[1271] | 1 | /* $Id: CbcCutGenerator.cpp 2105 2015-01-05 13:11:11Z tkr $ */ |
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[2] | 2 | // Copyright (C) 2003, International Business Machines |
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| 3 | // Corporation and others. All Rights Reserved. |
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[1573] | 4 | // This code is licensed under the terms of the Eclipse Public License (EPL). |
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| 5 | |
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[2] | 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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[838] | 10 | #include "CbcConfig.h" |
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[2] | 11 | #include <cassert> |
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[904] | 12 | #include <cstdlib> |
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[2] | 13 | #include <cmath> |
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| 14 | #include <cfloat> |
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| 15 | |
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[838] | 16 | #ifdef COIN_HAS_CLP |
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| 17 | #include "OsiClpSolverInterface.hpp" |
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| 18 | #else |
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[2] | 19 | #include "OsiSolverInterface.hpp" |
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[838] | 20 | #endif |
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[1315] | 21 | //#define CGL_DEBUG 1 |
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| 22 | #ifdef CGL_DEBUG |
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| 23 | #include "OsiRowCutDebugger.hpp" |
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| 24 | #endif |
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[2] | 25 | #include "CbcModel.hpp" |
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| 26 | #include "CbcMessage.hpp" |
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| 27 | #include "CbcCutGenerator.hpp" |
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[640] | 28 | #include "CbcBranchDynamic.hpp" |
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[2] | 29 | #include "CglProbing.hpp" |
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[66] | 30 | #include "CoinTime.hpp" |
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[2] | 31 | |
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[1286] | 32 | // Default Constructor |
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[2] | 33 | CbcCutGenerator::CbcCutGenerator () |
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[1286] | 34 | : timeInCutGenerator_(0.0), |
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| 35 | model_(NULL), |
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| 36 | generator_(NULL), |
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| 37 | generatorName_(NULL), |
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| 38 | whenCutGenerator_(-1), |
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| 39 | whenCutGeneratorInSub_(-100), |
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| 40 | switchOffIfLessThan_(0), |
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| 41 | depthCutGenerator_(-1), |
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| 42 | depthCutGeneratorInSub_(-1), |
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| 43 | inaccuracy_(0), |
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| 44 | numberTimes_(0), |
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| 45 | numberCuts_(0), |
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| 46 | numberElements_(0), |
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| 47 | numberColumnCuts_(0), |
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| 48 | numberCutsActive_(0), |
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| 49 | numberCutsAtRoot_(0), |
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| 50 | numberActiveCutsAtRoot_(0), |
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| 51 | numberShortCutsAtRoot_(0), |
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[1880] | 52 | switches_(1), |
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| 53 | maximumTries_(-1) |
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[2] | 54 | { |
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| 55 | } |
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| 56 | // Normal constructor |
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[1286] | 57 | CbcCutGenerator::CbcCutGenerator(CbcModel * model, CglCutGenerator * generator, |
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| 58 | int howOften, const char * name, |
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| 59 | bool normal, bool atSolution, |
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| 60 | bool infeasible, int howOftenInSub, |
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| 61 | int whatDepth, int whatDepthInSub, |
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[202] | 62 | int switchOffIfLessThan) |
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[1286] | 63 | : |
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| 64 | timeInCutGenerator_(0.0), |
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| 65 | depthCutGenerator_(whatDepth), |
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| 66 | depthCutGeneratorInSub_(whatDepthInSub), |
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| 67 | inaccuracy_(0), |
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| 68 | numberTimes_(0), |
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| 69 | numberCuts_(0), |
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| 70 | numberElements_(0), |
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| 71 | numberColumnCuts_(0), |
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| 72 | numberCutsActive_(0), |
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| 73 | numberCutsAtRoot_(0), |
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| 74 | numberActiveCutsAtRoot_(0), |
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| 75 | numberShortCutsAtRoot_(0), |
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[1880] | 76 | switches_(1), |
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| 77 | maximumTries_(-1) |
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[2] | 78 | { |
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[1286] | 79 | if (howOften < -1900) { |
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| 80 | setGlobalCuts(true); |
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| 81 | howOften += 2000; |
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| 82 | } else if (howOften < -900) { |
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| 83 | setGlobalCutsAtRoot(true); |
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| 84 | howOften += 1000; |
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| 85 | } |
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| 86 | model_ = model; |
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| 87 | generator_ = generator->clone(); |
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| 88 | generator_->refreshSolver(model_->solver()); |
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| 89 | setNeedsOptimalBasis(generator_->needsOptimalBasis()); |
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| 90 | whenCutGenerator_ = howOften; |
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| 91 | whenCutGeneratorInSub_ = howOftenInSub; |
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| 92 | switchOffIfLessThan_ = switchOffIfLessThan; |
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| 93 | if (name) |
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[1336] | 94 | generatorName_ = CoinStrdup(name); |
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[1286] | 95 | else |
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[1336] | 96 | generatorName_ = CoinStrdup("Unknown"); |
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[1286] | 97 | setNormal(normal); |
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| 98 | setAtSolution(atSolution); |
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| 99 | setWhenInfeasible(infeasible); |
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[2] | 100 | } |
