
---|
2807 | sort[j] -= 1.0e10; // make more likely to be chosen |
---|
2808 | #endif |
---|
2809 | //if ((numberNodes%PRINT_STUFF)==0&&PRINT_STUFF>0) |
---|
2810 | if (!numberNodes) |
---|
2811 | printf("%d pen down ps %g -> %g up ps %g -> %g\n", |
---|
2812 | iObject,downCost[i],downPenalty,upCost[i],upPenalty); |
---|
2813 | } |
---|
2814 | } else |
---|
2815 | # endif /* COIN_HAS_CLP */ |
---|
2816 | { |
---|
2817 | if (!skipAll) { |
---|
2818 | // Mark hot start |
---|
2819 | solver->markHotStart(); |
---|
2820 | doneHotStart=true; |
---|
2821 | assert (auxiliaryInfo->warmStart()); |
---|
2822 | xMark++; |
---|
2823 | //if (solver->isProvenPrimalInfeasible()) |
---|
2824 | //printf("**** Hot start says node infeasible\n"); |
---|
2825 | } |
---|
2826 | // make sure best will be first |
---|
2827 | if (iBestGot>=0) |
---|
2828 | sort[iBestGot]=-1.0e120; |
---|
2829 | } |
---|
2830 | #else /* RANGING */ |
---|
2831 | if (!skipAll) { |
---|
2832 | // Mark hot start |
---|
2833 | doneHotStart=true; |
---|
2834 | assert (auxiliaryInfo->warmStart()); |
---|
2835 | solver->markHotStart(); |
---|
2836 | xMark++; |
---|
2837 | } |
---|
2838 | // make sure best will be first |
---|
2839 | if (iBestGot>=0) |
---|
2840 | sort[iBestGot]=-COIN_DBL_MAX; |
---|
2841 | #endif /* RANGING */ |
---|
2842 | // Actions 0 - exit for repeat, 1 resolve and try old choice,2 exit for continue |
---|
2843 | #define ACTION 0 |
---|
2844 | #if ACTION<2 |
---|
2845 | if (anyAction) |
---|
2846 | numberToDo=0; // skip as we will be trying again |
---|
2847 | #endif |
---|
2848 | // Sort |
---|
2849 | CoinSort_2(sort,sort+numberToDo,whichObject); |
---|
2850 | // Change in objective opposite infeasible |
---|
2851 | double worstFeasible=0.0; |
---|
2852 | // Just first if strong off |
---|
2853 | if (!numberStrong) |
---|
2854 | numberToDo=CoinMin(numberToDo,1); |
---|
2855 | iDo=0; |
---|
2856 | int saveLimit2; |
---|
2857 | solver->getIntParam(OsiMaxNumIterationHotStart,saveLimit2); |
---|
2858 | bool doQuickly = false; // numberToDo>2*numberStrong; |
---|
2859 | if (searchStrategy==2) |
---|
2860 | doQuickly=true; |
---|
2861 | //printf("todo %d, strong %d\n",numberToDo,numberStrong); |
---|
2862 | int numberTest=numberNotTrusted>0 ? numberStrong : (numberStrong+1)/2; |
---|
2863 | int numberTest2 = 2*numberStrong; |
---|
2864 | double distanceToCutoff2 = model->getCutoff()-objectiveValue_; |
---|
2865 | if (!newWay) { |
---|
2866 | if (searchStrategy==3) { |
---|
2867 | // Previously decided we need strong |
---|
2868 | doQuickly=false; |
---|
2869 | numberTest = numberStrong; |
---|
2870 | //numberTest2 = 1000000; |
---|
2871 | } |
---|
2872 | if (searchStrategy<0||searchStrategy==1) |
---|
2873 | //numberTest2 = 1000000; |
---|
2874 | #if 0 |
---|
2875 | if (numberBeforeTrust>20&&(numberNodes>20000||(numberNodes>200&&numberNotTrusted==0))) { |
---|
2876 | if ((numberNodes%20)!=0) { |
---|
2877 | numberTest=0; |
---|
2878 | doQuickly=true; |
---|
2879 | } |
---|
2880 | } |
---|
2881 | #else |
---|
2882 | // Try nearly always off |
---|
2883 | if (searchStrategy<2) { |
---|
2884 | if ((numberNodes%20)!=0) { |
---|
2885 | if ((model->specialOptions()&8)==0) { |
---|
2886 | numberTest=0; |
---|
2887 | doQuickly=true; |
---|
2888 | } |
---|
2889 | } else { |
---|
2890 | doQuickly=false; |
---|
2891 | numberTest=2*numberStrong; |
---|
2892 | skipAll=false; |
---|
2893 | } |
---|
2894 | } else if (searchStrategy!=3) { |
---|
2895 | doQuickly=true; |
---|
2896 | numberTest=numberStrong; |
---|
2897 | } |
---|
2898 | #endif |
---|
2899 | if (depth_<8&&numberStrong) { |
---|
2900 | if (searchStrategy!=2) { |
---|
2901 | doQuickly=false; |
---|
2902 | int numberRows = solver->getNumRows(); |
---|
2903 | // whether to do this or not is important - think |
---|
2904 | if (numberRows<300||numberRows+numberColumns<2500) { |
---|
2905 | if (depth_<7) |
---|
2906 | numberStrong = CoinMin(3*numberStrong,numberToDo); |
---|
2907 | if (!depth_) |
---|
2908 | numberStrong=CoinMin(6*numberStrong,numberToDo); |
---|
2909 | } |
---|
2910 | numberTest=numberStrong; |
---|
2911 | skipAll=false; |
---|
2912 | } |
---|
2913 | model->setStateOfSearch(2); // use min min |
---|
2914 | } |
---|
2915 | // could adjust using average iterations per branch |
---|
2916 | // double average = ((double)model->getIterationCount())/ |
---|
2917 | //((double) model->getNodeCount()+1.0); |
---|
2918 | // if too many and big then just do 10 its |
---|
2919 | if (!skipAll&&saveStateOfSearch) { |
---|
2920 | //if (numberNotTrusted>3*numberStrong&&numberRows>250&&numberColumns>1000&&saveLimit==100) |
---|
2921 | // off solver->setIntParam(OsiMaxNumIterationHotStart,10); |
---|
2922 | } |
---|
2923 | // make negative for test |
---|
2924 | distanceToCutoff = - distanceToCutoff; |
---|
2925 | if (numberObjects>-100) { |
---|
2926 | // larger |
---|
2927 | distanceToCutoff *= 100.0; |
---|
2928 | } |
---|
2929 | distanceToCutoff = -COIN_DBL_MAX; |
---|
2930 | // Do at least 5 strong |
---|
2931 | if (numberColumns<1000&&(depth_<15||numberNodes<1000000)) |
---|
2932 | numberTest = CoinMax(numberTest,5); |
---|
2933 | if ((model->specialOptions()&8)==0) { |
---|
2934 | if (skipAll) { |
---|
2935 | numberTest=0; |
---|
2936 | doQuickly=true; |
---|
2937 | } |
---|
2938 | } else { |
---|
2939 | // do 5 as strong is fixing |
---|
2940 | numberTest = CoinMax(numberTest,5); |
---|
2941 | } |
---|
2942 | } else { |
---|
2943 | int numberTest=numberNotTrusted>0 ? numberStrong : (numberStrong+1)/2; |
---|
2944 | int numberTest2 = 2*numberStrong; |
---|
2945 | if (searchStrategy>=3) { |
---|
2946 | // Previously decided we need strong |
---|
2947 | doQuickly=false; |
---|
2948 | if (depth_<7) |
---|
2949 | numberStrong *=3; |
---|
2950 | if (!depth_) |
---|
2951 | numberStrong=CoinMin(6*numberStrong,numberToDo); |
---|
2952 | numberTest = numberStrong; |
---|
2953 | numberTest2 *= 2; |
---|
2954 | } else if (searchStrategy==2||(searchStrategy==1&&depth_<6)) { |
---|
2955 | numberStrong *=2; |
---|
2956 | if (!depth_) |
---|
2957 | numberStrong=CoinMin(2*numberStrong,numberToDo); |
---|
2958 | numberTest = numberStrong; |
---|
2959 | } else if (searchStrategy==1&&numberNotTrusted) { |
---|
2960 | numberTest = numberStrong; |
---|
2961 | } else { |
---|
2962 | numberTest=0; |
---|
2963 | skipAll=true; |
---|
2964 | } |
---|
2965 | distanceToCutoff=model->getCutoff()-objectiveValue_; |
---|
2966 | // make negative for test |
---|
2967 | distanceToCutoff = - distanceToCutoff; |
---|
2968 | if (numberObjects>-100) { |
---|
2969 | // larger |
---|
2970 | distanceToCutoff *= 100.0; |
---|
2971 | } |
---|
2972 | distanceToCutoff = -COIN_DBL_MAX; |
---|
2973 | if (skipAll) { |
---|
2974 | numberTest=0; |
---|
2975 | doQuickly=true; |
---|
2976 | } |
---|
2977 | } |
---|
2978 | #if 0 |
---|
2979 | // temp - always switch off |
---|
2980 | if (0) { |
---|
2981 | int numberIterations = model->getIterationCount(); |
---|
2982 | int numberStrongIterations = model->numberStrongIterations(); |
---|
2983 | if (numberStrongIterations>numberIterations+10000&&depth_>=5) { |
---|
2984 | skipAll=true; |
---|
2985 | newWay=false; |
---|
2986 | numberTest=0; |
---|
2987 | doQuickly=true; |
---|
2988 | } |
---|
2989 | } |
---|
2990 | // temp - always switch on |
---|
2991 | if (0) { |
---|
2992 | int numberIterations = model->getIterationCount(); |
---|
2993 | int numberStrongIterations = model->numberStrongIterations(); |
---|
2994 | if (2*numberStrongIterations<numberIterations||depth_<=5) { |
---|
2995 | skipAll=false; |
---|
2996 | newWay=false; |
---|
2997 | numberTest=CoinMax(numberTest,numberStrong); |
---|
2998 | doQuickly=false; |
---|
2999 | } |
---|
3000 | } |
---|
3001 | #endif |
---|
3002 | px[0]=numberTest; |
---|
3003 | px[1]=numberTest2; |
---|
3004 | px[2]= doQuickly ? 1 : -1; |
---|
3005 | px[3]=numberStrong; |
---|
3006 | if (!newWay) { |
---|
3007 | if (numberColumns>8*solver->getNumRows()&&false) { |
---|
3008 | printf("skipAll %c doQuickly %c numberTest %d numberTest2 %d numberNot %d\n", |
---|
3009 | skipAll ? 'Y' : 'N',doQuickly ? 'Y' : 'N',numberTest,numberTest2,numberNotTrusted); |
---|
3010 | numberTest = CoinMin(numberTest,model->numberStrong()); |
---|
3011 | numberTest2 = CoinMin(numberTest2,model->numberStrong()); |
---|
3012 | printf("new test,test2 %d %d\n",numberTest,numberTest2); |
---|
3013 | } |
---|
3014 | } |
---|
3015 | //printf("skipAll %c doQuickly %c numberTest %d numberTest2 %d numberNot %d\n", |
---|
3016 | // skipAll ? 'Y' : 'N',doQuickly ? 'Y' : 'N',numberTest,numberTest2,numberNotTrusted); |
---|
3017 | // See if we want mini tree |
---|
3018 | bool wantMiniTree=false; |
---|
3019 | if (model->sizeMiniTree()&&depth_>7&&saveStateOfSearch>0) |
---|
3020 | wantMiniTree=true; |
---|
3021 | numberMini=0; |
---|
3022 | //if (skipAll&&numberTest==0&&doQuickly) |
---|
3023 | //numberToDo = 1; // trust previous stuff |
---|
3024 | bool couldChooseFirst = false ; //(skipAll&&numberTest==0&&doQuickly); |
---|
3025 | //skipAll=false; |
---|
3026 | for ( iDo=0;iDo<numberToDo;iDo++) { |
