1 | /* $Id: CbcHeuristicRandRound.cpp 1902 2013-04-10 16:58:16Z stefan $ */ |
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2 | // Copyright (C) 2008, International Business Machines |
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3 | // Corporation and others. All Rights Reserved. |
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4 | // This code is licensed under the terms of the Eclipse Public License (EPL). |
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5 | |
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6 | #if defined(_MSC_VER) |
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7 | // Turn off compiler warning about long names |
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8 | # pragma warning(disable:4786) |
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9 | #endif |
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10 | #include <cassert> |
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11 | #include <cstdlib> |
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12 | #include <cmath> |
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13 | #include <cfloat> |
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14 | #include <vector> |
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15 | |
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16 | #include "CoinHelperFunctions.hpp" |
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17 | #include "OsiSolverInterface.hpp" |
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18 | #include "CbcModel.hpp" |
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19 | #include "CbcMessage.hpp" |
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20 | #include "CbcHeuristicRandRound.hpp" |
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21 | #include "OsiClpSolverInterface.hpp" |
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22 | #include "CoinTime.hpp" |
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23 | |
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24 | static inline int intRand(const int range) |
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25 | { |
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26 | return static_cast<int> (floor(CoinDrand48() * range)); |
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27 | } |
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28 | |
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29 | // Default Constructor |
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30 | CbcHeuristicRandRound::CbcHeuristicRandRound() |
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31 | : CbcHeuristic() |
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32 | { |
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33 | } |
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34 | |
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35 | // Constructor with model - assumed before cuts |
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36 | CbcHeuristicRandRound::CbcHeuristicRandRound(CbcModel & model) |
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37 | : CbcHeuristic(model) |
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38 | { |
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39 | model_ = &model; |
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40 | setWhen(1); |
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41 | } |
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42 | |
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43 | // Destructor |
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44 | CbcHeuristicRandRound::~CbcHeuristicRandRound () |
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45 | { |
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46 | } |
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47 | |
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48 | // Clone |
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49 | CbcHeuristic * |
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50 | CbcHeuristicRandRound::clone() const |
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51 | { |
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52 | return new CbcHeuristicRandRound(*this); |
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53 | } |
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54 | |
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55 | // Create C++ lines to get to current state |
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56 | void |
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57 | CbcHeuristicRandRound::generateCpp( FILE * fp) |
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58 | { |
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59 | CbcHeuristicRandRound other; |
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60 | fprintf(fp, "0#include \"CbcHeuristicRandRound.hpp\"\n"); |
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61 | fprintf(fp, "3 CbcHeuristicRandRound heuristicPFX(*cbcModel);\n"); |
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62 | CbcHeuristic::generateCpp(fp, "heuristicPFX"); |
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63 | fprintf(fp, "3 cbcModel->addHeuristic(&heuristicPFX);\n"); |
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64 | } |
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65 | |
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66 | // Copy constructor |
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67 | CbcHeuristicRandRound::CbcHeuristicRandRound(const CbcHeuristicRandRound & rhs) |
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68 | : |
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69 | CbcHeuristic(rhs) |
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70 | { |
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71 | } |
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72 | |
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73 | // Assignment operator |
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74 | CbcHeuristicRandRound & |
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75 | CbcHeuristicRandRound::operator=( const CbcHeuristicRandRound & rhs) |
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76 | { |
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77 | if (this != &rhs) { |
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78 | CbcHeuristic::operator=(rhs); |
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79 | } |
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80 | return *this; |
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81 | } |
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82 | |
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83 | // Resets stuff if model changes |
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84 | void |
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85 | CbcHeuristicRandRound::resetModel(CbcModel * model) |
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86 | { |
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87 | CbcHeuristic::resetModel(model); |
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88 | } |
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89 | |
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90 | /* |
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91 | Randomized Rounding Heuristic |
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92 | Returns 1 if solution, 0 if not |
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93 | */ |