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| 101 | |
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[1286] | 102 | // Copy constructor |
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[2] | 103 | CbcCutGenerator::CbcCutGenerator ( const CbcCutGenerator & rhs) |
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| 104 | { |
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| 105 | model_ = rhs.model_; |
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[1286] | 106 | generator_ = rhs.generator_->clone(); |
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| 107 | //generator_->refreshSolver(model_->solver()); |
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| 108 | whenCutGenerator_ = rhs.whenCutGenerator_; |
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[5] | 109 | whenCutGeneratorInSub_ = rhs.whenCutGeneratorInSub_; |
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[202] | 110 | switchOffIfLessThan_ = rhs.switchOffIfLessThan_; |
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[1286] | 111 | depthCutGenerator_ = rhs.depthCutGenerator_; |
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[13] | 112 | depthCutGeneratorInSub_ = rhs.depthCutGeneratorInSub_; |
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[1336] | 113 | generatorName_ = CoinStrdup(rhs.generatorName_); |
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[1271] | 114 | switches_ = rhs.switches_; |
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[1880] | 115 | maximumTries_ = rhs.maximumTries_; |
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[66] | 116 | timeInCutGenerator_ = rhs.timeInCutGenerator_; |
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[1271] | 117 | savedCuts_ = rhs.savedCuts_; |
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[1132] | 118 | inaccuracy_ = rhs.inaccuracy_; |
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[2] | 119 | numberTimes_ = rhs.numberTimes_; |
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| 120 | numberCuts_ = rhs.numberCuts_; |
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[1271] | 121 | numberElements_ = rhs.numberElements_; |
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[259] | 122 | numberColumnCuts_ = rhs.numberColumnCuts_; |
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[2] | 123 | numberCutsActive_ = rhs.numberCutsActive_; |
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[640] | 124 | numberCutsAtRoot_ = rhs.numberCutsAtRoot_; |
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| 125 | numberActiveCutsAtRoot_ = rhs.numberActiveCutsAtRoot_; |
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[1271] | 126 | numberShortCutsAtRoot_ = rhs.numberShortCutsAtRoot_; |
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[2] | 127 | } |
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| 128 | |
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[1286] | 129 | // Assignment operator |
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| 130 | CbcCutGenerator & |
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| 131 | CbcCutGenerator::operator=( const CbcCutGenerator & rhs) |
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| 132 | { |
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| 133 | if (this != &rhs) { |
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| 134 | delete generator_; |
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| 135 | free(generatorName_); |
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| 136 | model_ = rhs.model_; |
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| 137 | generator_ = rhs.generator_->clone(); |
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| 138 | generator_->refreshSolver(model_->solver()); |
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| 139 | whenCutGenerator_ = rhs.whenCutGenerator_; |
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| 140 | whenCutGeneratorInSub_ = rhs.whenCutGeneratorInSub_; |
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| 141 | switchOffIfLessThan_ = rhs.switchOffIfLessThan_; |
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| 142 | depthCutGenerator_ = rhs.depthCutGenerator_; |
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| 143 | depthCutGeneratorInSub_ = rhs.depthCutGeneratorInSub_; |
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[1336] | 144 | generatorName_ = CoinStrdup(rhs.generatorName_); |
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[1286] | 145 | switches_ = rhs.switches_; |
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[1880] | 146 | maximumTries_ = rhs.maximumTries_; |
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[1286] | 147 | timeInCutGenerator_ = rhs.timeInCutGenerator_; |
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| 148 | savedCuts_ = rhs.savedCuts_; |
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| 149 | inaccuracy_ = rhs.inaccuracy_; |
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| 150 | numberTimes_ = rhs.numberTimes_; |
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| 151 | numberCuts_ = rhs.numberCuts_; |
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| 152 | numberElements_ = rhs.numberElements_; |
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| 153 | numberColumnCuts_ = rhs.numberColumnCuts_; |
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| 154 | numberCutsActive_ = rhs.numberCutsActive_; |
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| 155 | numberCutsAtRoot_ = rhs.numberCutsAtRoot_; |
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| 156 | numberActiveCutsAtRoot_ = rhs.numberActiveCutsAtRoot_; |
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| 157 | numberShortCutsAtRoot_ = rhs.numberShortCutsAtRoot_; |
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| 158 | } |
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| 159 | return *this; |
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| 160 | } |
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| 161 | |
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| 162 | // Destructor |
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[2] | 163 | CbcCutGenerator::~CbcCutGenerator () |
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| 164 | { |
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[1286] | 165 | free(generatorName_); |
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| 166 | delete generator_; |
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[2] | 167 | } |
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| 168 | |
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| 169 | /* This is used to refresh any inforamtion. |
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| 170 | It also refreshes the solver in the cut generator |
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[1286] | 171 | in case generator wants to do some work |
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[2] | 172 | */ |
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[1286] | 173 | void |
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[2] | 174 | CbcCutGenerator::refreshModel(CbcModel * model) |
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| 175 | { |
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[1286] | 176 | model_ = model; |
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[2094] | 177 | // added test - helps if generator not thread safe |
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| 178 | if (whenCutGenerator_!=-100) |
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| 179 | generator_->refreshSolver(model_->solver()); |
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[2] | 180 | } |
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| 181 | /* Generate cuts for the model data contained in si. |
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| 182 | The generated cuts are inserted into and returned in the |
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| 183 | collection of cuts cs. |
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| 184 | */ |
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| 185 | bool |
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[931] | 186 | CbcCutGenerator::generateCuts( OsiCuts & cs , int fullScan, OsiSolverInterface * solver, CbcNode * node) |
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[2] | 187 | { |
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[1362] | 188 | /* |