---|
3027 | CbcStrongInfo choice; |
---|
3028 | int iObject = whichObject[iDo]; |
---|
3029 | OsiObject * object = model->modifiableObject(iObject); |
---|
3030 | CbcSimpleIntegerDynamicPseudoCost * dynamicObject = |
---|
3031 | dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ; |
---|
3032 | int iColumn = dynamicObject->columnNumber(); |
---|
3033 | int preferredWay; |
---|
3034 | double infeasibility = object->infeasibility(&usefulInfo,preferredWay); |
---|
3035 | // may have become feasible |
---|
3036 | if (!infeasibility) |
---|
3037 | continue; |
---|
3038 | CbcSimpleInteger * obj = |
---|
3039 | dynamic_cast <CbcSimpleInteger *>(object) ; |
---|
3040 | if (obj) { |
---|
3041 | choice.possibleBranch=obj->createBranch(solver,&usefulInfo,preferredWay); |
---|
3042 | } else { |
---|
3043 | CbcObject * obj = |
---|
3044 | dynamic_cast <CbcObject *>(object) ; |
---|
3045 | assert (obj); |
---|
3046 | choice.possibleBranch=obj->createBranch(preferredWay); |
---|
3047 | } |
---|
3048 | // Save which object it was |
---|
3049 | choice.objectNumber=iObject; |
---|
3050 | choice.numIntInfeasUp = numberUnsatisfied_; |
---|
3051 | choice.numIntInfeasDown = numberUnsatisfied_; |
---|
3052 | choice.upMovement = upEstimate[iObject]; |
---|
3053 | choice.downMovement = downEstimate[iObject]; |
---|
3054 | assert (choice.upMovement>=0.0); |
---|
3055 | assert (choice.downMovement>=0.0); |
---|
3056 | choice.fix=0; // say not fixed |
---|
3057 | double maxChange = 0.5*(choice.upMovement+choice.downMovement); |
---|
3058 | maxChange = CoinMin(choice.upMovement,choice.downMovement); |
---|
3059 | maxChange = CoinMax(choice.upMovement,choice.downMovement); |
---|
3060 | if (searchStrategy==2) |
---|
3061 | maxChange = COIN_DBL_MAX; |
---|
3062 | //maxChange *= 5.0; |
---|
3063 | if (dynamicObject->method()==1) |
---|
3064 | maxChange *= 0.1; // probing |
---|
3065 | // see if can skip strong branching |
---|
3066 | int canSkip = choice.possibleBranch->fillStrongInfo(choice); |
---|
3067 | if (!newWay) { |
---|
3068 | if ((maxChange>distanceToCutoff2)&&(!doQuickly||(numberTest>0&&searchStrategy!=2))) |
---|
3069 | canSkip=0; |
---|
3070 | } else { |
---|
3071 | if (skipAll) |
---|
3072 | canSkip=1; |
---|
3073 | else if (numberTest>0&&searchStrategy>=3) |
---|
3074 | canSkip=0; |
---|
3075 | } |
---|
3076 | if (!numberBeforeTrust) { |
---|
3077 | canSkip=1; |
---|
3078 | } |
---|
3079 | if (sort[iDo]<distanceToCutoff) |
---|
3080 | canSkip=0; |
---|
3081 | if (((numberTest2<=0&&numberTest<=0)||skipAll)&&sort[iDo]>distanceToCutoff) { |
---|
3082 | canSkip=1; // always skip |
---|
3083 | if (iDo>20) { |
---|
3084 | delete choice.possibleBranch; |
---|
3085 | choice.possibleBranch=NULL; |
---|
3086 | break; // give up anyway |
---|
3087 | } |
---|
3088 | } |
---|
3089 | if (model->messageHandler()->logLevel()>3&&numberBeforeTrust) |
---|
3090 | dynamicObject->print(1,choice.possibleBranch->value()); |
---|
3091 | // was if (!canSkip) |
---|
3092 | if (newWay) |
---|
3093 | numberTest2--; |
---|
3094 | if (!canSkip) { |
---|
3095 | //#ifndef RANGING |
---|
3096 | if (!doneHotStart) { |
---|
3097 | // Mark hot start |
---|
3098 | doneHotStart=true; |
---|
3099 | assert (auxiliaryInfo->warmStart()); |
---|
3100 | solver->markHotStart(); |
---|
3101 | xMark++; |
---|
3102 | } |
---|
3103 | //#endif |
---|
3104 | assert (!couldChooseFirst); |
---|
3105 | numberTest--; |
---|
3106 | if (!newWay) |
---|
3107 | numberTest2--; |
---|
3108 | // just do a few |
---|
3109 | //if (canSkip) |
---|
3110 | //solver->setIntParam(OsiMaxNumIterationHotStart,10); |
---|
3111 | double objectiveChange ; |
---|
3112 | double newObjectiveValue=1.0e100; |
---|
3113 | int j; |
---|
3114 | // status is 0 finished, 1 infeasible and other |
---|
3115 | int iStatus; |
---|
3116 | if (0) { |
---|
3117 | CbcDynamicPseudoCostBranchingObject * cbcobj = dynamic_cast<CbcDynamicPseudoCostBranchingObject *> (choice.possibleBranch); |
---|
3118 | if (cbcobj) { |
---|
3119 | CbcSimpleIntegerDynamicPseudoCost * object = cbcobj->object(); |
---|
3120 | printf("strong %d ",iDo); |
---|
3121 | object->print(1,0.5); |
---|
3122 | } |
---|
3123 | } |
---|
3124 | /* |
---|
3125 | Try the down direction first. (Specify the initial branching alternative as |
---|
3126 | down with a call to way(-1). Each subsequent call to branch() performs the |
---|
3127 | specified branch and advances the branch object state to the next branch |
---|
3128 | alternative.) |
---|
3129 | */ |
---|
3130 | choice.possibleBranch->way(-1) ; |
---|
3131 | #if NEW_UPDATE_OBJECT==0 |
---|
3132 | decision->saveBranchingObject( choice.possibleBranch); |
---|
3133 | #endif |
---|
3134 | choice.possibleBranch->branch() ; |
---|
3135 | solver->solveFromHotStart() ; |
---|
3136 | bool needHotStartUpdate=false; |
---|
3137 | numberStrongDone++; |
---|
3138 | numberStrongIterations += solver->getIterationCount(); |
---|
3139 | /* |
---|
3140 | We now have an estimate of objective degradation that we can use for strong |
---|
3141 | branching. If we're over the cutoff, the variable is monotone up. |
---|
3142 | If we actually made it to optimality, check for a solution, and if we have |
---|
3143 | a good one, call setBestSolution to process it. Note that this may reduce the |
---|
3144 | cutoff, so we check again to see if we can declare this variable monotone. |
---|
3145 | */ |
---|
3146 | if (solver->isProvenOptimal()) |
---|
3147 | iStatus=0; // optimal |
---|
3148 | else if (solver->isIterationLimitReached() |
---|
3149 | &&!solver->isDualObjectiveLimitReached()) |
---|
3150 | iStatus=2; // unknown |
---|
3151 | else |
---|
3152 | iStatus=1; // infeasible |
---|
3153 | newObjectiveValue = solver->getObjSense()*solver->getObjValue(); |
---|
3154 | choice.numItersDown = solver->getIterationCount(); |
---|
3155 | objectiveChange = CoinMax(newObjectiveValue - objectiveValue_,0.0); |
---|
3156 | // Update branching information if wanted |
---|
3157 | #if NEW_UPDATE_OBJECT==0 |
---|
3158 | decision->updateInformation( solver,this); |
---|
3159 | #elif NEW_UPDATE_OBJECT<2 |
---|
3160 | CbcBranchingObject * cbcobj = dynamic_cast<CbcBranchingObject *> (choice.possibleBranch); |
---|
3161 | if (cbcobj) { |
---|
3162 | CbcObject * object = cbcobj->object(); |
---|
3163 | CbcObjectUpdateData update = object->createUpdateInformation(solver,this,cbcobj); |
---|
3164 | object->updateInformation(update); |
---|
3165 | } else { |
---|
3166 | decision->updateInformation( solver,this); |
---|
3167 | } |
---|
3168 | #else |
---|
3169 | CbcBranchingObject * cbcobj = dynamic_cast<CbcBranchingObject *> (choice.possibleBranch); |
---|
3170 | if (cbcobj) { |
---|
3171 | CbcObject * object = cbcobj->object(); |
---|
3172 | CbcObjectUpdateData update = object->createUpdateInformation(solver,this,cbcobj); |
---|
3173 | update.objectNumber_ = choice.objectNumber; |
---|
3174 | model->addUpdateInformation(update); |
---|
3175 | } else { |
---|
3176 | decision->updateInformation( solver,this); |
---|
3177 | } |
---|
3178 | #endif |
---|
3179 | if (!iStatus) { |
---|
3180 | choice.finishedDown = true ; |
---|
3181 | if (newObjectiveValue>=cutoff) { |
---|
3182 | objectiveChange = 1.0e100; // say infeasible |
---|
3183 | numberStrongInfeasible++; |
---|
3184 | } else { |
---|
3185 | // See if integer solution |
---|
3186 | if (model->feasibleSolution(choice.numIntInfeasDown, |
---|
3187 | choice.numObjInfeasDown) |
---|
3188 | &&model->problemFeasibility()->feasible(model,-1)>=0) { |
---|
3189 | if (auxiliaryInfo->solutionAddsCuts()) { |
---|
3190 | needHotStartUpdate=true; |
---|
3191 | solver->unmarkHotStart(); |
---|
3192 | } |
---|
3193 | model->setBestSolution(CBC_STRONGSOL, |
---|
3194 | newObjectiveValue, |
---|
3195 | solver->getColSolution()) ; |
---|
3196 | if (needHotStartUpdate) { |
---|
3197 | solver->resolve(); |
---|
3198 | newObjectiveValue = solver->getObjSense()*solver->getObjValue(); |
---|
3199 | objectiveChange = CoinMax(newObjectiveValue - objectiveValue_,0.0); |
---|
3200 | model->feasibleSolution(choice.numIntInfeasDown, |
---|
3201 | choice.numObjInfeasDown); |
---|
3202 | } |
---|
3203 | model->setLastHeuristic(NULL); |
---|
3204 | model->incrementUsed(solver->getColSolution()); |
---|
3205 | cutoff =model->getCutoff(); |
---|
3206 | if (newObjectiveValue >= cutoff) { // *new* cutoff |
---|
3207 | objectiveChange = 1.0e100 ; |
---|
3208 | numberStrongInfeasible++; |
---|
3209 | } |
---|
3210 | } |
---|
3211 | } |
---|
3212 | } else if (iStatus==1) { |
---|
3213 | objectiveChange = 1.0e100 ; |
---|
3214 | numberStrongInfeasible++; |
---|
3215 | } else { |
---|
3216 | // Can't say much as we did not finish |
---|
3217 | choice.finishedDown = false ; |
---|
3218 | numberUnfinished++; |
---|
3219 | } |
---|
3220 | choice.downMovement = objectiveChange ; |
---|
3221 | |
---|
3222 | // restore bounds |
---|
3223 | for ( j=0;j<numberColumns;j++) { |
---|
3224 | if (saveLower[j] != lower[j]) |
---|
3225 | solver->setColLower(j,saveLower[j]); |
---|
3226 | if (saveUpper[j] != upper[j]) |
---|