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94 | int |
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95 | CbcHeuristicRandRound::solution(double & solutionValue, |
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96 | double * betterSolution) |
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97 | { |
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98 | // rlh: Todo: Memory Cleanup |
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99 | |
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100 | // std::cout << "Entering the Randomized Rounding Heuristic" << std::endl; |
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101 | |
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102 | setWhen(1); // setWhen(1) didn't have the effect I expected (e.g., run once). |
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103 | |
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104 | // Run only once. |
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105 | // |
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106 | // See if at root node |
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107 | bool atRoot = model_->getNodeCount() == 0; |
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108 | int passNumber = model_->getCurrentPassNumber(); |
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109 | // Just do once |
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110 | if (!atRoot || passNumber != 1) { |
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111 | // std::cout << "Leaving the Randomized Rounding Heuristic" << std::endl; |
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112 | return 0; |
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113 | } |
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114 | |
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115 | std::cout << "Entering the Randomized Rounding Heuristic" << std::endl; |
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116 | typedef struct { |
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117 | int numberSolutions; |
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118 | int maximumSolutions; |
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119 | int numberColumns; |
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120 | double ** solution; |
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121 | int * numberUnsatisfied; |
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122 | } clpSolution; |
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123 | |
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124 | double start = CoinCpuTime(); |
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125 | numCouldRun_++; // |
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126 | // Todo: Ask JJHF what "number of times |
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127 | // the heuristic could run" means. |
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128 | |
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129 | OsiSolverInterface * solver = model_->solver()->clone(); |
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130 | double primalTolerance ; |
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131 | solver->getDblParam(OsiPrimalTolerance, primalTolerance) ; |
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132 | OsiClpSolverInterface * clpSolver = dynamic_cast<OsiClpSolverInterface *> (solver); |
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133 | assert (clpSolver); |
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134 | ClpSimplex * simplex = clpSolver->getModelPtr(); |
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135 | |
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136 | // Initialize the structure holding the solutions for the Simplex iterations |
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137 | clpSolution solutions; |
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138 | // Set typeStruct field of ClpTrustedData struct to 1 to indicate |
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139 | // desired behavior for RandRound heuristic (which is what?) |
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140 | ClpTrustedData trustedSolutions; |
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141 | trustedSolutions.typeStruct = 1; |
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142 | trustedSolutions.data = &solutions; |
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143 | solutions.numberSolutions = 0; |
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144 | solutions.maximumSolutions = 0; |
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145 | solutions.numberColumns = simplex->numberColumns(); |
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146 | solutions.solution = NULL; |
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147 | solutions.numberUnsatisfied = NULL; |
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148 | simplex->setTrustedUserPointer(&trustedSolutions); |
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149 | |
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150 | // Solve from all slack to get some points |
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151 | simplex->allSlackBasis(); |
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152 | |
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153 | // Calling primal() invalidates pointers to some rim vectors, |
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154 | // like...row sense (!) |
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155 | simplex->primal(); |
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156 | |
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157 | // 1. Okay - so a workaround would be to copy the data I want BEFORE |
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158 | // calling primal. |
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159 | // 2. Another approach is to ask the simplex solvers NOT to mess up my |
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160 | // rims. |
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161 | // 3. See freeCachedResults() for what is getting |
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162 | // deleted. Everything else points into the structure. |
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163 | // ...or use collower and colupper rather than rowsense. |
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164 | // ..store address of where one of these |
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165 | |
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166 | // Store the basic problem information |
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167 | // -Get the number of columns, rows and rhs vector |
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168 | int numCols = clpSolver->getNumCols(); |
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169 | int numRows = clpSolver->getNumRows(); |
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170 | |
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171 | // Find the integer variables (use columnType(?)) |
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172 | // One if not continuous, that is binary or general integer) |
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173 | // columnType() = 0 continuous |
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174 | // = 1 binary |
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175 | // = 2 general integer |