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| 189 | Make some decisions about whether we'll generate cuts. First convert |
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| 190 | whenCutGenerator_ to a set of canonical values for comparison to the node |
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| 191 | count. |
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| 192 | |
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| 193 | 0 < mod 1000000, with a result of 0 forced to 1 |
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| 194 | -99 <= <= 0 convert to 1 |
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| 195 | -100 = Off, period |
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| 196 | */ |
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| 197 | int depth; |
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[1286] | 198 | if (node) |
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| 199 | depth = node->depth(); |
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| 200 | else |
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| 201 | depth = 0; |
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| 202 | int howOften = whenCutGenerator_; |
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| 203 | if (dynamic_cast<CglProbing*>(generator_)) { |
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| 204 | if (howOften == -100 && model_->doCutsNow(3)) { |
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| 205 | howOften = 1; // do anyway |
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| 206 | } |
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[1015] | 207 | } |
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[1286] | 208 | if (howOften == -100) |
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| 209 | return false; |
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[1880] | 210 | int pass = model_->getCurrentPassNumber() - 1; |
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| 211 | if (maximumTries_>0) { |
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| 212 | // howOften means what it says |
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| 213 | if ((pass%howOften)!=0||depth) |
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| 214 | return false; |
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| 215 | else |
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| 216 | howOften=1; |
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| 217 | } |
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[1286] | 218 | if (howOften > 0) |
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| 219 | howOften = howOften % 1000000; |
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| 220 | else |
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| 221 | howOften = 1; |
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| 222 | if (!howOften) |
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| 223 | howOften = 1; |
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| 224 | bool returnCode = false; |
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| 225 | //OsiSolverInterface * solver = model_->solver(); |
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| 226 | // Reset cuts on first pass |
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| 227 | if (!pass) |
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| 228 | savedCuts_ = OsiCuts(); |
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[1362] | 229 | /* |
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| 230 | Determine if we should generate cuts based on node count. |
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| 231 | */ |
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| 232 | bool doThis = (model_->getNodeCount() % howOften) == 0; |
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| 233 | /* |
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| 234 | If the user has provided a depth specification, it will override the node |
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| 235 | count specification. |
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| 236 | */ |
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| 237 | if (depthCutGenerator_ > 0) { |
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[1286] | 238 | doThis = (depth % depthCutGenerator_) == 0; |
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| 239 | if (depth < depthCutGenerator_) |
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| 240 | doThis = true; // and also at top of tree |
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| 241 | } |
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[1362] | 242 | /* |
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| 243 | A few magic numbers ... |
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| 244 | |
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| 245 | The distinction between -100 and 100 for howOften is that we can override 100 |
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| 246 | with fullScan. -100 means no cuts, period. As does the magic number -200 for |
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| 247 | whenCutGeneratorInSub_. |
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| 248 | */ |
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| 249 | |
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[1286] | 250 | // But turn off if 100 |
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| 251 | if (howOften == 100) |
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| 252 | doThis = false; |
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| 253 | // Switch off if special setting |
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| 254 | if (whenCutGeneratorInSub_ == -200 && model_->parentModel()) { |
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| 255 | fullScan = 0; |
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| 256 | doThis = false; |
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| 257 | } |
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| 258 | if (fullScan || doThis) { |
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| 259 | CoinThreadRandom * randomNumberGenerator = NULL; |
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[1271] | 260 | #ifdef COIN_HAS_CLP |
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[1286] | 261 | { |
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| 262 | OsiClpSolverInterface * clpSolver |
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| 263 | = dynamic_cast<OsiClpSolverInterface *> (solver); |
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| 264 | if (clpSolver) |
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| 265 | randomNumberGenerator = |
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| 266 | clpSolver->getModelPtr()->randomNumberGenerator(); |
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| 267 | } |
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[1271] | 268 | #endif |
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[1286] | 269 | double time1 = 0.0; |
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| 270 | if (timing()) |
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| 271 | time1 = CoinCpuTime(); |
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| 272 | //#define CBC_DEBUG |
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| 273 | int numberRowCutsBefore = cs.sizeRowCuts() ; |
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| 274 | int numberColumnCutsBefore = cs.sizeColCuts() ; |
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[1393] | 275 | #ifdef JJF_ZERO |
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[1286] | 276 | int cutsBefore = cs.sizeCuts(); |
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[931] | 277 | #endif |
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[1286] | 278 | CglTreeInfo info; |
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| 279 | info.level = depth; |
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| 280 | info.pass = pass; |
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| 281 | info.formulation_rows = model_->numberRowsAtContinuous(); |
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| 282 | info.inTree = node != NULL; |
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| 283 | info.randomNumberGenerator = randomNumberGenerator; |
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| 284 | info.options = (globalCutsAtRoot()) ? 8 : 0; |