3227 | solver->setColUpper(j,saveUpper[j]); |
---|
3228 | } |
---|
3229 | if(needHotStartUpdate) { |
---|
3230 | needHotStartUpdate = false; |
---|
3231 | solver->resolve(); |
---|
3232 | //we may again have an integer feasible solution |
---|
3233 | int numberIntegerInfeasibilities; |
---|
3234 | int numberObjectInfeasibilities; |
---|
3235 | if (model->feasibleSolution( |
---|
3236 | numberIntegerInfeasibilities, |
---|
3237 | numberObjectInfeasibilities)) { |
---|
3238 | #ifdef BONMIN |
---|
3239 | //In this case node has become integer feasible, let us exit the loop |
---|
3240 | std::cout<<"Node has become integer feasible"<<std::endl; |
---|
3241 | numberUnsatisfied_ = 0; |
---|
3242 | break; |
---|
3243 | #endif |
---|
3244 | double objValue = solver->getObjValue(); |
---|
3245 | model->setBestSolution(CBC_STRONGSOL, |
---|
3246 | objValue, |
---|
3247 | solver->getColSolution()) ; |
---|
3248 | solver->resolve(); |
---|
3249 | cutoff =model->getCutoff(); |
---|
3250 | } |
---|
3251 | solver->markHotStart(); |
---|
3252 | } |
---|
3253 | //printf("Down on %d, status is %d, obj %g its %d cost %g finished %d inf %d infobj %d\n", |
---|
3254 | //printf("Down on %d, status is %d, obj %g its %d cost %g finished %d inf %d infobj %d\n", |
---|
3255 | // choice.objectNumber,iStatus,newObjectiveValue,choice.numItersDown, |
---|
3256 | // choice.downMovement,choice.finishedDown,choice.numIntInfeasDown, |
---|
3257 | // choice.numObjInfeasDown); |
---|
3258 | |
---|
3259 | // repeat the whole exercise, forcing the variable up |
---|
3260 | #if NEW_UPDATE_OBJECT==0 |
---|
3261 | decision->saveBranchingObject( choice.possibleBranch); |
---|
3262 | #endif |
---|
3263 | choice.possibleBranch->branch(); |
---|
3264 | solver->solveFromHotStart() ; |
---|
3265 | numberStrongDone++; |
---|
3266 | numberStrongIterations += solver->getIterationCount(); |
---|
3267 | /* |
---|
3268 | We now have an estimate of objective degradation that we can use for strong |
---|
3269 | branching. If we're over the cutoff, the variable is monotone up. |
---|
3270 | If we actually made it to optimality, check for a solution, and if we have |
---|
3271 | a good one, call setBestSolution to process it. Note that this may reduce the |
---|
3272 | cutoff, so we check again to see if we can declare this variable monotone. |
---|
3273 | */ |
---|
3274 | if (solver->isProvenOptimal()) |
---|
3275 | iStatus=0; // optimal |
---|
3276 | else if (solver->isIterationLimitReached() |
---|
3277 | &&!solver->isDualObjectiveLimitReached()) |
---|
3278 | iStatus=2; // unknown |
---|
3279 | else |
---|
3280 | iStatus=1; // infeasible |
---|
3281 | newObjectiveValue = solver->getObjSense()*solver->getObjValue(); |
---|
3282 | choice.numItersUp = solver->getIterationCount(); |
---|
3283 | objectiveChange = CoinMax(newObjectiveValue - objectiveValue_,0.0); |
---|
3284 | // Update branching information if wanted |
---|
3285 | #if NEW_UPDATE_OBJECT==0 |
---|
3286 | decision->updateInformation( solver,this); |
---|
3287 | #elif NEW_UPDATE_OBJECT<2 |
---|
3288 | cbcobj = dynamic_cast<CbcBranchingObject *> (choice.possibleBranch); |
---|
3289 | if (cbcobj) { |
---|
3290 | CbcObject * object = cbcobj->object(); |
---|
3291 | CbcObjectUpdateData update = object->createUpdateInformation(solver,this,cbcobj); |
---|
3292 | object->updateInformation(update); |
---|
3293 | } else { |
---|
3294 | decision->updateInformation( solver,this); |
---|
3295 | } |
---|
3296 | #else |
---|
3297 | cbcobj = dynamic_cast<CbcBranchingObject *> (choice.possibleBranch); |
---|
3298 | if (cbcobj) { |
---|
3299 | CbcObject * object = cbcobj->object(); |
---|
3300 | CbcObjectUpdateData update = object->createUpdateInformation(solver,this,cbcobj); |
---|
3301 | update.objectNumber_ = choice.objectNumber; |
---|
3302 | model->addUpdateInformation(update); |
---|
3303 | } else { |
---|
3304 | decision->updateInformation( solver,this); |
---|
3305 | } |
---|
3306 | #endif |
---|
3307 | if (!iStatus) { |
---|
3308 | choice.finishedUp = true ; |
---|
3309 | if (newObjectiveValue>=cutoff) { |
---|
3310 | objectiveChange = 1.0e100; // say infeasible |
---|
3311 | numberStrongInfeasible++; |
---|
3312 | } else { |
---|
3313 | // See if integer solution |
---|
3314 | if (model->feasibleSolution(choice.numIntInfeasUp, |
---|
3315 | choice.numObjInfeasUp) |
---|
3316 | &&model->problemFeasibility()->feasible(model,-1)>=0) { |
---|
3317 | #ifdef BONMIN |
---|
3318 | std::cout<<"Node has become integer feasible"<<std::endl; |
---|
3319 | numberUnsatisfied_ = 0; |
---|
3320 | break; |
---|
3321 | #endif |
---|
3322 | if (auxiliaryInfo->solutionAddsCuts()) { |
---|
3323 | needHotStartUpdate=true; |
---|
3324 | solver->unmarkHotStart(); |
---|
3325 | } |
---|
3326 | model->setBestSolution(CBC_STRONGSOL, |
---|
3327 | newObjectiveValue, |
---|
3328 | solver->getColSolution()) ; |
---|
3329 | if (needHotStartUpdate) { |
---|
3330 | solver->resolve(); |
---|
3331 | newObjectiveValue = solver->getObjSense()*solver->getObjValue(); |
---|
3332 | objectiveChange = CoinMax(newObjectiveValue - objectiveValue_,0.0); |
---|
3333 | model->feasibleSolution(choice.numIntInfeasDown, |
---|
3334 | choice.numObjInfeasDown); |
---|
3335 | } |
---|
3336 | model->setLastHeuristic(NULL); |
---|
3337 | model->incrementUsed(solver->getColSolution()); |
---|
3338 | cutoff =model->getCutoff(); |
---|
3339 | if (newObjectiveValue >= cutoff) { // *new* cutoff |
---|
3340 | objectiveChange = 1.0e100 ; |
---|
3341 | numberStrongInfeasible++; |
---|
3342 | } |
---|
3343 | } |
---|
3344 | } |
---|
3345 | } else if (iStatus==1) { |
---|
3346 | objectiveChange = 1.0e100 ; |
---|
3347 | numberStrongInfeasible++; |
---|
3348 | } else { |
---|
3349 | // Can't say much as we did not finish |
---|
3350 | choice.finishedUp = false ; |
---|
3351 | numberUnfinished++; |
---|
3352 | } |
---|
3353 | choice.upMovement = objectiveChange ; |
---|
3354 | |
---|
3355 | // restore bounds |
---|
3356 | for ( j=0;j<numberColumns;j++) { |
---|
3357 | if (saveLower[j] != lower[j]) |
---|
3358 | solver->setColLower(j,saveLower[j]); |
---|
3359 | if (saveUpper[j] != upper[j]) |
---|
3360 | solver->setColUpper(j,saveUpper[j]); |
---|
3361 | } |
---|
3362 | if(needHotStartUpdate) { |
---|
3363 | needHotStartUpdate = false; |
---|
3364 | solver->resolve(); |
---|
3365 | //we may again have an integer feasible solution |
---|
3366 | int numberIntegerInfeasibilities; |
---|
3367 | int numberObjectInfeasibilities; |
---|
3368 | if (model->feasibleSolution( |
---|
3369 | numberIntegerInfeasibilities, |
---|
3370 | numberObjectInfeasibilities)) { |
---|
3371 | double objValue = solver->getObjValue(); |
---|
3372 | model->setBestSolution(CBC_STRONGSOL, |
---|
3373 | objValue, |
---|
3374 | solver->getColSolution()) ; |
---|
3375 | solver->resolve(); |
---|
3376 | cutoff =model->getCutoff(); |
---|
3377 | } |
---|
3378 | solver->markHotStart(); |
---|
3379 | } |
---|
3380 | |
---|
3381 | //printf("Up on %d, status is %d, obj %g its %d cost %g finished %d inf %d infobj %d\n", |
---|
3382 | // choice.objectNumber,iStatus,newObjectiveValue,choice.numItersUp, |
---|
3383 | // choice.upMovement,choice.finishedUp,choice.numIntInfeasUp, |
---|
3384 | // choice.numObjInfeasUp); |
---|
3385 | } |
---|
3386 | |
---|
3387 | solver->setIntParam(OsiMaxNumIterationHotStart,saveLimit2); |
---|
3388 | /* |
---|
3389 | End of evaluation for this candidate variable. Possibilities are: |
---|
3390 | * Both sides below cutoff; this variable is a candidate for branching. |
---|
3391 | * Both sides infeasible or above the objective cutoff: no further action |
---|
3392 | here. Break from the evaluation loop and assume the node will be purged |
---|
3393 | by the caller. |
---|
3394 | * One side below cutoff: Install the branch (i.e., fix the variable). Break |
---|
3395 | from the evaluation loop and assume the node will be reoptimised by the |
---|
3396 | caller. |
---|
3397 | */ |
---|
3398 | // reset |
---|
3399 | choice.possibleBranch->resetNumberBranchesLeft(); |
---|
3400 | if (choice.upMovement<1.0e100) { |
---|
3401 | if(choice.downMovement<1.0e100) { |
---|
3402 | // In case solution coming in was odd |
---|
3403 | choice.upMovement = CoinMax(0.0,choice.upMovement); |
---|
3404 | choice.downMovement = CoinMax(0.0,choice.downMovement); |
---|
3405 | if (couldChooseFirst) |
---|
3406 | printf("candidate %d up %g down %g sort %g\n",iDo,choice.upMovement,choice.downMovement,sort[iDo]); |
---|
3407 | #if ZERO_ONE==2 |
---|
3408 | // branch on 0-1 first (temp) |
---|
3409 | if (fabs(choice.possibleBranch->value())<1.0) { |
---|
3410 | choice.upMovement *= ZERO_FAKE; |
---|
3411 | choice.downMovement *= ZERO_FAKE; |
---|
3412 | } |
---|
3413 | #endif |
---|
3414 | // feasible - see which best |
---|
3415 | if (!canSkip) { |
---|
3416 | if (iColumn==-46) { |
---|
3417 | printf("sort %g downest %g upest %g ",sort[iDo],downEstimate[iObject], |
---|
3418 | upEstimate[iObject]); |
---|
3419 | printf("downMove %g upMove %g value %g current pseudo %g %g\n", |
---|
3420 | choice.downMovement,choice.upMovement,choice.possibleBranch->value(), |