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176 | bool * varClassInt = new bool[numCols]; |
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177 | const char* columnType = clpSolver->columnType(); |
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178 | int numGenInt = 0; |
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179 | for (int i = 0; i < numCols; i++) { |
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180 | if (clpSolver->isContinuous(i)) |
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181 | varClassInt[i] = 0; |
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182 | else |
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183 | varClassInt[i] = 1; |
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184 | if (columnType[i] == 2) numGenInt++; |
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185 | } |
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186 | |
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187 | // Heuristic is for problems with general integer variables. |
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188 | // If there are none, quit. |
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189 | if (numGenInt++ < 1) { |
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190 | delete [] varClassInt ; |
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191 | std::cout << "Leaving the Randomized Rounding Heuristic" << std::endl; |
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192 | return 0; |
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193 | } |
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194 | |
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195 | |
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196 | // -Get the rows sense |
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197 | const char * rowSense; |
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198 | rowSense = clpSolver->getRowSense(); |
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199 | |
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200 | // -Get the objective coefficients |
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201 | double *originalObjCoeff = CoinCopyOfArray(clpSolver->getObjCoefficients(), numCols); |
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202 | |
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203 | // -Get the matrix of the problem |
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204 | // rlh: look at using sparse representation |
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205 | double ** matrix = new double * [numRows]; |
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206 | for (int i = 0; i < numRows; i++) { |
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207 | matrix[i] = new double[numCols]; |
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208 | for (int j = 0; j < numCols; j++) |
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209 | matrix[i][j] = 0; |
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210 | } |
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211 | |
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212 | const CoinPackedMatrix* matrixByRow = clpSolver->getMatrixByRow(); |
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213 | const double * matrixElements = matrixByRow->getElements(); |
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214 | const int * matrixIndices = matrixByRow->getIndices(); |
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215 | const int * matrixStarts = matrixByRow->getVectorStarts(); |
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216 | for (int j = 0; j < numRows; j++) { |
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217 | for (int i = matrixStarts[j]; i < matrixStarts[j+1]; i++) { |
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218 | matrix[j][matrixIndices[i]] = matrixElements[i]; |
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219 | } |
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220 | } |
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221 | |
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222 | double * newObj = new double [numCols]; |
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223 | srand ( static_cast<unsigned int>(time(NULL) + 1)); |
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224 | int randNum; |
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225 | |
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226 | // Shuffle the rows: |
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227 | // Put the rows in a random order |
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228 | // so that the optimal solution is a different corner point than the |
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229 | // starting point. |
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230 | int * index = new int [numRows]; |
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231 | for (int i = 0; i < numRows; i++) |
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232 | index[i] = i; |
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233 | for (int i = 0; i < numRows; i++) { |
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234 | int temp = index[i]; |
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235 | int randNumTemp = i + intRand(numRows - i); |
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236 | index[i] = index[randNumTemp]; |
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237 | index[randNumTemp] = temp; |
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238 | } |
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239 | |
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240 | // Start finding corner points by iteratively doing the following: |
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241 | // - contruct a randomly tilted objective |
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242 | // - solve |
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243 | for (int i = 0; i < numRows; i++) { |
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244 | // TODO: that 10,000 could be a param in the member data |
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245 | if (solutions.numberSolutions > 10000) |
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246 | break; |
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247 | randNum = intRand(2); |
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248 | for (int j = 0; j < numCols; j++) { |
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249 | // for row i and column j vary the coefficient "a bit" |
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250 | if (randNum == 1) |
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251 | // if the element is zero, then set the new obj |
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252 | // coefficient to 0.1 (i.e., round up) |
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253 | if (fabs(matrix[index[i]][j]) < primalTolerance) |
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254 | newObj[j] = 0.1; |
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255 | else |
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256 | // if the element is nonzero, then increase the new obj |
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257 | // coefficient "a bit" |
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258 | newObj[j] = matrix[index[i]][j] * 1.1; |
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259 | else |