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| 285 | if (ineffectualCuts()) |
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| 286 | info.options |= 32; |
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| 287 | if (globalCuts()) |
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| 288 | info.options |= 16; |
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| 289 | if (fullScan < 0) |
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| 290 | info.options |= 128; |
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[1656] | 291 | if (whetherInMustCallAgainMode()) |
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| 292 | info.options |= 1024; |
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[1286] | 293 | // See if we want alternate set of cuts |
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| 294 | if ((model_->moreSpecialOptions()&16384) != 0) |
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| 295 | info.options |= 256; |
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| 296 | if (model_->parentModel()) |
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| 297 | info.options |= 512; |
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| 298 | // above had &&!model_->parentModel()&&depth<2) |
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| 299 | incrementNumberTimesEntered(); |
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| 300 | CglProbing* generator = |
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| 301 | dynamic_cast<CglProbing*>(generator_); |
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[1880] | 302 | //if (!depth&&!pass) |
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| 303 | //printf("Cut generator %s when %d\n",generatorName_,whenCutGenerator_); |
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[1286] | 304 | if (!generator) { |
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| 305 | // Pass across model information in case it could be useful |
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| 306 | //void * saveData = solver->getApplicationData(); |
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| 307 | //solver->setApplicationData(model_); |
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| 308 | generator_->generateCuts(*solver, cs, info); |
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| 309 | //solver->setApplicationData(saveData); |
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| 310 | } else { |
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| 311 | // Probing - return tight column bounds |
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| 312 | CglTreeProbingInfo * info2 = model_->probingInfo(); |
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| 313 | bool doCuts = false; |
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| 314 | if (info2 && !depth) { |
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| 315 | info2->options = (globalCutsAtRoot()) ? 8 : 0; |
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| 316 | info2->level = depth; |
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| 317 | info2->pass = pass; |
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| 318 | info2->formulation_rows = model_->numberRowsAtContinuous(); |
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| 319 | info2->inTree = node != NULL; |
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| 320 | info2->randomNumberGenerator = randomNumberGenerator; |
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| 321 | generator->generateCutsAndModify(*solver, cs, info2); |
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| 322 | doCuts = true; |
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| 323 | } else if (depth) { |
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| 324 | /* The idea behind this is that probing may work in a different |
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| 325 | way deep in tree. So every now and then try various |
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| 326 | combinations to see what works. |
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| 327 | */ |
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[1271] | 328 | #define TRY_NOW_AND_THEN |
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| 329 | #ifdef TRY_NOW_AND_THEN |
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[1286] | 330 | if ((numberTimes_ == 200 || (numberTimes_ > 200 && (numberTimes_ % 2000) == 0)) |
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| 331 | && !model_->parentModel() && info.formulation_rows > 200) { |
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| 332 | /* In tree, every now and then try various combinations |
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| 333 | maxStack, maxProbe (last 5 digits) |
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| 334 | 123 is special and means CglProbing will try and |
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| 335 | be intelligent. |
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| 336 | */ |
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| 337 | int test[] = { |
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| 338 | 100123, |
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| 339 | 199999, |
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| 340 | 200123, |
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| 341 | 299999, |
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| 342 | 500123, |
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| 343 | 599999, |
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| 344 | 1000123, |
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| 345 | 1099999, |
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| 346 | 2000123, |
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| 347 | 2099999 |
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| 348 | }; |
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| 349 | int n = static_cast<int> (sizeof(test) / sizeof(int)); |
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| 350 | int saveStack = generator->getMaxLook(); |
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| 351 | int saveNumber = generator->getMaxProbe(); |
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| 352 | int kr1 = 0; |
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| 353 | int kc1 = 0; |
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| 354 | int bestStackTree = -1; |
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| 355 | int bestNumberTree = -1; |
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| 356 | for (int i = 0; i < n; i++) { |
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| 357 | //OsiCuts cs2 = cs; |
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| 358 | int stack = test[i] / 100000; |
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| 359 | int number = test[i] - 100000 * stack; |
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| 360 | generator->setMaxLook(stack); |
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| 361 | generator->setMaxProbe(number); |
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| 362 | int numberRowCutsBefore = cs.sizeRowCuts() ; |
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| 363 | int numberColumnCutsBefore = cs.sizeColCuts() ; |
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| 364 | generator_->generateCuts(*solver, cs, info); |
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| 365 | int numberRowCuts = cs.sizeRowCuts() - numberRowCutsBefore ; |
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| 366 | int numberColumnCuts = cs.sizeColCuts() - numberColumnCutsBefore ; |
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[1015] | 367 | #ifdef CLP_INVESTIGATE |
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[1286] | 368 | if (numberRowCuts < kr1 || numberColumnCuts < kc1) |
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| 369 | printf("Odd "); |
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[1271] | 370 | #endif |
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[1286] | 371 | if (numberRowCuts > kr1 || numberColumnCuts > kc1) { |
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[1271] | 372 | #ifdef CLP_INVESTIGATE |
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[1286] | 373 | printf("*** "); |
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[1271] | 374 | #endif |