---|
3421 | dynamicObject->downDynamicPseudoCost(),dynamicObject->upDynamicPseudoCost()); |
---|
3422 | } |
---|
3423 | if (model->messageHandler()->logLevel()>3) |
---|
3424 | printf("sort %g downest %g upest %g ",sort[iDo],downEstimate[iObject], |
---|
3425 | upEstimate[iObject]); |
---|
3426 | model->messageHandler()->message(CBC_STRONG,*model->messagesPointer()) |
---|
3427 | << iObject << iColumn |
---|
3428 | <<choice.downMovement<<choice.numIntInfeasDown |
---|
3429 | <<choice.upMovement<<choice.numIntInfeasUp |
---|
3430 | <<choice.possibleBranch->value() |
---|
3431 | <<CoinMessageEol; |
---|
3432 | } |
---|
3433 | //if (!stateOfSearch) |
---|
3434 | //choice.numIntInfeasDown=99999; // temp fudge |
---|
3435 | if (wantMiniTree) |
---|
3436 | decision->setBestCriterion(-1.0); |
---|
3437 | double bestCriterion = -1.0; |
---|
3438 | //double gap = saveUpper[iColumn]-saveLower[iColumn]; |
---|
3439 | // Give precedence to ones with gap of 1.0 |
---|
3440 | //assert(gap>0.0); |
---|
3441 | double factor = 1.0; //changeFactor/CoinMin(gap,100.0); |
---|
3442 | int betterWay; |
---|
3443 | { |
---|
3444 | CbcBranchingObject * branchObj = |
---|
3445 | dynamic_cast <CbcBranchingObject *>(branch_) ; |
---|
3446 | if (branch_) |
---|
3447 | assert (branchObj); |
---|
3448 | betterWay = decision->betterBranch(choice.possibleBranch, |
---|
3449 | branchObj, |
---|
3450 | choice.upMovement*factor, |
---|
3451 | choice.numIntInfeasUp , |
---|
3452 | choice.downMovement*factor, |
---|
3453 | choice.numIntInfeasDown ); |
---|
3454 | } |
---|
3455 | if (wantMiniTree) { |
---|
3456 | double criterion = decision->getBestCriterion(); |
---|
3457 | sort[numberMini]=-criterion; |
---|
3458 | whichObject[numberMini++]=whichObject[iDo]; |
---|
3459 | assert (betterWay); |
---|
3460 | if (criterion>bestCriterion) |
---|
3461 | bestCriterion=criterion; |
---|
3462 | else |
---|
3463 | betterWay=0; |
---|
3464 | } |
---|
3465 | if (iDo>=changeStrategy) { |
---|
3466 | // make less likely |
---|
3467 | changeStrategy+=numberStrong; |
---|
3468 | changeFactor *= 0.9; |
---|
3469 | } |
---|
3470 | if (betterWay) { |
---|
3471 | delete branch_; |
---|
3472 | // C) create branching object |
---|
3473 | branch_ = choice.possibleBranch; |
---|
3474 | choice.possibleBranch=NULL; |
---|
3475 | { |
---|
3476 | CbcBranchingObject * branchObj = |
---|
3477 | dynamic_cast <CbcBranchingObject *>(branch_) ; |
---|
3478 | assert (branchObj); |
---|
3479 | //branchObj->way(preferredWay); |
---|
3480 | branchObj->way(betterWay); |
---|
3481 | } |
---|
3482 | if (couldChooseFirst) |
---|
3483 | printf("choosing %d way %d\n",iDo,betterWay); |
---|
3484 | bestChoice = choice.objectNumber; |
---|
3485 | whichChoice = iDo; |
---|
3486 | if (numberStrong<=1) { |
---|
3487 | delete ws; |
---|
3488 | ws=NULL; |
---|
3489 | break; |
---|
3490 | } |
---|
3491 | } else { |
---|
3492 | delete choice.possibleBranch; |
---|
3493 | choice.possibleBranch=NULL; |
---|
3494 | if (iDo>=2*numberStrong) { |
---|
3495 | delete ws; |
---|
3496 | ws=NULL; |
---|
3497 | break; |
---|
3498 | } |
---|
3499 | if (!dynamicObject||dynamicObject->numberTimesUp()>1) { |
---|
3500 | if (iDo-whichChoice>=numberStrong) { |
---|
3501 | delete choice.possibleBranch; |
---|
3502 | choice.possibleBranch=NULL; |
---|
3503 | break; // give up |
---|
3504 | } |
---|
3505 | } else { |
---|
3506 | if (iDo-whichChoice>=2*numberStrong) { |
---|
3507 | delete ws; |
---|
3508 | ws=NULL; |
---|
3509 | delete choice.possibleBranch; |
---|
3510 | choice.possibleBranch=NULL; |
---|
3511 | break; // give up |
---|
3512 | } |
---|
3513 | } |
---|
3514 | } |
---|
3515 | } else { |
---|
3516 | // up feasible, down infeasible |
---|
3517 | anyAction=-1; |
---|
3518 | worstFeasible = CoinMax(worstFeasible,choice.upMovement); |
---|
3519 | //printf("Down infeasible for choice %d sequence %d\n",i, |
---|
3520 | // model->object(choice.objectNumber)->columnNumber()); |
---|
3521 | if (!solveAll) { |
---|
3522 | choice.possibleBranch->way(1); |
---|
3523 | choice.possibleBranch->branch(); |
---|
3524 | delete choice.possibleBranch; |
---|
3525 | choice.possibleBranch=NULL; |
---|
3526 | delete ws; |
---|
3527 | ws=NULL; |
---|
3528 | break; |
---|
3529 | } else { |
---|
3530 | choice.fix=1; |
---|
3531 | fixObject[numberToFix++]=choice; |
---|
3532 | choice.possibleBranch=NULL; |
---|
3533 | #define FIXNOW |
---|
3534 | #ifdef FIXNOW |
---|
3535 | double value = ceil(saveSolution[iColumn]); |
---|
3536 | saveLower[iColumn]=value; |
---|
3537 | solver->setColLower(iColumn,value); |
---|
3538 | assert(doneHotStart); |
---|
3539 | solver->unmarkHotStart(); |
---|
3540 | solver->resolve(); |
---|
3541 | solver->markHotStart(); |
---|
3542 | // may be infeasible (if other way stopped on iterations) |
---|
3543 | if (!solver->isProvenOptimal()) { |
---|
3544 | // neither side feasible |
---|
3545 | anyAction=-2; |
---|
3546 | delete choice.possibleBranch; |
---|
3547 | choice.possibleBranch=NULL; |
---|
3548 | //printf("Both infeasible for choice %d sequence %d\n",i, |
---|
3549 | // model->object(choice.objectNumber)->columnNumber()); |
---|
3550 | delete ws; |
---|
3551 | ws=NULL; |
---|
3552 | break; |
---|
3553 | } |
---|
3554 | #endif |
---|
3555 | } |
---|
3556 | } |
---|
3557 | } else { |
---|
3558 | if(choice.downMovement<1.0e100) { |
---|
3559 | // down feasible, up infeasible |
---|
3560 | anyAction=-1; |
---|
3561 | worstFeasible = CoinMax(worstFeasible,choice.downMovement); |
---|
3562 | //printf("Up infeasible for choice %d sequence %d\n",i, |
---|
3563 | // model->object(choice.objectNumber)->columnNumber()); |
---|
3564 | if (!solveAll) { |
---|
3565 | choice.possibleBranch->way(-1); |
---|
3566 | choice.possibleBranch->branch(); |
---|
3567 | delete choice.possibleBranch; |
---|
3568 | choice.possibleBranch=NULL; |
---|
3569 | delete ws; |
---|
3570 | ws=NULL; |
---|
3571 | break; |
---|
3572 | } else { |
---|
3573 | choice.fix=-1; |
---|
3574 | fixObject[numberToFix++]=choice; |
---|
3575 | choice.possibleBranch=NULL; |
---|
3576 | #ifdef FIXNOW |
---|
3577 | double value = floor(saveSolution[iColumn]); |
---|
3578 | saveUpper[iColumn]=value; |
---|
3579 | solver->setColUpper(iColumn,value); |
---|
3580 | assert(doneHotStart); |
---|
3581 | solver->unmarkHotStart(); |
---|
3582 | solver->resolve(); |
---|
3583 | solver->markHotStart(); |
---|
3584 | // may be infeasible (if other way stopped on iterations) |
---|
3585 | if (!solver->isProvenOptimal()) { |
---|
3586 | // neither side feasible |
---|
3587 | anyAction=-2; |
---|
3588 | delete choice.possibleBranch; |
---|
3589 | choice.possibleBranch=NULL; |
---|
3590 | //printf("Both infeasible for choice %d sequence %d\n",i, |
---|
3591 | // model->object(choice.objectNumber)->columnNumber()); |
---|
3592 | delete ws; |
---|
3593 | ws=NULL; |
---|
3594 | break; |
---|
3595 | } |
---|
3596 | #endif |
---|
3597 | } |
---|
3598 | } else { |
---|
3599 | // neither side feasible |
---|
3600 | anyAction=-2; |
---|
3601 | delete choice.possibleBranch; |
---|
3602 | choice.possibleBranch=NULL; |
---|
3603 | //printf("Both infeasible for choice %d sequence %d\n",i, |
---|
3604 | // model->object(choice.objectNumber)->columnNumber()); |
---|
3605 | delete ws; |
---|
3606 | ws=NULL; |
---|
3607 | break; |
---|
3608 | } |
---|
3609 | } |
---|
3610 | // Check max time |
---|
3611 | hitMaxTime = ( CoinCpuTime()-model->getDblParam(CbcModel::CbcStartSeconds) > |
---|
3612 | model->getDblParam(CbcModel::CbcMaximumSeconds)); |
---|
3613 | if (hitMaxTime) { |
---|
3614 | // make sure rest are fast |
---|
3615 | doQuickly=true; |
---|
3616 | for ( int jDo=iDo+1;jDo<numberToDo;jDo++) { |
---|
3617 | int iObject = whichObject[iDo]; |
---|
3618 | OsiObject * object = model->modifiableObject(iObject); |
---|
3619 | CbcSimpleIntegerDynamicPseudoCost * dynamicObject = |
---|
3620 | dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ; |
---|
3621 | dynamicObject->setNumberBeforeTrust(0); |
---|
3622 | } |
---|
3623 | numberTest=0; |
---|
3624 | distanceToCutoff=-COIN_DBL_MAX; |
---|
3625 | } |
---|
3626 | delete choice.possibleBranch; |
---|
3627 | } |
---|
3628 | double averageChange = model->sumChangeObjective()/((double) model->getNodeCount()); |
---|
3629 | if (depth_<10||worstFeasible>0.2*averageChange) |
---|
3630 | solveAll=false; |
---|
3631 | if (model->messageHandler()->logLevel()>3||false) { |
---|
3632 | if (anyAction==-2) { |
---|
3633 | printf("infeasible\n"); |
---|
3634 | } else if(anyAction==-1) { |
---|
3635 | if (!solveAll) |
---|
3636 | printf("%d fixed\n",numberToFix); |
---|
3637 | else |
---|
3638 | printf("%d fixed AND choosing %d iDo %d iChosenWhen %d numberToDo %d\n",numberToFix,bestChoice, |
---|
3639 | iDo,whichChoice,numberToDo); |
---|
3640 | } else { |
---|
3641 | printf("choosing %d iDo %d iChosenWhen %d numberToDo %d\n",bestChoice, |
---|
3642 | iDo,whichChoice,numberToDo); |
---|
3643 | } |
---|
3644 | } |
---|
3645 | if (doneHotStart) { |
---|
3646 | // Delete the snapshot |
---|
3647 | solver->unmarkHotStart(); |