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260 | // if randnum is 2, then |
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261 | // if the element is zero, then set the new obj coeffient |
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262 | // to NEGATIVE 0.1 (i.e., round down) |
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263 | if (fabs(matrix[index[i]][j]) < primalTolerance) |
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264 | newObj[j] = -0.1; |
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265 | else |
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266 | // if the element is nonzero, then DEcrease the new obj coeffienct "a bit" |
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267 | newObj[j] = matrix[index[i]][j] * 0.9; |
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268 | } |
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269 | // Use the new "tilted" objective |
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270 | clpSolver->setObjective(newObj); |
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271 | |
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272 | // Based on the row sense, we decide whether to max or min |
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273 | if (rowSense[i] == 'L') |
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274 | clpSolver->setObjSense(-1); |
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275 | else |
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276 | clpSolver->setObjSense(1); |
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277 | |
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278 | // Solve with primal simplex |
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279 | simplex->primal(1); |
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280 | // rlh+ll: This was the original code. But we already have the |
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281 | // model pointer (it's in simplex). And, calling getModelPtr() |
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282 | // invalidates the cached data in the OsiClpSolverInterface |
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283 | // object, which means our precious rowsens is lost. So let's |
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284 | // not use the line below... |
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285 | /******* clpSolver->getModelPtr()->primal(1); */ |
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286 | printf("---------------------------------------------------------------- %d\n", i); |
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287 | } |
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288 | // Iteratively do this process until... |
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289 | // either you reach the max number of corner points (aka 10K) |
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290 | // or all the rows have been used as an objective. |
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291 | |
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292 | // Look at solutions |
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293 | int numberSolutions = solutions.numberSolutions; |
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294 | //const char * integerInfo = simplex->integerInformation(); |
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295 | //const double * columnLower = simplex->columnLower(); |
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296 | //const double * columnUpper = simplex->columnUpper(); |
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297 | printf("there are %d solutions\n", numberSolutions); |
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298 | |
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299 | // Up to here we have all the corner points |
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300 | // Now we need to do the random walks and roundings |
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301 | |
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302 | double ** cornerPoints = new double * [numberSolutions]; |
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303 | for (int j = 0; j < numberSolutions; j++) |
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304 | cornerPoints[j] = solutions.solution[j]; |
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305 | |
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306 | bool feasibility = 1; |
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307 | // rlh: use some COIN max instead of 1e30 (?) |
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308 | double bestObj = 1e30; |
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309 | std::vector< std::vector <double> > feasibles; |
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310 | int numFeasibles = 0; |
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311 | |
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312 | // Check the feasibility of the corner points |
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313 | int numCornerPoints = numberSolutions; |
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314 | |
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315 | const double * rhs = clpSolver->getRightHandSide(); |
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316 | // rlh: row sense hasn't changed. why a fresh copy? |
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317 | // Delete next line. |
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318 | rowSense = clpSolver->getRowSense(); |
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319 | |
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320 | for (int i = 0; i < numCornerPoints; i++) { |
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321 | //get the objective value for this this point |
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322 | double objValue = 0; |
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323 | for (int k = 0; k < numCols; k++) |
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324 | objValue += cornerPoints[i][k] * originalObjCoeff[k]; |
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325 | |
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326 | if (objValue < bestObj) { |
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327 | // check integer feasibility |
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328 | feasibility = 1; |
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329 | for (int j = 0; j < numCols; j++) { |
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330 | if (varClassInt[j]) { |
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331 | double closest = floor(cornerPoints[i][j] + 0.5); |
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332 | if (fabs(cornerPoints[i][j] - closest) > primalTolerance) { |
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333 | feasibility = 0; |
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334 | break; |
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335 | } |
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336 | } |
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337 | } |
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338 | // check all constraints satisfied |
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339 | if (feasibility) { |
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340 | for (int irow = 0; irow < numRows; irow++) { |