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[1286] | 375 | kr1 = numberRowCuts; |
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| 376 | kc1 = numberColumnCuts; |
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| 377 | bestStackTree = stack; |
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| 378 | bestNumberTree = number; |
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| 379 | doCuts = true; |
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| 380 | } |
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[1271] | 381 | #ifdef CLP_INVESTIGATE |
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[1286] | 382 | printf("maxStack %d number %d gives %d row cuts and %d column cuts\n", |
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| 383 | stack, number, numberRowCuts, numberColumnCuts); |
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[1015] | 384 | #endif |
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[1286] | 385 | } |
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| 386 | generator->setMaxLook(saveStack); |
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| 387 | generator->setMaxProbe(saveNumber); |
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| 388 | if (bestStackTree > 0) { |
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| 389 | generator->setMaxLook(bestStackTree); |
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| 390 | generator->setMaxProbe(bestNumberTree); |
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[1015] | 391 | #ifdef CLP_INVESTIGATE |
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[1286] | 392 | printf("RRNumber %d -> %d, stack %d -> %d\n", |
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| 393 | saveNumber, bestNumberTree, saveStack, bestStackTree); |
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[1015] | 394 | #endif |
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[1286] | 395 | } else { |
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| 396 | // no good |
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| 397 | generator->setMaxLook(0); |
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[1015] | 398 | #ifdef CLP_INVESTIGATE |
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[1286] | 399 | printf("RRSwitching off number %d -> %d, stack %d -> %d\n", |
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| 400 | saveNumber, saveNumber, saveStack, 1); |
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[1015] | 401 | #endif |
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[1286] | 402 | } |
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| 403 | } |
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[1015] | 404 | #endif |
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[1286] | 405 | if (generator->getMaxLook() > 0 && !doCuts) { |
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| 406 | generator->generateCutsAndModify(*solver, cs, &info); |
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| 407 | doCuts = true; |
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| 408 | } |
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| 409 | } else { |
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| 410 | // at root - don't always do |
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| 411 | if (pass < 15 || (pass&1) == 0) { |
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| 412 | generator->generateCutsAndModify(*solver, cs, &info); |
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| 413 | doCuts = true; |
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| 414 | } |
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| 415 | } |
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| 416 | if (doCuts && generator->tightLower()) { |
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| 417 | // probing may have tightened bounds - check |
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| 418 | const double * tightLower = generator->tightLower(); |
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| 419 | const double * lower = solver->getColLower(); |
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| 420 | const double * tightUpper = generator->tightUpper(); |
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| 421 | const double * upper = solver->getColUpper(); |
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| 422 | const double * solution = solver->getColSolution(); |
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| 423 | int j; |
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| 424 | int numberColumns = solver->getNumCols(); |
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| 425 | double primalTolerance = 1.0e-8; |
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| 426 | const char * tightenBounds = generator->tightenBounds(); |
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[1315] | 427 | #ifdef CGL_DEBUG |
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| 428 | const OsiRowCutDebugger * debugger = solver->getRowCutDebugger(); |
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| 429 | if (debugger && debugger->onOptimalPath(*solver)) { |
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| 430 | printf("On optimal path CbcCut\n"); |
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| 431 | int nCols = solver->getNumCols(); |
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| 432 | int i; |
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| 433 | const double * optimal = debugger->optimalSolution(); |
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| 434 | const double * objective = solver->getObjCoefficients(); |
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| 435 | double objval1 = 0.0, objval2 = 0.0; |
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| 436 | for (i = 0; i < nCols; i++) { |
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| 437 | #if CGL_DEBUG>1 |
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| 438 | printf("%d %g %g %g %g\n", i, lower[i], solution[i], upper[i], optimal[i]); |
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| 439 | #endif |
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| 440 | objval1 += solution[i] * objective[i]; |
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| 441 | objval2 += optimal[i] * objective[i]; |
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| 442 | assert(optimal[i] >= lower[i] - 1.0e-5 && optimal[i] <= upper[i] + 1.0e-5); |
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| 443 | assert(optimal[i] >= tightLower[i] - 1.0e-5 && optimal[i] <= tightUpper[i] + 1.0e-5); |
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| 444 | } |
---|
| 445 | printf("current obj %g, integer %g\n", objval1, objval2); |
---|
| 446 | } |
---|
| 447 | #endif |
---|
| 448 | bool feasible = true; |
---|
[1286] | 449 | if ((model_->getThreadMode()&2) == 0) { |
---|
| 450 | for (j = 0; j < numberColumns; j++) { |
---|
| 451 | if (solver->isInteger(j)) { |
---|
| 452 | if (tightUpper[j] < upper[j]) { |
---|
| 453 | double nearest = floor(tightUpper[j] + 0.5); |
---|
| 454 | //assert (fabs(tightUpper[j]-nearest)<1.0e-5); may be infeasible |
---|
| 455 | solver->setColUpper(j, nearest); |
---|
| 456 | if (nearest < solution[j] - primalTolerance) |
---|
| 457 | returnCode = true; |
---|
| 458 | } |
---|
| 459 | if (tightLower[j] > lower[j]) { |
---|
| 460 | double nearest = floor(tightLower[j] + 0.5); |
---|
| 461 | //assert (fabs(tightLower[j]-nearest)<1.0e-5); may be infeasible |
---|
| 462 | solver->setColLower(j, nearest); |
---|
| 463 | if (nearest > solution[j] + primalTolerance) |
---|
| 464 | returnCode = true; |
---|
| 465 | } |
---|
| 466 | } else { |
---|
| 467 | if (upper[j] > lower[j]) { |
---|
| 468 | if (tightUpper[j] == tightLower[j]) { |
---|
| 469 | // fix |
---|
[1315] | 470 | //if (tightLower[j]!=lower[j]) |
---|
[1286] | 471 | solver->setColLower(j, tightLower[j]); |
---|
[1315] | 472 | //if (tightUpper[j]!=upper[j]) |
---|
[1286] | 473 | solver->setColUpper(j, tightUpper[j]); |
---|
| 474 | if (tightLower[j] > solution[j] + primalTolerance || |
---|
| 475 | tightUpper[j] < solution[j] - primalTolerance) |
---|
| 476 | returnCode = true; |
---|
| 477 | } else if (tightenBounds && tightenBounds[j]) { |
---|
| 478 | solver->setColLower(j, CoinMax(tightLower[j], lower[j])); |
---|
| 479 | solver->setColUpper(j, CoinMin(tightUpper[j], upper[j])); |
---|
| 480 | if (tightLower[j] > solution[j] + primalTolerance || |
---|