---|
3648 | // back to normal |
---|
3649 | solver->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo,NULL) ; |
---|
3650 | // restore basis |
---|
3651 | solver->setWarmStart(ws); |
---|
3652 | } |
---|
3653 | solver->setIntParam(OsiMaxNumIterationHotStart,saveLimit); |
---|
3654 | // Unless infeasible we will carry on |
---|
3655 | // But we could fix anyway |
---|
3656 | if (numberToFix&&!hitMaxTime) { |
---|
3657 | if (anyAction==-2) { |
---|
3658 | // take off |
---|
3659 | for (i = 0 ; i < numberToFix ; i++) { |
---|
3660 | delete fixObject[i].possibleBranch; |
---|
3661 | } |
---|
3662 | } else { |
---|
3663 | // apply and take off |
---|
3664 | for (i = 0 ; i < numberToFix ; i++) { |
---|
3665 | #ifndef FIXNOW |
---|
3666 | fixObject[i].possibleBranch->way(fixObject[i].fix) ; |
---|
3667 | fixObject[i].possibleBranch->branch() ; |
---|
3668 | #endif |
---|
3669 | delete fixObject[i].possibleBranch; |
---|
3670 | } |
---|
3671 | bool feasible=true; |
---|
3672 | #if ACTION <2 |
---|
3673 | if (solveAll) { |
---|
3674 | // can do quick optimality check |
---|
3675 | int easy=2; |
---|
3676 | solver->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo,&easy) ; |
---|
3677 | solver->resolve() ; |
---|
3678 | solver->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo,NULL) ; |
---|
3679 | feasible = solver->isProvenOptimal(); |
---|
3680 | if (feasible) { |
---|
3681 | anyAction=0; |
---|
3682 | numberMini=0; |
---|
3683 | memcpy(saveSolution,solver->getColSolution(),numberColumns*sizeof(double)); |
---|
3684 | model->reserveCurrentSolution(saveSolution); |
---|
3685 | memcpy(saveLower,solver->getColLower(),numberColumns*sizeof(double)); |
---|
3686 | memcpy(saveUpper,solver->getColUpper(),numberColumns*sizeof(double)); |
---|
3687 | model->setPointers(solver); |
---|
3688 | // See if candidate still possible |
---|
3689 | if (branch_) { |
---|
3690 | const OsiObject * object = model->object(bestChoice); |
---|
3691 | int preferredWay; |
---|
3692 | double infeasibility = object->infeasibility(&usefulInfo,preferredWay); |
---|
3693 | if (!infeasibility) { |
---|
3694 | // take out |
---|
3695 | delete branch_; |
---|
3696 | branch_=NULL; |
---|
3697 | } else { |
---|
3698 | CbcBranchingObject * branchObj = |
---|
3699 | dynamic_cast <CbcBranchingObject *>(branch_) ; |
---|
3700 | assert (branchObj); |
---|
3701 | branchObj->way(preferredWay); |
---|
3702 | } |
---|
3703 | } |
---|
3704 | } else { |
---|
3705 | anyAction=-2; |
---|
3706 | finished=true; |
---|
3707 | } |
---|
3708 | } |
---|
3709 | #endif |
---|
3710 | // If fixed then round again |
---|
3711 | if (!branch_&&anyAction!=-2) { |
---|
3712 | finished=false; |
---|
3713 | } |
---|
3714 | // If these in then different action |
---|
3715 | #if ACTION == 1 |
---|
3716 | if (!anyAction) |
---|
3717 | anyAction=-1; |
---|
3718 | finished=true; |
---|
3719 | #endif |
---|
3720 | } |
---|
3721 | } |
---|
3722 | delete ws; |
---|
3723 | } |
---|
3724 | } |
---|
3725 | if (model->messageHandler()->logLevel()>2) |
---|
3726 | printf("%d strong, %d iters, %d pen, %d mark, %d fixed, action %d nnott %d nt %d, %d dq %s ns %d\n", |
---|
3727 | numberStrongDone,numberStrongIterations,xPen,xMark, |
---|
3728 | numberToFix,anyAction,numberNotTrusted,px[0],px[1],px[2]>0 ? "y" : "n",px[3]); |
---|
3729 | // update number of strong iterations etc |
---|
3730 | model->incrementStrongInfo(numberStrongDone,numberStrongIterations, |
---|
3731 | anyAction==-2 ? 0:numberToFix,anyAction==-2); |
---|
3732 | if (!newWay) { |
---|
3733 | if (((model->searchStrategy()+1)%1000)==0) { |
---|
3734 | if (solver->messageHandler()->logLevel()>1) |
---|
3735 | printf("%d strong, %d iters, %d inf, %d not finished, %d not trusted\n", |
---|
3736 | numberStrongDone,numberStrongIterations,numberStrongInfeasible,numberUnfinished, |
---|
3737 | numberNotTrusted); |
---|
3738 | // decide what to do |
---|
3739 | int strategy=1; |
---|
3740 | if (numberUnfinished*4>numberStrongDone&&numberStrongInfeasible*10<numberStrongDone) { |
---|
3741 | strategy=2; |
---|
3742 | if (model->logLevel()>1) |
---|
3743 | printf("going to strategy 2\n"); |
---|
3744 | } |
---|
3745 | if (numberNodes) |
---|
3746 | strategy=1; // should only happen after hot start |
---|
3747 | model->setSearchStrategy(strategy); |
---|
3748 | } |
---|
3749 | } |
---|
3750 | //if (numberToFix&&depth_<5) |
---|
3751 | //printf("%d fixed by strong at depth %d\n",numberToFix,depth_); |
---|
3752 | // Set guessed solution value |
---|
3753 | guessedObjectiveValue_ = objectiveValue_+estimatedDegradation; |
---|
3754 | |
---|
3755 | // Get collection of branches if mini tree wanted |
---|
3756 | if (anyAction==0&&numberMini&&numberMini>1) { |
---|
3757 | // Sort |
---|
3758 | CoinSort_2(sort,sort+numberMini,whichObject); |
---|
3759 | delete branch_; |
---|
3760 | branch_=NULL; |
---|
3761 | numberMini = CoinMin(numberMini,model->sizeMiniTree()); |
---|
3762 | anyAction=numberMini; |
---|
3763 | branches = new OsiSolverBranch[numberMini]; |
---|
3764 | for (int iDo=0;iDo<numberMini;iDo++) { |
---|
3765 | int iObject = whichObject[iDo]; |
---|
3766 | OsiObject * object = model->modifiableObject(iObject); |
---|
3767 | CbcSimpleInteger * obj = |
---|
3768 | dynamic_cast <CbcSimpleInteger *>(object) ; |
---|
3769 | OsiSolverBranch * oneBranch; |
---|
3770 | if (obj) { |
---|
3771 | oneBranch = obj->solverBranch(solver,&usefulInfo); |
---|
3772 | } else { |
---|
3773 | CbcObject * obj = |
---|
3774 | dynamic_cast <CbcObject *>(object) ; |
---|
3775 | assert (obj); |
---|
3776 | oneBranch = obj->solverBranch(); |
---|
3777 | } |
---|
3778 | branches[iDo]=*oneBranch; |
---|
3779 | delete oneBranch; |
---|
3780 | } |
---|
3781 | } |
---|
3782 | /* |
---|
3783 | Cleanup, then we're finished |
---|
3784 | */ |
---|
3785 | if (!model->branchingMethod()) |
---|
3786 | delete decision; |
---|
3787 | |
---|
3788 | delete [] fixObject; |
---|
3789 | delete [] sort; |
---|
3790 | delete [] whichObject; |
---|
3791 | delete [] objectMark; |
---|
3792 | delete [] saveLower; |
---|
3793 | delete [] saveUpper; |
---|
3794 | delete [] upEstimate; |
---|
3795 | delete [] downEstimate; |
---|
3796 | # ifdef COIN_HAS_CLP |
---|
3797 | if (osiclp) |
---|
3798 | osiclp->setSpecialOptions(saveClpOptions); |
---|
3799 | # endif |
---|
3800 | // restore solution |
---|
3801 | solver->setColSolution(saveSolution); |
---|
3802 | model->reserveCurrentSolution(saveSolution); |
---|
3803 | delete [] saveSolution; |
---|
3804 | model->setStateOfSearch(saveStateOfSearch); |
---|
3805 | model->setLogLevel(saveLogLevel); |
---|
3806 | return anyAction; |
---|
3807 | } |
---|
3808 | int CbcNode::analyze (CbcModel *model, double * results) |
---|
3809 | { |
---|
3810 | int i; |
---|
3811 | int numberIterationsAllowed = model->numberAnalyzeIterations(); |
---|
3812 | OsiSolverInterface * solver = model->solver(); |
---|
3813 | objectiveValue_ = solver->getObjSense()*solver->getObjValue(); |
---|
3814 | double cutoff =model->getCutoff(); |
---|
3815 | const double * lower = solver->getColLower(); |
---|
3816 | const double * upper = solver->getColUpper(); |
---|
3817 | const double * dj = solver->getReducedCost(); |
---|
3818 | int numberObjects = model->numberObjects(); |
---|
3819 | int numberColumns = model->getNumCols(); |
---|
3820 | // Initialize arrays |
---|
3821 | int numberIntegers = model->numberIntegers(); |
---|
3822 | int * back = new int[numberColumns]; |
---|
3823 | const int * integerVariable = model->integerVariable(); |
---|
3824 | for (i=0;i<numberColumns;i++) |
---|
3825 | back[i]=-1; |
---|
3826 | // What results is |
---|
3827 | double * newLower = results; |
---|
3828 | double * objLower = newLower+numberIntegers; |
---|
3829 | double * newUpper = objLower+numberIntegers; |
---|
3830 | double * objUpper = newUpper+numberIntegers; |
---|
3831 | for (i=0;i<numberIntegers;i++) { |
---|
3832 | int iColumn = integerVariable[i]; |
---|
3833 | back[iColumn]=i; |
---|
3834 | newLower[i]=0.0; |
---|
3835 | objLower[i]=-COIN_DBL_MAX; |
---|
3836 | newUpper[i]=0.0; |
---|
3837 | objUpper[i]=-COIN_DBL_MAX; |
---|
3838 | } |
---|
3839 | double * saveUpper = new double[numberColumns]; |
---|
3840 | double * saveLower = new double[numberColumns]; |
---|
3841 | int anyAction=0; |
---|
3842 | // Save solution in case heuristics need good solution later |
---|
3843 | |
---|
3844 | double * saveSolution = new double[numberColumns]; |
---|
3845 | memcpy(saveSolution,solver->getColSolution(),numberColumns*sizeof(double)); |
---|
3846 | model->reserveCurrentSolution(saveSolution); |
---|
3847 | for (i=0;i<numberColumns;i++) { |
---|
3848 | saveLower[i] = lower[i]; |
---|
3849 | saveUpper[i] = upper[i]; |
---|
3850 | } |
---|
3851 | // Get arrays to sort |
---|
3852 | double * sort = new double[numberObjects]; |
---|
3853 | int * whichObject = new int[numberObjects]; |
---|
3854 | int numberToFix=0; |
---|
3855 | int numberToDo=0; |
---|
3856 | double integerTolerance = |
---|
3857 | model->getDblParam(CbcModel::CbcIntegerTolerance); |
---|