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341 | double lhs = 0; |
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342 | for (int j = 0; j < numCols; j++) { |
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343 | lhs += matrix[irow][j] * cornerPoints[i][j]; |
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344 | } |
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345 | if (rowSense[irow] == 'L' && lhs > rhs[irow] + primalTolerance) { |
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346 | feasibility = 0; |
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347 | break; |
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348 | } |
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349 | if (rowSense[irow] == 'G' && lhs < rhs[irow] - primalTolerance) { |
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350 | feasibility = 0; |
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351 | break; |
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352 | } |
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353 | if (rowSense[irow] == 'E' && (lhs - rhs[irow] > primalTolerance || lhs - rhs[irow] < -primalTolerance)) { |
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354 | feasibility = 0; |
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355 | break; |
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356 | } |
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357 | } |
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358 | } |
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359 | |
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360 | if (feasibility) { |
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361 | numFeasibles++; |
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362 | feasibles.push_back(std::vector <double> (numCols)); |
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363 | for (int k = 0; k < numCols; k++) |
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364 | feasibles[numFeasibles-1][k] = cornerPoints[i][k]; |
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365 | printf("obj: %f\n", objValue); |
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366 | if (objValue < bestObj) |
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367 | bestObj = objValue; |
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368 | } |
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369 | } |
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370 | } |
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371 | int numFeasibleCorners; |
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372 | numFeasibleCorners = numFeasibles; |
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373 | //find the center of gravity of the corner points as the first random point |
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374 | double * rp = new double[numCols]; |
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375 | for (int i = 0; i < numCols; i++) { |
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376 | rp[i] = 0; |
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377 | for (int j = 0; j < numCornerPoints; j++) { |
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378 | rp[i] += cornerPoints[j][i]; |
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379 | } |
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380 | rp[i] = rp[i] / numCornerPoints; |
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381 | } |
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382 | |
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383 | //------------------------------------------- |
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384 | //main loop: |
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385 | // -generate the next random point |
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386 | // -round the random point |
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387 | // -check the feasibility of the random point |
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388 | //------------------------------------------- |
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389 | |
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390 | srand ( static_cast<unsigned int>(time(NULL) + 1)); |
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391 | int numRandomPoints = 0; |
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392 | while (numRandomPoints < 50000) { |
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393 | numRandomPoints++; |
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394 | //generate the next random point |
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395 | int randomIndex = intRand(numCornerPoints); |
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396 | double random = CoinDrand48(); |
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397 | for (int i = 0; i < numCols; i++) { |
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398 | rp[i] = (random * (cornerPoints[randomIndex][i] - rp[i])) + rp[i]; |
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399 | } |
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400 | |
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401 | //CRISP ROUNDING |
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402 | //round the random point just generated |
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403 | double * roundRp = new double[numCols]; |
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404 | for (int i = 0; i < numCols; i++) { |
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405 | roundRp[i] = rp[i]; |
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406 | if (varClassInt[i]) { |
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407 | if (rp[i] >= 0) { |
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408 | if (fmod(rp[i], 1) > 0.5) |
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409 | roundRp[i] = floor(rp[i]) + 1; |
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410 | else |
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411 | roundRp[i] = floor(rp[i]); |
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412 | } else { |
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413 | if (fabs(fmod(rp[i], 1)) > 0.5) |
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414 | roundRp[i] = floor(rp[i]); |
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415 | else |
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416 | roundRp[i] = floor(rp[i]) + 1; |
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417 | |
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418 | } |
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419 | } |
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420 | } |
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421 | |
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422 | |
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423 | //SOFT ROUNDING |
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424 | // Look at original files for the "how to" on soft rounding; |
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425 | // Soft rounding omitted here. |
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426 | |
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427 | //Check the feasibility of the rounded random point |
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428 | // -Check the feasibility |
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429 | // -Get the rows sense |