| 481 | tightUpper[j] < solution[j] - primalTolerance) |
---|
| 482 | returnCode = true; |
---|
| 483 | } |
---|
| 484 | } |
---|
| 485 | } |
---|
[1315] | 486 | if (upper[j] < lower[j] - 1.0e-3) { |
---|
| 487 | feasible = false; |
---|
| 488 | break; |
---|
| 489 | } |
---|
[1286] | 490 | } |
---|
| 491 | } else { |
---|
| 492 | CoinPackedVector lbs; |
---|
| 493 | CoinPackedVector ubs; |
---|
| 494 | int numberChanged = 0; |
---|
| 495 | bool ifCut = false; |
---|
| 496 | for (j = 0; j < numberColumns; j++) { |
---|
| 497 | if (solver->isInteger(j)) { |
---|
| 498 | if (tightUpper[j] < upper[j]) { |
---|
| 499 | double nearest = floor(tightUpper[j] + 0.5); |
---|
| 500 | //assert (fabs(tightUpper[j]-nearest)<1.0e-5); may be infeasible |
---|
| 501 | ubs.insert(j, nearest); |
---|
| 502 | numberChanged++; |
---|
| 503 | if (nearest < solution[j] - primalTolerance) |
---|
| 504 | ifCut = true; |
---|
| 505 | } |
---|
| 506 | if (tightLower[j] > lower[j]) { |
---|
| 507 | double nearest = floor(tightLower[j] + 0.5); |
---|
| 508 | //assert (fabs(tightLower[j]-nearest)<1.0e-5); may be infeasible |
---|
| 509 | lbs.insert(j, nearest); |
---|
| 510 | numberChanged++; |
---|
| 511 | if (nearest > solution[j] + primalTolerance) |
---|
| 512 | ifCut = true; |
---|
| 513 | } |
---|
| 514 | } else { |
---|
| 515 | if (upper[j] > lower[j]) { |
---|
| 516 | if (tightUpper[j] == tightLower[j]) { |
---|
| 517 | // fix |
---|
| 518 | lbs.insert(j, tightLower[j]); |
---|
| 519 | ubs.insert(j, tightUpper[j]); |
---|
| 520 | if (tightLower[j] > solution[j] + primalTolerance || |
---|
| 521 | tightUpper[j] < solution[j] - primalTolerance) |
---|
| 522 | ifCut = true; |
---|
| 523 | } else if (tightenBounds && tightenBounds[j]) { |
---|
| 524 | lbs.insert(j, CoinMax(tightLower[j], lower[j])); |
---|
| 525 | ubs.insert(j, CoinMin(tightUpper[j], upper[j])); |
---|
| 526 | if (tightLower[j] > solution[j] + primalTolerance || |
---|
| 527 | tightUpper[j] < solution[j] - primalTolerance) |
---|
| 528 | ifCut = true; |
---|
| 529 | } |
---|
| 530 | } |
---|
| 531 | } |
---|
[1315] | 532 | if (upper[j] < lower[j] - 1.0e-3) { |
---|
| 533 | feasible = false; |
---|
| 534 | break; |
---|
| 535 | } |
---|
[1286] | 536 | } |
---|
| 537 | if (numberChanged) { |
---|
| 538 | OsiColCut cc; |
---|
| 539 | cc.setUbs(ubs); |
---|
| 540 | cc.setLbs(lbs); |
---|
| 541 | if (ifCut) { |
---|
| 542 | cc.setEffectiveness(100.0); |
---|
| 543 | } else { |
---|
| 544 | cc.setEffectiveness(1.0e-5); |
---|
| 545 | } |
---|
| 546 | cs.insert(cc); |
---|
| 547 | } |
---|
| 548 | } |
---|
[1315] | 549 | if (!feasible) { |
---|
| 550 | // not feasible -add infeasible cut |
---|
| 551 | OsiRowCut rc; |
---|
[1643] | 552 | rc.setLb(COIN_DBL_MAX); |
---|
[1315] | 553 | rc.setUb(0.0); |
---|
| 554 | cs.insert(rc); |
---|
| 555 | } |
---|
[1286] | 556 | } |
---|
| 557 | //if (!solver->basisIsAvailable()) |
---|
[1656] | 558 | //returnCode=true; |
---|
| 559 | if (!returnCode) { |
---|
| 560 | // bounds changed but still optimal |
---|
| 561 | #ifdef COIN_HAS_CLP |
---|
| 562 | OsiClpSolverInterface * clpSolver |
---|
| 563 | = dynamic_cast<OsiClpSolverInterface *> (solver); |
---|
| 564 | if (clpSolver) { |
---|
| 565 | clpSolver->setLastAlgorithm(2); |
---|
| 566 | } |
---|
| 567 | #endif |
---|
| 568 | } |
---|
[1393] | 569 | #ifdef JJF_ZERO |
---|
[1286] | 570 | // Pass across info to pseudocosts |
---|
| 571 | char * mark = new char[numberColumns]; |
---|
| 572 | memset(mark, 0, numberColumns); |
---|
| 573 | int nLook = generator->numberThisTime(); |
---|
| 574 | const int * lookedAt = generator->lookedAt(); |
---|
| 575 | const int * fixedDown = generator->fixedDown(); |
---|
| 576 | const int * fixedUp = generator->fixedUp(); |
---|
| 577 | for (j = 0; j < nLook; j++) |
---|
| 578 | mark[lookedAt[j]] = 1; |
---|
| 579 | int numberObjects = model_->numberObjects(); |
---|
| 580 | for (int i = 0; i < numberObjects; i++) { |
---|
| 581 | CbcSimpleIntegerDynamicPseudoCost * obj1 = |
---|
| 582 | dynamic_cast <CbcSimpleIntegerDynamicPseudoCost *>(model_->modifiableObject(i)) ; |
---|
| 583 | if (obj1) { |
---|
| 584 | int iColumn = obj1->columnNumber(); |
---|
| 585 | if (mark[iColumn]) |
---|
| 586 | obj1->setProbingInformation(fixedDown[iColumn], fixedUp[iColumn]); |
---|
| 587 | } |
---|
| 588 | } |
---|
| 589 | delete [] mark; |
---|
[640] | 590 | #endif |
---|
[1286] | 591 | } |
---|
| 592 | CbcCutModifier * modifier = model_->cutModifier(); |
---|
| 593 | if (modifier) { |
---|
| 594 | int numberRowCutsAfter = cs.sizeRowCuts() ; |
---|
| 595 | int k ; |
---|
| 596 | int nOdd = 0; |
---|
| 597 | //const OsiSolverInterface * solver = model_->solver(); |
---|
| 598 | for (k = numberRowCutsAfter - 1; k >= numberRowCutsBefore; k--) { |
---|
| 599 | OsiRowCut & thisCut = cs.rowCut(k) ; |
---|
| 600 | int returnCode = modifier->modify(solver, thisCut); |
---|
| 601 | if (returnCode) { |
---|
| 602 | nOdd++; |
---|
| 603 | if (returnCode == 3) |
---|
| 604 | cs.eraseRowCut(k); |
---|
| 605 | } |
---|
| 606 | } |
---|
| 607 | if (nOdd) |
---|
[1641] | 608 | COIN_DETAIL_PRINT(printf("Cut generator %s produced %d cuts of which %d were modified\n", |
---|
| 609 | generatorName_, numberRowCutsAfter - numberRowCutsBefore, nOdd)); |
---|
[1286] | 610 | } |
---|
| 611 | { |
---|
| 612 | // make all row cuts without test for duplicate |
---|
| 613 | int numberRowCutsAfter = cs.sizeRowCuts() ; |
---|
| 614 | int k ; |
---|
[1315] | 615 | #ifdef CGL_DEBUG |
---|
| 616 | const OsiRowCutDebugger * debugger = solver->getRowCutDebugger(); |
---|
| 617 | #endif |
---|
[1286] | 618 | for (k = numberRowCutsBefore; k < numberRowCutsAfter; k++) { |
---|
| 619 | OsiRowCut * thisCut = cs.rowCutPtr(k) ; |
---|
[1315] | 620 | #ifdef CGL_DEBUG |
---|
[2105] | 621 | if (debugger && debugger->onOptimalPath(*solver)) { |
---|
[1315] | 622 | assert(!debugger->invalidCut(*thisCut)); |
---|
[2105] | 623 | if(debugger->invalidCut(*thisCut)) |
---|
| 624 | abort(); |
---|
| 625 | } |
---|
[1315] | 626 | #endif |
---|
[1286] | 627 | thisCut->mutableRow().setTestForDuplicateIndex(false); |
---|
| 628 | } |
---|
| 629 | } |
---|
| 630 | // Add in saved cuts if violated |
---|
| 631 | if (false && !depth) { |
---|
| 632 | const double * solution = solver->getColSolution(); |
---|
| 633 | double primalTolerance = 1.0e-7; |
---|
| 634 | int numberCuts = savedCuts_.sizeRowCuts() ; |
---|
| 635 | for (int k = numberCuts - 1; k >= 0; k--) { |
---|
| 636 | const OsiRowCut * thisCut = savedCuts_.rowCutPtr(k) ; |
---|
| 637 | double sum = 0.0; |
---|
| 638 | int n = thisCut->row().getNumElements(); |
---|
| 639 | const int * column = thisCut->row().getIndices(); |
---|
| 640 | const double * element = thisCut->row().getElements(); |
---|
| 641 | assert (n); |
---|
| 642 | for (int i = 0; i < n; i++) { |
---|
| 643 | double value = element[i]; |
---|
| 644 | sum += value * solution[column[i]]; |
---|
| 645 | } |
---|
| 646 | if (sum > thisCut->ub() + primalTolerance) { |
---|
| 647 | sum = sum - thisCut->ub(); |
---|
| 648 | } else if (sum < thisCut->lb() - primalTolerance) { |
---|
| 649 | sum = thisCut->lb() - sum; |
---|
| 650 | } else { |
---|
| 651 | sum = 0.0; |
---|
| 652 | } |
---|
| 653 | if (sum) { |
---|
| 654 | // add to candidates and take out here |
---|
| 655 | cs.insert(*thisCut); |
---|
| 656 | savedCuts_.eraseRowCut(k); |
---|
| 657 | } |
---|
| 658 | } |
---|
| 659 | } |
---|
| 660 | if (!atSolution()) { |
---|
| 661 | int numberRowCutsAfter = cs.sizeRowCuts() ; |
---|
| 662 | int k ; |
---|
| 663 | int nEls = 0; |
---|
| 664 | int nCuts = numberRowCutsAfter - numberRowCutsBefore; |
---|
| 665 | // Remove NULL cuts! |
---|
| 666 | int nNull = 0; |
---|
| 667 | const double * solution = solver->getColSolution(); |
---|
| 668 | bool feasible = true; |
---|
| 669 | double primalTolerance = 1.0e-7; |
---|
| 670 | int shortCut = (depth) ? -1 : generator_->maximumLengthOfCutInTree(); |
---|
| 671 | for (k = numberRowCutsAfter - 1; k >= numberRowCutsBefore; k--) { |
---|
| 672 | const OsiRowCut * thisCut = cs.rowCutPtr(k) ; |
---|
| 673 | double sum = 0.0; |
---|
| 674 | if (thisCut->lb() <= thisCut->ub()) { |
---|
| 675 | int n = thisCut->row().getNumElements(); |
---|
| 676 | if (n <= shortCut) |
---|
| 677 | numberShortCutsAtRoot_++; |
---|
| 678 | const int * column = thisCut->row().getIndices(); |
---|
| 679 | const double * element = thisCut->row().getElements(); |
---|
| 680 | if (n <= 0) { |
---|
| 681 | // infeasible cut - give up |
---|
| 682 | feasible = false; |
---|
| 683 | break; |