3858 | // point to useful information |
---|
3859 | OsiBranchingInformation usefulInfo = model->usefulInformation(); |
---|
3860 | // and modify |
---|
3861 | usefulInfo.depth_=depth_; |
---|
3862 | |
---|
3863 | // compute current state |
---|
3864 | int numberObjectInfeasibilities; // just odd ones |
---|
3865 | int numberIntegerInfeasibilities; |
---|
3866 | model->feasibleSolution( |
---|
3867 | numberIntegerInfeasibilities, |
---|
3868 | numberObjectInfeasibilities); |
---|
3869 | # ifdef COIN_HAS_CLP |
---|
3870 | OsiClpSolverInterface * osiclp = dynamic_cast< OsiClpSolverInterface*> (solver); |
---|
3871 | int saveClpOptions=0; |
---|
3872 | bool fastIterations = (model->specialOptions()&8)!=0; |
---|
3873 | if (osiclp&&fastIterations) { |
---|
3874 | // for faster hot start |
---|
3875 | saveClpOptions = osiclp->specialOptions(); |
---|
3876 | osiclp->setSpecialOptions(saveClpOptions|8192); |
---|
3877 | } |
---|
3878 | # else |
---|
3879 | bool fastIterations = false ; |
---|
3880 | # endif |
---|
3881 | /* |
---|
3882 | Scan for branching objects that indicate infeasibility. Choose candidates |
---|
3883 | using priority as the first criteria, then integer infeasibility. |
---|
3884 | |
---|
3885 | The algorithm is to fill the array with a set of good candidates (by |
---|
3886 | infeasibility) with priority bestPriority. Finding a candidate with |
---|
3887 | priority better (less) than bestPriority flushes the choice array. (This |
---|
3888 | serves as initialization when the first candidate is found.) |
---|
3889 | |
---|
3890 | */ |
---|
3891 | numberToDo=0; |
---|
3892 | for (i=0;i<numberObjects;i++) { |
---|
3893 | OsiObject * object = model->modifiableObject(i); |
---|
3894 | CbcSimpleIntegerDynamicPseudoCost * dynamicObject = |
---|
3895 | dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ; |
---|
3896 | if(!dynamicObject) |
---|
3897 | continue; |
---|
3898 | int preferredWay; |
---|
3899 | double infeasibility = object->infeasibility(&usefulInfo,preferredWay); |
---|
3900 | int iColumn = dynamicObject->columnNumber(); |
---|
3901 | if (saveUpper[iColumn]==saveLower[iColumn]) |
---|
3902 | continue; |
---|
3903 | if (infeasibility) |
---|
3904 | sort[numberToDo]=-1.0e10-infeasibility; |
---|
3905 | else |
---|
3906 | sort[numberToDo]=-fabs(dj[iColumn]); |
---|
3907 | whichObject[numberToDo++]=i; |
---|
3908 | } |
---|
3909 | // Save basis |
---|
3910 | CoinWarmStart * ws = solver->getWarmStart(); |
---|
3911 | int saveLimit; |
---|
3912 | solver->getIntParam(OsiMaxNumIterationHotStart,saveLimit); |
---|
3913 | int targetIterations = CoinMax(500,numberIterationsAllowed/numberObjects); |
---|
3914 | if (saveLimit<targetIterations) |
---|
3915 | solver->setIntParam(OsiMaxNumIterationHotStart,targetIterations); |
---|
3916 | // Mark hot start |
---|
3917 | solver->markHotStart(); |
---|
3918 | // Sort |
---|
3919 | CoinSort_2(sort,sort+numberToDo,whichObject); |
---|
3920 | //double distanceToCutoff=model->getCutoff()-objectiveValue_; |
---|
3921 | double * currentSolution = model->currentSolution(); |
---|
3922 | double objMin = 1.0e50; |
---|
3923 | double objMax = -1.0e50; |
---|
3924 | bool needResolve=false; |
---|
3925 | int iDo; |
---|
3926 | for (iDo=0;iDo<numberToDo;iDo++) { |
---|
3927 | CbcStrongInfo choice; |
---|
3928 | int iObject = whichObject[iDo]; |
---|
3929 | OsiObject * object = model->modifiableObject(iObject); |
---|
3930 | CbcSimpleIntegerDynamicPseudoCost * dynamicObject = |
---|
3931 | dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(object) ; |
---|
3932 | int iColumn = dynamicObject->columnNumber(); |
---|
3933 | int preferredWay; |
---|
3934 | object->infeasibility(&usefulInfo,preferredWay); |
---|
3935 | double value = currentSolution[iColumn]; |
---|
3936 | double nearest = floor(value+0.5); |
---|
3937 | double lowerValue = floor(value); |
---|
3938 | bool satisfied=false; |
---|
3939 | if (fabs(value-nearest)<=integerTolerance||value<saveLower[iColumn]||value>saveUpper[iColumn]) { |
---|
3940 | satisfied=true; |
---|
3941 | double newValue; |
---|
3942 | if (nearest<saveUpper[iColumn]) { |
---|
3943 | newValue = nearest + 1.0001*integerTolerance; |
---|
3944 | lowerValue = nearest; |
---|
3945 | } else { |
---|
3946 | newValue = nearest - 1.0001*integerTolerance; |
---|
3947 | lowerValue = nearest-1; |
---|
3948 | } |
---|
3949 | currentSolution[iColumn]=newValue; |
---|
3950 | } |
---|
3951 | double upperValue = lowerValue+1.0; |
---|
3952 | CbcSimpleInteger * obj = |
---|
3953 | dynamic_cast <CbcSimpleInteger *>(object) ; |
---|
3954 | if (obj) { |
---|
3955 | choice.possibleBranch=obj->createBranch(solver,&usefulInfo,preferredWay); |
---|
3956 | } else { |
---|
3957 | CbcObject * obj = |
---|
3958 | dynamic_cast <CbcObject *>(object) ; |
---|
3959 | assert (obj); |
---|
3960 | choice.possibleBranch=obj->createBranch(preferredWay); |
---|
3961 | } |
---|
3962 | currentSolution[iColumn]=value; |
---|
3963 | // Save which object it was |
---|
3964 | choice.objectNumber=iObject; |
---|
3965 | choice.numIntInfeasUp = numberUnsatisfied_; |
---|
3966 | choice.numIntInfeasDown = numberUnsatisfied_; |
---|
3967 | choice.downMovement = 0.0; |
---|
3968 | choice.upMovement = 0.0; |
---|
3969 | choice.numItersDown = 0; |
---|
3970 | choice.numItersUp = 0; |
---|
3971 | choice.fix=0; // say not fixed |
---|
3972 | double objectiveChange ; |
---|
3973 | double newObjectiveValue=1.0e100; |
---|
3974 | int j; |
---|
3975 | // status is 0 finished, 1 infeasible and other |
---|
3976 | int iStatus; |
---|
3977 | /* |
---|
3978 | Try the down direction first. (Specify the initial branching alternative as |
---|
3979 | down with a call to way(-1). Each subsequent call to branch() performs the |
---|
3980 | specified branch and advances the branch object state to the next branch |
---|
3981 | alternative.) |
---|
3982 | */ |
---|
3983 | choice.possibleBranch->way(-1) ; |
---|
3984 | choice.possibleBranch->branch() ; |
---|
3985 | if (fabs(value-lowerValue)>integerTolerance) { |
---|
3986 | solver->solveFromHotStart() ; |
---|
3987 | /* |
---|
3988 | We now have an estimate of objective degradation that we can use for strong |
---|
3989 | branching. If we're over the cutoff, the variable is monotone up. |
---|
3990 | If we actually made it to optimality, check for a solution, and if we have |
---|
3991 | a good one, call setBestSolution to process it. Note that this may reduce the |
---|
3992 | cutoff, so we check again to see if we can declare this variable monotone. |
---|
3993 | */ |
---|
3994 | if (solver->isProvenOptimal()) |
---|
3995 | iStatus=0; // optimal |
---|
3996 | else if (solver->isIterationLimitReached() |
---|
3997 | &&!solver->isDualObjectiveLimitReached()) |
---|
3998 | iStatus=2; // unknown |
---|
3999 | else |
---|
4000 | iStatus=1; // infeasible |
---|
4001 | newObjectiveValue = solver->getObjSense()*solver->getObjValue(); |
---|
4002 | choice.numItersDown = solver->getIterationCount(); |
---|
4003 | numberIterationsAllowed -= choice.numItersDown; |
---|
4004 | objectiveChange = newObjectiveValue - objectiveValue_; |
---|
4005 | if (!iStatus) { |
---|
4006 | choice.finishedDown = true ; |
---|
4007 | if (newObjectiveValue>=cutoff) { |
---|
4008 | objectiveChange = 1.0e100; // say infeasible |
---|
4009 | } else { |
---|
4010 | // See if integer solution |
---|
4011 | if (model->feasibleSolution(choice.numIntInfeasDown, |
---|
4012 | choice.numObjInfeasDown) |
---|
4013 | &&model->problemFeasibility()->feasible(model,-1)>=0) { |
---|
4014 | model->setBestSolution(CBC_STRONGSOL, |
---|
4015 | newObjectiveValue, |
---|
4016 | solver->getColSolution()) ; |
---|
4017 | model->setLastHeuristic(NULL); |
---|
4018 | model->incrementUsed(solver->getColSolution()); |
---|
4019 | cutoff =model->getCutoff(); |
---|
4020 | if (newObjectiveValue >= cutoff) // *new* cutoff |
---|
4021 | objectiveChange = 1.0e100 ; |
---|
4022 | } |
---|
4023 | } |
---|
4024 | } else if (iStatus==1) { |
---|
4025 | objectiveChange = 1.0e100 ; |
---|
4026 | } else { |
---|
4027 | // Can't say much as we did not finish |
---|
4028 | choice.finishedDown = false ; |
---|
4029 | } |
---|
4030 | choice.downMovement = objectiveChange ; |
---|
4031 | } |
---|
4032 | // restore bounds |
---|
4033 | for ( j=0;j<numberColumns;j++) { |
---|
4034 | if (saveLower[j] != lower[j]) |
---|
4035 | solver->setColLower(j,saveLower[j]); |
---|
4036 | if (saveUpper[j] != upper[j]) |
---|
4037 | solver->setColUpper(j,saveUpper[j]); |
---|
4038 | } |
---|
4039 | // repeat the whole exercise, forcing the variable up |
---|
4040 | choice.possibleBranch->branch(); |
---|
4041 | if (fabs(value-upperValue)>integerTolerance) { |
---|
4042 | solver->solveFromHotStart() ; |
---|
4043 | /* |
---|
4044 | We now have an estimate of objective degradation that we can use for strong |
---|
4045 | branching. If we're over the cutoff, the variable is monotone up. |
---|
4046 | If we actually made it to optimality, check for a solution, and if we have |
---|
4047 | a good one, call setBestSolution to process it. Note that this may reduce the |