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430 | rowSense = clpSolver->getRowSense(); |
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431 | rhs = clpSolver->getRightHandSide(); |
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432 | |
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433 | //get the objective value for this feasible point |
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434 | double objValue = 0; |
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435 | for (int i = 0; i < numCols; i++) |
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436 | objValue += roundRp[i] * originalObjCoeff[i]; |
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437 | |
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438 | if (objValue < bestObj) { |
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439 | feasibility = 1; |
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440 | for (int i = 0; i < numRows; i++) { |
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441 | double lhs = 0; |
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442 | for (int j = 0; j < numCols; j++) { |
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443 | lhs += matrix[i][j] * roundRp[j]; |
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444 | } |
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445 | if (rowSense[i] == 'L' && lhs > rhs[i] + primalTolerance) { |
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446 | feasibility = 0; |
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447 | break; |
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448 | } |
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449 | if (rowSense[i] == 'G' && lhs < rhs[i] - primalTolerance) { |
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450 | feasibility = 0; |
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451 | break; |
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452 | } |
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453 | if (rowSense[i] == 'E' && (lhs - rhs[i] > primalTolerance || lhs - rhs[i] < -primalTolerance)) { |
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454 | feasibility = 0; |
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455 | break; |
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456 | } |
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457 | } |
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458 | if (feasibility) { |
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459 | printf("Feasible Found.\n"); |
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460 | printf("%.2f\n", CoinCpuTime() - start); |
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461 | numFeasibles++; |
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462 | feasibles.push_back(std::vector <double> (numCols)); |
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463 | for (int i = 0; i < numCols; i++) |
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464 | feasibles[numFeasibles-1][i] = roundRp[i]; |
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465 | printf("obj: %f\n", objValue); |
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466 | if (objValue < bestObj) |
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467 | bestObj = objValue; |
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468 | } |
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469 | } |
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470 | delete [] roundRp; |
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471 | } |
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472 | printf("Number of Feasible Corners: %d\n", numFeasibleCorners); |
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473 | printf("Number of Feasibles Found: %d\n", numFeasibles); |
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474 | if (numFeasibles > 0) |
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475 | printf("Best Objective: %f\n", bestObj); |
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476 | printf("time: %.2f\n", CoinCpuTime() - start); |
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477 | |
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478 | if (numFeasibles == 0) { |
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479 | // cleanup |
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480 | delete [] varClassInt; |
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481 | for (int i = 0; i < numRows; i++) |
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482 | delete matrix[i]; |
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483 | delete [] matrix; |
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484 | delete [] newObj; |
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485 | delete [] index; |
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486 | for (int i = 0; i < numberSolutions; i++) |
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487 | delete cornerPoints[i]; |
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488 | delete [] cornerPoints; |
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489 | delete [] rp; |
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490 | return 0; |
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491 | } |
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492 | |
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493 | // We found something better |
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494 | solutionValue = bestObj; |
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495 | for (int k = 0; k < numCols; k++) { |
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496 | betterSolution[k] = feasibles[numFeasibles-1][k]; |
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497 | } |
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498 | delete [] varClassInt; |
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499 | for (int i = 0; i < numRows; i++) |
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500 | delete matrix[i]; |
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501 | delete [] matrix; |
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502 | delete [] newObj; |
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503 | delete [] index; |
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504 | for (int i = 0; i < numberSolutions; i++) |
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505 | delete cornerPoints[i]; |
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506 | delete [] cornerPoints; |
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507 | delete [] rp; |
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508 | std::cout << "Leaving the Randomized Rounding Heuristic" << std::endl; |
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509 | return 1; |
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510 | |
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511 | } |
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512 | // update model |
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513 | void CbcHeuristicRandRound::setModel(CbcModel * model) |
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514 | { |
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515 | CbcHeuristic::setModel(model); |
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516 | } |
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517 | |
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518 | |
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