---|
| 684 | } |
---|
| 685 | nEls += n; |
---|
| 686 | for (int i = 0; i < n; i++) { |
---|
| 687 | double value = element[i]; |
---|
| 688 | sum += value * solution[column[i]]; |
---|
| 689 | } |
---|
| 690 | if (sum > thisCut->ub() + primalTolerance) { |
---|
| 691 | sum = sum - thisCut->ub(); |
---|
| 692 | } else if (sum < thisCut->lb() - primalTolerance) { |
---|
| 693 | sum = thisCut->lb() - sum; |
---|
| 694 | } else { |
---|
| 695 | sum = 0.0; |
---|
| 696 | cs.eraseRowCut(k); |
---|
| 697 | nNull++; |
---|
| 698 | } |
---|
| 699 | } |
---|
| 700 | } |
---|
| 701 | //if (nNull) |
---|
| 702 | //printf("%s has %d cuts and %d elements - %d null!\n",generatorName_, |
---|
| 703 | // nCuts,nEls,nNull); |
---|
| 704 | numberRowCutsAfter = cs.sizeRowCuts() ; |
---|
| 705 | nCuts = numberRowCutsAfter - numberRowCutsBefore; |
---|
| 706 | nEls = 0; |
---|
| 707 | for (k = numberRowCutsBefore; k < numberRowCutsAfter; k++) { |
---|
| 708 | const OsiRowCut * thisCut = cs.rowCutPtr(k) ; |
---|
| 709 | int n = thisCut->row().getNumElements(); |
---|
| 710 | nEls += n; |
---|
| 711 | } |
---|
| 712 | //printf("%s has %d cuts and %d elements\n",generatorName_, |
---|
| 713 | // nCuts,nEls); |
---|
| 714 | int nElsNow = solver->getMatrixByCol()->getNumElements(); |
---|
| 715 | int numberColumns = solver->getNumCols(); |
---|
| 716 | int numberRows = solver->getNumRows(); |
---|
| 717 | //double averagePerRow = static_cast<double>(nElsNow)/ |
---|
| 718 | //static_cast<double>(numberRows); |
---|
| 719 | int nAdd; |
---|
| 720 | int nAdd2; |
---|
| 721 | int nReasonable; |
---|
| 722 | if (!model_->parentModel() && depth < 2) { |
---|
| 723 | if (inaccuracy_ < 3) { |
---|
| 724 | nAdd = 10000; |
---|
| 725 | if (pass > 0 && numberColumns > -500) |
---|
| 726 | nAdd = CoinMin(nAdd, nElsNow + 2 * numberRows); |
---|
| 727 | } else { |
---|
| 728 | nAdd = 10000; |
---|
| 729 | if (pass > 0) |
---|
| 730 | nAdd = CoinMin(nAdd, nElsNow + 2 * numberRows); |
---|
| 731 | } |
---|
| 732 | nAdd2 = 5 * numberColumns; |
---|
| 733 | nReasonable = CoinMax(nAdd2, nElsNow / 8 + nAdd); |
---|
| 734 | if (!depth && !pass) { |
---|
| 735 | // allow more |
---|
| 736 | nAdd += nElsNow / 2; |
---|
| 737 | nAdd2 += nElsNow / 2; |
---|
| 738 | nReasonable += nElsNow / 2; |
---|
| 739 | } |
---|
| 740 | //if (!depth&&ineffectualCuts()) |
---|
| 741 | //nReasonable *= 2; |
---|
| 742 | } else { |
---|
| 743 | nAdd = 200; |
---|
| 744 | nAdd2 = 2 * numberColumns; |
---|
| 745 | nReasonable = CoinMax(nAdd2, nElsNow / 8 + nAdd); |
---|
| 746 | } |
---|
| 747 | //#define UNS_WEIGHT 0.1 |
---|
[1132] | 748 | #ifdef UNS_WEIGHT |
---|
[1286] | 749 | const double * colLower = solver->getColLower(); |
---|
| 750 | const double * colUpper = solver->getColUpper(); |
---|
[1132] | 751 | #endif |
---|
[1286] | 752 | if (/*nEls>CoinMax(nAdd2,nElsNow/8+nAdd)*/nCuts && feasible) { |
---|
| 753 | //printf("need to remove cuts\n"); |
---|
| 754 | // just add most effective |
---|
[1393] | 755 | #ifndef JJF_ONE |
---|
[1286] | 756 | int nDelete = nEls - nReasonable; |
---|
| 757 | |
---|
| 758 | nElsNow = nEls; |
---|
| 759 | double * sort = new double [nCuts]; |
---|
| 760 | int * which = new int [nCuts]; |
---|
| 761 | // For parallel cuts |
---|
| 762 | double * element2 = new double [numberColumns]; |
---|
| 763 | //#define USE_OBJECTIVE 2 |
---|
[1271] | 764 | #ifdef USE_OBJECTIVE |
---|
[1286] | 765 | const double *objective = solver->getObjCoefficients() ; |
---|
[1271] | 766 | #if USE_OBJECTIVE>1 |
---|
[1286] | 767 | double objNorm = 0.0; |
---|
| 768 | for (int i = 0; i < numberColumns; i++) |
---|
| 769 | objNorm += objective[i] * objective[i]; |
---|
| 770 | if (objNorm) |
---|
| 771 | objNorm = 1.0 / sqrt(objNorm); |
---|
| 772 | else |
---|
| 773 | objNorm = 1.0; |
---|
| 774 | objNorm *= 0.01; // downgrade |
---|
[1271] | 775 | #endif |
---|
| 776 | #endif |
---|
[1286] | 777 | CoinZeroN(element2, numberColumns); |
---|
| 778 | for (k = numberRowCutsBefore; k < numberRowCutsAfter; k++) { |
---|
| 779 | const OsiRowCut * thisCut = cs.rowCutPtr(k) ; |
---|
| 780 | double sum = 0.0; |
---|
| 781 | if (thisCut->lb() <= thisCut->ub()) { |
---|
| 782 | int n = thisCut->row().getNumElements(); |
---|
| 783 | const int * column = thisCut->row().getIndices(); |
---|
| 784 | const double * element = thisCut->row().getElements(); |
---|
| 785 | assert (n); |
---|
[1132] | 786 | #ifdef UNS_WEIGHT |
---|
[1286] | 787 | double normU = 0.0; |
---|
| 788 | double norm = 1.0e-3; |
---|
| 789 | int nU = 0; |
---|
| 790 | for (int i = 0; i < n; i++) { |
---|
| 791 | double value = element[i]; |
---|
| 792 | int iColumn = column[i]; |
---|
| 793 | double solValue = solution[iColumn]; |
---|
| 794 | sum += value * solValue; |
---|
| 795 | value *= value; |
---|
| 796 | norm += value; |
---|
| 797 | if (solValue > colLower[iColumn] + 1.0e-6 && |
---|
| 798 | solValue < colUpper[iColumn] - 1.0e-6) { |
---|
| 799 | normU += value; |
---|
| 800 | nU++; |
---|
| 801 | } |
---|
| 802 | } |
---|
[1393] | 803 | #ifdef JJF_ZERO |
---|
[1286] | 804 | int nS = n - nU; |
---|
| 805 | if (numberColumns > 20000) { |
---|
| 806 | if (nS > 50) { |
---|
| 807 | double ratio = 50.0 / nS; |
---|
| 808 | normU /= ratio; |
---|
| 809 | } |
---|
| 810 | } |
---|
[1132] | 811 | #endif |
---|
[1286] | 812 | norm += UNS_WEIGHT * (normU - norm); |
---|
[1132] | 813 | #else |
---|
[1286] | 814 | double norm = 1.0e-3; |
---|
[1271] | 815 | #ifdef USE_OBJECTIVE |
---|
[1286] | 816 | double obj = 0.0; |
---|
[1271] | 817 | #endif |
---|
[1286] | 818 | for (int i = 0; i < n; i++) { |
---|
| 819 | int iColumn = column[i]; |
---|
| 820 | double value = element[i]; |
---|
| 821 | sum += value * solution[iColumn]; |
---|
| 822 | norm += value * value; |
---|
[1271] | 823 | #ifdef USE_OBJECTIVE |
---|
[1286] | 824 | obj += value * objective[iColumn]; |
---|
[1271] | 825 | #endif |
---|
[1286] | 826 | } |
---|
[1132] | 827 | #endif |
---|
[1286] | 828 | if (sum > thisCut->ub()) { |
---|
| 829 | sum = sum - thisCut->ub(); |
---|
| 830 | } else if (sum < thisCut->lb()) { |
---|
| 831 | sum = thisCut->lb() - sum; |
---|
| 832 | } else { |
---|
| 833 | sum = 0.0; |
---|
| 834 | } |
---|
[1271] | 835 | #ifdef USE_OBJECTIVE |
---|
[1286] | 836 | if (sum) { |
---|
[1271] | 837 | #if USE_OBJECTIVE==1 |
---|
[1286] | 838 | obj = CoinMax(1.0e-6, fabs(obj)); |
---|
| 839 | norm = sqrt(obj * norm); |
---|
| 840 | //sum += fabs(obj)*invObjNorm; |
---|
| 841 | //printf("sum %g norm %g normobj %g invNorm %g mod %g\n", |
---|
| 842 | // sum,norm,obj,invObjNorm,obj*invObjNorm); |
---|
| 843 | // normalize |
---|
| 844 | sum /= sqrt(norm); |
---|
[1271] | 845 | #else |
---|
[1286] | 846 | // normalize |
---|
| 847 | norm = 1.0 / sqrt(norm); |
---|
| 848 | sum = (sum + objNorm * obj) * norm; |
---|
[1271] | 849 | #endif |
---|
[1286] | 850 | } |
---|
[1271] | 851 | #else |
---|
[1286] | 852 | // normalize |
---|
| 853 | sum /= sqrt(norm); |
---|
[1271] | 854 | #endif |
---|
[1286] | 855 | //sum /= pow(norm,0.3); |
---|
| 856 | // adjust for length |
---|
| 857 | //sum /= pow(reinterpret_cast<double>(n),0.2); |
---|
| 858 | //sum /= sqrt((double) n); |
---|
| 859 | // randomize |
---|
| 860 | //double randomNumber = |
---|
| 861 | //model_->randomNumberGenerator()->randomDouble(); |
---|
| 862 | //sum *= (0.5+randomNumber); |
---|
| 863 | } else { |
---|
| 864 | // keep |
---|
| 865 | sum = COIN_DBL_MAX; |
---|
| 866 | } |
---|
| 867 | sort[k-numberRowCutsBefore] = sum; |
---|
| 868 | which[k-numberRowCutsBefore] = k; |
---|
| 869 | } |
---|
| 870 | CoinSort_2(sort, sort + nCuts, which); |
---|
| 871 | // Now see which ones are too similar |
---|
| 872 | int nParallel = 0; |
---|
| 873 | double testValue = (depth > 1) ? 0.99 : 0.999999; |
---|
| 874 | for (k = 0; k < nCuts; k++) { |
---|
| 875 | int j = which[k]; |
---|
| 876 | const OsiRowCut * thisCut = cs.rowCutPtr(j) ; |
---|
| 877 | if (thisCut->lb() > thisCut->ub()) |
---|
| 878 | break; // cut is infeasible |
---|
| 879 | int n = thisCut->row().getNumElements(); |
---|
| 880 | const int * column = thisCut->row().getIndices(); |
---|
| 881 | const double * element = thisCut->row().getElements(); |
---|
| 882 | assert (n); |
---|
| 883 | double norm = 0.0; |
---|
| 884 | double lb = thisCut->lb(); |
---|
| 885 | double ub = thisCut->ub(); |
---|
| 886 | for (int i = 0; i < n; i++) { |
---|
| 887 | double value = element[i]; |
---|
| 888 | element2[column[i]] = value; |
---|
| 889 | norm += value * value; |
---|
| 890 | } |
---|