---|
4048 | cutoff, so we check again to see if we can declare this variable monotone. |
---|
4049 | */ |
---|
4050 | if (solver->isProvenOptimal()) |
---|
4051 | iStatus=0; // optimal |
---|
4052 | else if (solver->isIterationLimitReached() |
---|
4053 | &&!solver->isDualObjectiveLimitReached()) |
---|
4054 | iStatus=2; // unknown |
---|
4055 | else |
---|
4056 | iStatus=1; // infeasible |
---|
4057 | newObjectiveValue = solver->getObjSense()*solver->getObjValue(); |
---|
4058 | choice.numItersUp = solver->getIterationCount(); |
---|
4059 | numberIterationsAllowed -= choice.numItersUp; |
---|
4060 | objectiveChange = newObjectiveValue - objectiveValue_; |
---|
4061 | if (!iStatus) { |
---|
4062 | choice.finishedUp = true ; |
---|
4063 | if (newObjectiveValue>=cutoff) { |
---|
4064 | objectiveChange = 1.0e100; // say infeasible |
---|
4065 | } else { |
---|
4066 | // See if integer solution |
---|
4067 | if (model->feasibleSolution(choice.numIntInfeasUp, |
---|
4068 | choice.numObjInfeasUp) |
---|
4069 | &&model->problemFeasibility()->feasible(model,-1)>=0) { |
---|
4070 | model->setBestSolution(CBC_STRONGSOL, |
---|
4071 | newObjectiveValue, |
---|
4072 | solver->getColSolution()) ; |
---|
4073 | model->setLastHeuristic(NULL); |
---|
4074 | model->incrementUsed(solver->getColSolution()); |
---|
4075 | cutoff =model->getCutoff(); |
---|
4076 | if (newObjectiveValue >= cutoff) // *new* cutoff |
---|
4077 | objectiveChange = 1.0e100 ; |
---|
4078 | } |
---|
4079 | } |
---|
4080 | } else if (iStatus==1) { |
---|
4081 | objectiveChange = 1.0e100 ; |
---|
4082 | } else { |
---|
4083 | // Can't say much as we did not finish |
---|
4084 | choice.finishedUp = false ; |
---|
4085 | } |
---|
4086 | choice.upMovement = objectiveChange ; |
---|
4087 | |
---|
4088 | // restore bounds |
---|
4089 | for ( j=0;j<numberColumns;j++) { |
---|
4090 | if (saveLower[j] != lower[j]) |
---|
4091 | solver->setColLower(j,saveLower[j]); |
---|
4092 | if (saveUpper[j] != upper[j]) |
---|
4093 | solver->setColUpper(j,saveUpper[j]); |
---|
4094 | } |
---|
4095 | } |
---|
4096 | // If objective goes above certain amount we can set bound |
---|
4097 | int jInt = back[iColumn]; |
---|
4098 | newLower[jInt]=upperValue; |
---|
4099 | if (choice.finishedDown||!fastIterations) |
---|
4100 | objLower[jInt]=choice.downMovement+objectiveValue_; |
---|
4101 | else |
---|
4102 | objLower[jInt]=objectiveValue_; |
---|
4103 | newUpper[jInt]=lowerValue; |
---|
4104 | if (choice.finishedUp||!fastIterations) |
---|
4105 | objUpper[jInt]=choice.upMovement+objectiveValue_; |
---|
4106 | else |
---|
4107 | objUpper[jInt]=objectiveValue_; |
---|
4108 | objMin = CoinMin(CoinMin(objLower[jInt],objUpper[jInt]),objMin); |
---|
4109 | /* |
---|
4110 | End of evaluation for this candidate variable. Possibilities are: |
---|
4111 | * Both sides below cutoff; this variable is a candidate for branching. |
---|
4112 | * Both sides infeasible or above the objective cutoff: no further action |
---|
4113 | here. Break from the evaluation loop and assume the node will be purged |
---|
4114 | by the caller. |
---|
4115 | * One side below cutoff: Install the branch (i.e., fix the variable). Break |
---|
4116 | from the evaluation loop and assume the node will be reoptimised by the |
---|
4117 | caller. |
---|
4118 | */ |
---|
4119 | if (choice.upMovement<1.0e100) { |
---|
4120 | if(choice.downMovement<1.0e100) { |
---|
4121 | objMax = CoinMax(CoinMax(objLower[jInt],objUpper[jInt]),objMax); |
---|
4122 | // In case solution coming in was odd |
---|
4123 | choice.upMovement = CoinMax(0.0,choice.upMovement); |
---|
4124 | choice.downMovement = CoinMax(0.0,choice.downMovement); |
---|
4125 | // feasible - |
---|
4126 | model->messageHandler()->message(CBC_STRONG,*model->messagesPointer()) |
---|
4127 | << iObject << iColumn |
---|
4128 | <<choice.downMovement<<choice.numIntInfeasDown |
---|
4129 | <<choice.upMovement<<choice.numIntInfeasUp |
---|
4130 | <<value |
---|
4131 | <<CoinMessageEol; |
---|
4132 | } else { |
---|
4133 | // up feasible, down infeasible |
---|
4134 | anyAction=-1; |
---|
4135 | if (!satisfied) |
---|
4136 | needResolve=true; |
---|
4137 | choice.fix=1; |
---|
4138 | numberToFix++; |
---|
4139 | saveLower[iColumn]=upperValue; |
---|
4140 | solver->setColLower(iColumn,upperValue); |
---|
4141 | } |
---|
4142 | } else { |
---|
4143 | if(choice.downMovement<1.0e100) { |
---|
4144 | // down feasible, up infeasible |
---|
4145 | anyAction=-1; |
---|
4146 | if (!satisfied) |
---|
4147 | needResolve=true; |
---|
4148 | choice.fix=-1; |
---|
4149 | numberToFix++; |
---|
4150 | saveUpper[iColumn]=lowerValue; |
---|
4151 | solver->setColUpper(iColumn,lowerValue); |
---|
4152 | } else { |
---|
4153 | // neither side feasible |
---|
4154 | anyAction=-2; |
---|
4155 | printf("Both infeasible for choice %d sequence %d\n",i, |
---|
4156 | model->object(choice.objectNumber)->columnNumber()); |
---|
4157 | delete ws; |
---|
4158 | ws=NULL; |
---|
4159 | //solver->writeMps("bad"); |
---|
4160 | numberToFix=-1; |
---|
4161 | delete choice.possibleBranch; |
---|
4162 | choice.possibleBranch=NULL; |
---|
4163 | break; |
---|
4164 | } |
---|
4165 | } |
---|
4166 | delete choice.possibleBranch; |
---|
4167 | if (numberIterationsAllowed<=0) |
---|
4168 | break; |
---|
4169 | //printf("obj %d, col %d, down %g up %g value %g\n",iObject,iColumn, |
---|
4170 | // choice.downMovement,choice.upMovement,value); |
---|
4171 | } |
---|
4172 | printf("Best possible solution %g, can fix more if solution of %g found - looked at %d variables in %d iterations\n", |
---|
4173 | objMin,objMax,iDo,model->numberAnalyzeIterations()-numberIterationsAllowed); |
---|
4174 | model->setNumberAnalyzeIterations(numberIterationsAllowed); |
---|
4175 | // Delete the snapshot |
---|
4176 | solver->unmarkHotStart(); |
---|
4177 | // back to normal |
---|
4178 | solver->setHintParam(OsiDoInBranchAndCut,true,OsiHintDo,NULL) ; |
---|
4179 | solver->setIntParam(OsiMaxNumIterationHotStart,saveLimit); |
---|
4180 | // restore basis |
---|
4181 | solver->setWarmStart(ws); |
---|
4182 | delete ws; |
---|
4183 | |
---|
4184 | delete [] sort; |
---|
4185 | delete [] whichObject; |
---|
4186 | delete [] saveLower; |
---|
4187 | delete [] saveUpper; |
---|
4188 | delete [] back; |
---|
4189 | // restore solution |
---|
4190 | solver->setColSolution(saveSolution); |
---|
4191 | # ifdef COIN_HAS_CLP |
---|
4192 | if (osiclp) |
---|
4193 | osiclp->setSpecialOptions(saveClpOptions); |
---|
4194 | # endif |
---|
4195 | model->reserveCurrentSolution(saveSolution); |
---|
4196 | delete [] saveSolution; |
---|
4197 | if (needResolve) |
---|
4198 | solver->resolve(); |
---|
4199 | return numberToFix; |
---|
4200 | } |
---|
4201 | |
---|
4202 | |
---|
4203 | CbcNode::CbcNode(const CbcNode & rhs) |
---|
4204 | { |
---|
4205 | #ifdef CHECK_NODE |
---|
4206 | printf("CbcNode %x Constructor from rhs %x\n",this,&rhs); |
---|
4207 | #endif |
---|
4208 | if (rhs.nodeInfo_) |
---|
4209 | nodeInfo_ = rhs.nodeInfo_->clone(); |
---|
4210 | else |
---|
4211 | nodeInfo_=NULL; |
---|
4212 | objectiveValue_=rhs.objectiveValue_; |
---|
4213 | guessedObjectiveValue_ = rhs.guessedObjectiveValue_; |
---|
4214 | sumInfeasibilities_ = rhs.sumInfeasibilities_; |
---|
4215 | if (rhs.branch_) |
---|
4216 | branch_=rhs.branch_->clone(); |
---|
4217 | else |
---|
4218 | branch_=NULL; |
---|
4219 | depth_ = rhs.depth_; |
---|
4220 | numberUnsatisfied_ = rhs.numberUnsatisfied_; |
---|
4221 | } |
---|
4222 | |
---|
4223 | CbcNode & |
---|
4224 | CbcNode::operator=(const CbcNode & rhs) |
---|
4225 | { |
---|
4226 | if (this != &rhs) { |
---|
4227 | delete nodeInfo_; |
---|
4228 | if (rhs.nodeInfo_) |
---|
4229 | nodeInfo_ = rhs.nodeInfo_->clone(); |
---|
4230 | else |
---|
4231 | nodeInfo_ = NULL; |
---|
4232 | objectiveValue_=rhs.objectiveValue_; |
---|
4233 | guessedObjectiveValue_ = rhs.guessedObjectiveValue_; |
---|
4234 | sumInfeasibilities_ = rhs.sumInfeasibilities_; |
---|
4235 | if (rhs.branch_) |
---|
4236 | branch_=rhs.branch_->clone(); |
---|
4237 | else |
---|
4238 | branch_=NULL, |
---|
4239 | depth_ = rhs.depth_; |
---|
4240 | numberUnsatisfied_ = rhs.numberUnsatisfied_; |
---|
4241 | } |
---|
4242 | return *this; |
---|
4243 | } |
---|
4244 | CbcNode::~CbcNode () |
---|
4245 | { |
---|
4246 | #ifdef CHECK_NODE |
---|
4247 | if (nodeInfo_) |
---|
4248 | printf("CbcNode %x Destructor nodeInfo %x (%d)\n", |
---|
4249 | this,nodeInfo_,nodeInfo_->numberPointingToThis()); |
---|
4250 | else |
---|
4251 | printf("CbcNode %x Destructor nodeInfo %x (?)\n", |
---|
4252 | this,nodeInfo_); |
---|
4253 | #endif |
---|
4254 | if (nodeInfo_) { |
---|
4255 | nodeInfo_->nullOwner(); |
---|
4256 | int numberToDelete=nodeInfo_->numberBranchesLeft(); |
---|
4257 | // CbcNodeInfo * parent = nodeInfo_->parent(); |
---|
4258 | //assert (nodeInfo_->numberPointingToThis()>0); |
---|
4259 | if (nodeInfo_->decrement(numberToDelete)==0) { |
---|
4260 | delete nodeInfo_; |
---|
4261 | } else { |
---|
4262 | //printf("node %x nodeinfo %x parent %x\n",this,nodeInfo_,nodeInfo_->parent()); |
---|
4263 | // anyway decrement parent |
---|
4264 | //if (parent) |
---|
4265 | ///parent->decrement(1); |
---|
4266 | } |
---|
4267 | } |
---|
4268 | delete branch_; |
---|
4269 | } |
---|
4270 | // Decrement active cut counts |
---|
4271 | void |
---|
4272 | CbcNode::decrementCuts(int change) |
---|
4273 | { |
---|
4274 | if(nodeInfo_) { |
---|
4275 | nodeInfo_->decrementCuts(change); |
---|
4276 | } |
---|
4277 | } |
---|
4278 | void |
---|
4279 | CbcNode::decrementParentCuts(int change) |
---|
4280 | { |
---|
4281 | if(nodeInfo_) { |
---|
4282 | nodeInfo_->decrementParentCuts(change); |
---|
4283 | } |
---|
4284 | } |
---|
4285 | |
---|
4286 | /* |
---|
4287 | Initialize reference counts (numberPointingToThis, numberBranchesLeft_) |
---|
4288 | in the attached nodeInfo_. |
---|
4289 | */ |
---|
4290 | void |
---|
4291 | CbcNode::initializeInfo() |
---|
4292 | { |
---|
4293 | assert(nodeInfo_ && branch_) ; |
---|
4294 | nodeInfo_->initializeInfo(branch_->numberBranches()); |
---|
4295 | } |
---|
4296 | // Nulls out node info |
---|
4297 | void |
---|
4298 | CbcNode::nullNodeInfo() |
---|
4299 | { |
---|
4300 | nodeInfo_=NULL; |
---|
4301 | } |
---|
4302 | |
---|
4303 | int |
---|
4304 | CbcNode::branch(OsiSolverInterface * solver) |
---|
4305 | { |
---|
4306 | double changeInGuessed; |
---|
4307 | if (!solver) |
---|
4308 | changeInGuessed=branch_->branch(); |
---|
4309 | else |
---|
4310 | changeInGuessed=branch_->branch(solver); |
---|
4311 | guessedObjectiveValue_+= changeInGuessed; |
---|
4312 | //#define PRINTIT |
---|
4313 | #ifdef PRINTIT |
---|
4314 | int numberLeft = nodeInfo_->numberBranchesLeft(); |
---|
4315 | CbcNodeInfo * parent = nodeInfo_->parent(); |
---|
4316 | int parentNodeNumber = -1; |
---|
4317 | //CbcBranchingObject * object1 = branch_->object_; |
---|
4318 | //OsiObject * object = object1-> |
---|
4319 | //int sequence = object->columnNumber); |
---|
4320 | int id=-1; |
---|
4321 | double value=0.0; |
---|
4322 | if (branch_) { |
---|
4323 | id = branch_->variable(); |
---|
4324 | value = branch_->value(); |
---|
4325 | } |
---|
4326 | printf("id %d value %g objvalue %g\n",id,value,objectiveValue_); |
---|
4327 | if (parent) |
---|
4328 | parentNodeNumber = parent->nodeNumber(); |
---|
4329 | printf("Node number %d, %s, way %d, depth %d, parent node number %d\n", |
---|
4330 | nodeInfo_->nodeNumber(),(numberLeft==2) ? "leftBranch" : "rightBranch", |
---|
4331 | way(),depth_,parentNodeNumber); |
---|
4332 | #endif |
---|
4333 | return nodeInfo_->branchedOn(); |
---|
4334 | } |
---|
4335 | /* Active arm of the attached OsiBranchingObject. |
---|
4336 | |
---|
4337 | In the simplest instance, coded -1 for the down arm of the branch, +1 for |
---|
4338 | the up arm. But see OsiBranchingObject::way() |
---|
4339 | Use nodeInfo--.numberBranchesLeft_ to see how active |
---|
4340 | */ |
---|
4341 | int |
---|
4342 | CbcNode::way() const |
---|
4343 | { |
---|
4344 | if (branch_) { |
---|
4345 | CbcBranchingObject * obj = |
---|
4346 | dynamic_cast <CbcBranchingObject *>(branch_) ; |
---|
4347 | assert (obj); |
---|
4348 | return obj->way(); |
---|
4349 | } else { |
---|
4350 | return 0; |
---|
4351 | } |
---|
4352 | } |
---|
4353 | /* Create a branching object for the node |
---|
4354 | |
---|
4355 | The routine scans the object list of the model and selects a set of |
---|
4356 | unsatisfied objects as candidates for branching. The candidates are |
---|
4357 | evaluated, and an appropriate branch object is installed. |
---|
4358 | |
---|
4359 | The numberPassesLeft is decremented to stop fixing one variable each time |
---|
4360 | and going on and on (e.g. for stock cutting, air crew scheduling) |
---|
4361 | |
---|
4362 | If evaluation determines that an object is monotone or infeasible, |
---|
4363 | the routine returns immediately. In the case of a monotone object, |
---|
4364 | the branch object has already been called to modify the model. |
---|
4365 | |
---|
4366 | Return value: |
---|
4367 | <ul> |
---|
4368 | <li> 0: A branching object has been installed |
---|
4369 | <li> -1: A monotone object was discovered |
---|
4370 | <li> -2: An infeasible object was discovered |
---|
4371 | </ul> |
---|
4372 | Branch state: |
---|
4373 | <ul> |
---|
4374 | <li> -1: start |
---|
4375 | <li> -1: A monotone object was discovered |
---|
4376 | <li> -2: An infeasible object was discovered |
---|
4377 | </ul> |
---|
4378 | */ |
---|
4379 | int |
---|
4380 | CbcNode::chooseOsiBranch (CbcModel * model, |
---|
4381 | CbcNode * lastNode, |
---|
4382 | OsiBranchingInformation * usefulInfo, |
---|
4383 | int branchState) |
---|
4384 | { |
---|
4385 | int returnStatus=0; |
---|
4386 | if (lastNode) |
---|
4387 | depth_ = lastNode->depth_+1; |
---|
4388 | else |
---|
4389 | depth_ = 0; |
---|
4390 | OsiSolverInterface * solver = model->solver(); |
---|
4391 | objectiveValue_ = solver->getObjValue()*solver->getObjSense(); |
---|
4392 | usefulInfo->objectiveValue_ = objectiveValue_; |
---|
4393 | usefulInfo->depth_ = depth_; |
---|
4394 | const double * saveInfoSol = usefulInfo->solution_; |
---|
4395 | double * saveSolution = new double[solver->getNumCols()]; |
---|
4396 | memcpy(saveSolution,solver->getColSolution(),solver->getNumCols()*sizeof(double)); |
---|
4397 | usefulInfo->solution_ = saveSolution; |
---|
4398 | OsiChooseVariable * choose = model->branchingMethod()->chooseMethod(); |
---|
4399 | int numberUnsatisfied=-1; |
---|
4400 | if (branchState<0) { |
---|
4401 | // initialize |
---|
4402 | // initialize sum of "infeasibilities" |
---|
4403 | sumInfeasibilities_ = 0.0; |
---|
4404 | numberUnsatisfied = choose->setupList(usefulInfo,true); |
---|
4405 | numberUnsatisfied_ = numberUnsatisfied; |
---|
4406 | branchState=0; |
---|
4407 | if (numberUnsatisfied_<0) { |
---|
4408 | // infeasible |
---|
4409 | delete [] saveSolution; |
---|
4410 | return -2; |
---|
4411 | } |
---|
4412 | } |
---|
4413 | // unset best |
---|
4414 | int best=-1; |
---|
4415 | choose->setBestObjectIndex(-1); |
---|
4416 | if (numberUnsatisfied) { |
---|
4417 | if (branchState>0||!choose->numberOnList()) { |
---|
4418 | // we need to return at once - don't do strong branching or anything |
---|
4419 | if (choose->numberOnList()||!choose->numberStrong()) { |
---|
4420 | best = choose->candidates()[0]; |
---|
4421 | choose->setBestObjectIndex(best); |
---|
4422 | } else { |
---|
4423 | // nothing on list - need to try again - keep any solution |
---|
4424 | numberUnsatisfied = choose->setupList(usefulInfo, false); |
---|
4425 | numberUnsatisfied_ = numberUnsatisfied; |
---|
4426 | if (numberUnsatisfied) { |
---|
4427 | best = choose->candidates()[0]; |
---|
4428 | choose->setBestObjectIndex(best); |
---|
4429 | } |
---|
4430 | } |
---|
4431 | } else { |
---|
4432 | // carry on with strong branching or whatever |
---|
4433 | int returnCode = choose->chooseVariable(solver, usefulInfo,true); |
---|
4434 | // update number of strong iterations etc |
---|
4435 | model->incrementStrongInfo(choose->numberStrongDone(),choose->numberStrongIterations(), |
---|
4436 | returnCode==-1 ? 0:choose->numberStrongFixed(),returnCode==-1); |
---|
4437 | if (returnCode>1) { |
---|
4438 | // has fixed some |
---|
4439 | returnStatus=-1; |
---|
4440 | } else if (returnCode==-1) { |
---|
4441 | // infeasible |
---|
4442 | returnStatus=-2; |
---|
4443 | } else if (returnCode==0) { |
---|
4444 | // normal |
---|
4445 | returnStatus=0; |
---|
4446 | numberUnsatisfied=1; |
---|
4447 | } else { |
---|
4448 | // ones on list satisfied - double check |
---|
4449 | numberUnsatisfied = choose->setupList(usefulInfo, false); |
---|
4450 | numberUnsatisfied_ = numberUnsatisfied; |
---|
4451 | if (numberUnsatisfied) { |
---|
4452 | best = choose->candidates()[0]; |
---|
4453 | choose->setBestObjectIndex(best); |
---|
4454 | } |
---|
4455 | } |
---|
4456 | } |
---|
4457 | } |
---|
4458 | delete branch_; |
---|
4459 | branch_ = NULL; |
---|
4460 | guessedObjectiveValue_ = objectiveValue_; // for now |
---|
4461 | if (!returnStatus) { |
---|
4462 | if (numberUnsatisfied) { |
---|
4463 | // create branching object |
---|
4464 | const OsiObject * obj = model->solver()->object(choose->bestObjectIndex()); |
---|
4465 | //const OsiSolverInterface * solver = usefulInfo->solver_; |
---|
4466 | branch_ = obj->createBranch(model->solver(),usefulInfo,obj->whichWay()); |
---|
4467 | } |
---|
4468 | } |
---|
4469 | usefulInfo->solution_=saveInfoSol; |
---|
4470 | delete [] saveSolution; |
---|
4471 | // may have got solution |
---|
4472 | if (choose->goodSolution() |
---|
4473 | &&model->problemFeasibility()->feasible(model,-1)>=0) { |
---|
4474 | // yes |
---|
4475 | double objValue = choose->goodObjectiveValue(); |
---|
4476 | model->setBestSolution(CBC_STRONGSOL, |
---|
4477 | objValue, |
---|
4478 | choose->goodSolution()) ; |
---|
4479 | model->setLastHeuristic(NULL); |
---|
4480 | model->incrementUsed(choose->goodSolution()); |
---|
4481 | choose->clearGoodSolution(); |
---|
4482 | } |
---|
4483 | return returnStatus; |
---|
4484 | } |
---|