| 891 | int kkk = CoinMin(nCuts, k + 5); |
---|
| 892 | for (int kk = k + 1; kk < kkk; kk++) { |
---|
| 893 | int jj = which[kk]; |
---|
| 894 | const OsiRowCut * thisCut2 = cs.rowCutPtr(jj) ; |
---|
| 895 | if (thisCut2->lb() > thisCut2->ub()) |
---|
| 896 | break; // cut is infeasible |
---|
| 897 | int nB = thisCut2->row().getNumElements(); |
---|
| 898 | const int * columnB = thisCut2->row().getIndices(); |
---|
| 899 | const double * elementB = thisCut2->row().getElements(); |
---|
| 900 | assert (nB); |
---|
| 901 | double normB = 0.0; |
---|
| 902 | double product = 0.0; |
---|
| 903 | for (int i = 0; i < nB; i++) { |
---|
| 904 | double value = elementB[i]; |
---|
| 905 | normB += value * value; |
---|
| 906 | product += value * element2[columnB[i]]; |
---|
| 907 | } |
---|
| 908 | if (product > 0.0 && product*product > testValue*norm*normB) { |
---|
| 909 | bool parallel = true; |
---|
| 910 | double lbB = thisCut2->lb(); |
---|
| 911 | double ubB = thisCut2->ub(); |
---|
| 912 | if ((lb < -1.0e20 && lbB > -1.0e20) || |
---|
| 913 | (lbB < -1.0e20 && lb > -1.0e20)) |
---|
| 914 | parallel = false; |
---|
| 915 | double tolerance; |
---|
| 916 | tolerance = CoinMax(fabs(lb), fabs(lbB)) + 1.0e-6; |
---|
| 917 | if (fabs(lb - lbB) > tolerance) |
---|
| 918 | parallel = false; |
---|
| 919 | if ((ub > 1.0e20 && ubB < 1.0e20) || |
---|
| 920 | (ubB > 1.0e20 && ub < 1.0e20)) |
---|
| 921 | parallel = false; |
---|
| 922 | tolerance = CoinMax(fabs(ub), fabs(ubB)) + 1.0e-6; |
---|
| 923 | if (fabs(ub - ubB) > tolerance) |
---|
| 924 | parallel = false; |
---|
| 925 | if (parallel) { |
---|
| 926 | nParallel++; |
---|
| 927 | sort[k] = 0.0; |
---|
| 928 | break; |
---|
| 929 | } |
---|
| 930 | } |
---|
| 931 | } |
---|
| 932 | for (int i = 0; i < n; i++) { |
---|
| 933 | element2[column[i]] = 0.0; |
---|
| 934 | } |
---|
| 935 | } |
---|
| 936 | delete [] element2; |
---|
| 937 | CoinSort_2(sort, sort + nCuts, which); |
---|
| 938 | k = 0; |
---|
| 939 | while (nDelete > 0 || !sort[k]) { |
---|
| 940 | int iCut = which[k]; |
---|
| 941 | const OsiRowCut * thisCut = cs.rowCutPtr(iCut) ; |
---|
| 942 | int n = thisCut->row().getNumElements(); |
---|
| 943 | // may be best, just to save if short |
---|
| 944 | if (false && n && sort[k]) { |
---|
| 945 | // add to saved cuts |
---|
| 946 | savedCuts_.insert(*thisCut); |
---|
| 947 | } |
---|
| 948 | nDelete -= n; |
---|
| 949 | k++; |
---|
| 950 | if (k >= nCuts) |
---|
| 951 | break; |
---|
| 952 | } |
---|
| 953 | std::sort(which, which + k); |
---|
| 954 | k--; |
---|
| 955 | for (; k >= 0; k--) { |
---|
| 956 | cs.eraseRowCut(which[k]); |
---|
| 957 | } |
---|
| 958 | delete [] sort; |
---|
| 959 | delete [] which; |
---|
| 960 | numberRowCutsAfter = cs.sizeRowCuts() ; |
---|
[1271] | 961 | #else |
---|
[1286] | 962 | double * norm = new double [nCuts]; |
---|
| 963 | int * which = new int [2*nCuts]; |
---|
| 964 | double * score = new double [nCuts]; |
---|
| 965 | double * ortho = new double [nCuts]; |
---|
| 966 | int nIn = 0; |
---|
| 967 | int nOut = nCuts; |
---|
| 968 | // For parallel cuts |
---|
| 969 | double * element2 = new double [numberColumns]; |
---|
| 970 | const double *objective = solver->getObjCoefficients() ; |
---|
| 971 | double objNorm = 0.0; |
---|
| 972 | for (int i = 0; i < numberColumns; i++) |
---|
| 973 | objNorm += objective[i] * objective[i]; |
---|
| 974 | if (objNorm) |
---|
| 975 | objNorm = 1.0 / sqrt(objNorm); |
---|
| 976 | else |
---|
| 977 | objNorm = 1.0; |
---|
| 978 | objNorm *= 0.1; // weight of 0.1 |
---|
| 979 | CoinZeroN(element2, numberColumns); |
---|
| 980 | int numberRowCuts = numberRowCutsAfter - numberRowCutsBefore; |
---|
| 981 | int iBest = -1; |
---|
| 982 | double best = 0.0; |
---|
| 983 | int nPossible = 0; |
---|
| 984 | double testValue = (depth > 1) ? 0.7 : 0.5; |
---|
| 985 | for (k = 0; k < numberRowCuts; k++) { |
---|
| 986 | const OsiRowCut * thisCut = cs.rowCutPtr(k + numberRowCutsBefore) ; |
---|
| 987 | double sum = 0.0; |
---|
| 988 | if (thisCut->lb() <= thisCut->ub()) { |
---|
| 989 | int n = thisCut->row().getNumElements(); |
---|
| 990 | const int * column = thisCut->row().getIndices(); |
---|
| 991 | const double * element = thisCut->row().getElements(); |
---|
| 992 | assert (n); |
---|
| 993 | double normThis = 1.0e-6; |
---|
| 994 | double obj = 0.0; |
---|
| 995 | for (int i = 0; i < n; i++) { |
---|
| 996 | int iColumn = column[i]; |
---|
| 997 | double value = element[i]; |
---|
| 998 | sum += value * solution[iColumn]; |
---|
| 999 | normThis += value * value; |
---|
| 1000 | obj += value * objective[iColumn]; |
---|
| 1001 | } |
---|
| 1002 | if (sum > thisCut->ub()) { |
---|
| 1003 | sum = sum - thisCut->ub(); |
---|
| 1004 | } else if (sum < thisCut->lb()) { |
---|
| 1005 | sum = thisCut->lb() - sum; |
---|
| 1006 | } else { |
---|
| 1007 | sum = 0.0; |
---|
| 1008 | } |
---|
| 1009 | if (sum) { |
---|
| 1010 | normThis = 1.0 / sqrt(normThis); |
---|
| 1011 | norm[k] = normThis; |
---|
| 1012 | sum *= normThis; |
---|
| 1013 | obj *= normThis; |
---|
| 1014 | score[k] = sum + obj * objNorm; |
---|
| 1015 | ortho[k] = 1.0; |
---|
| 1016 | } |
---|
| 1017 | } else { |
---|
| 1018 | // keep and discard others |
---|
| 1019 | nIn = 1; |
---|
| 1020 | which[0] = k; |
---|
| 1021 | for (int j = 0; j < numberRowCuts; j++) { |
---|
| 1022 | if (j != k) |
---|
| 1023 | which[nOut++] = j; |
---|
| 1024 | } |
---|
| 1025 | iBest = -1; |
---|
| 1026 | break; |
---|
| 1027 | } |
---|
| 1028 | if (sum) { |
---|
| 1029 | if (score[k] > best) { |
---|
| 1030 | best = score[k]; |
---|
| 1031 | iBest = nPossible; |
---|
| 1032 | } |
---|
| 1033 | which[nPossible++] = k; |
---|
| 1034 | } else { |
---|
| 1035 | which[nOut++] = k; |
---|
| 1036 | } |
---|
| 1037 | } |
---|
| 1038 | while (iBest >= 0) { |
---|
| 1039 | int kBest = which[iBest]; |
---|
| 1040 | int j = which[nIn]; |
---|
| 1041 | which[iBest] = j; |
---|
| 1042 | which[nIn++] = kBest; |
---|
| 1043 | const OsiRowCut * thisCut = cs.rowCutPtr(kBest + numberRowCutsBefore) ; |
---|
| 1044 | int n = thisCut->row().getNumElements(); |
---|
| 1045 | nReasonable -= n; |
---|
| 1046 | if (nReasonable <= 0) { |
---|
| 1047 | for (k = nIn; k < nPossible; k++) |
---|
| 1048 | which[nOut++] = which[k]; |
---|
| 1049 | break; |
---|
| 1050 | } |
---|
| 1051 | // Now see which ones are too similar and choose next |
---|
| 1052 | iBest = -1; |
---|
| 1053 | best = 0.0; |
---|
| 1054 | int nOld = nPossible; |
---|
| 1055 | nPossible = nIn; |
---|
| 1056 | const int * column = thisCut->row().getIndices(); |
---|
| 1057 | const double * element = thisCut->row().getElements(); |
---|
| 1058 | assert (n); |
---|
| 1059 | double normNew = norm[kBest]; |
---|
| 1060 | for (int i = 0; i < n; i++) { |
---|
| 1061 | double value = element[i]; |
---|
| 1062 | element2[column[i]] = value; |
---|
| 1063 | } |
---|
| 1064 | for (int j = nIn; j < nOld; j++) { |
---|
| 1065 | k = which[j]; |
---|
| 1066 | const OsiRowCut * thisCut2 = cs.rowCutPtr(k + numberRowCutsBefore) ; |
---|
| 1067 | int nB = thisCut2->row().getNumElements(); |
---|
| 1068 | const int * columnB = thisCut2->row().getIndices(); |
---|
| 1069 | const double * elementB = thisCut2->row().getElements(); |
---|
| 1070 | assert (nB); |
---|
| 1071 | double normB = norm[k]; |
---|
| 1072 | double product = 0.0; |
---|
| 1073 | for (int i = 0; i < nB; i++) { |
---|
| 1074 | double value = elementB[i]; |
---|
| 1075 | product += value * element2[columnB[i]]; |
---|
| 1076 | } |
---|
| 1077 | double orthoScore = 1.0 - product * normNew * normB; |
---|
| 1078 | if (orthoScore >= testValue) { |
---|
| 1079 | ortho[k] = CoinMin(orthoScore, ortho[k]); |
---|
| 1080 | double test = score[k] + ortho[k]; |
---|
| 1081 | if (test > best) { |
---|
| 1082 | best = score[k]; |
---|
| 1083 | iBest = nPossible; |
---|
| 1084 | } |
---|
| 1085 | which[nPossible++] = k; |
---|
| 1086 | } else { |
---|
| 1087 | which[nOut++] = k; |
---|
| 1088 | } |
---|
| 1089 | } |
---|
| 1090 | for (int i = 0; i < n; i++) { |
---|
| 1091 | element2[column[i]] = 0.0; |
---|
| 1092 | } |
---|
| 1093 | } |
---|
| 1094 | delete [] score; |
---|
| 1095 | delete [] ortho; |
---|
| 1096 | std::sort(which + nCuts, which + nOut); |
---|
| 1097 | k = nOut - 1; |
---|
| 1098 | for (; k >= nCuts; k--) { |
---|
| 1099 | cs.eraseRowCut(which[k] + numberRowCutsBefore); |
---|
| 1100 | } |
---|
| 1101 | delete [] norm; |
---|
| 1102 | delete [] which; |
---|
| 1103 | numberRowCutsAfter = cs.sizeRowCuts() ; |
---|
[1006] | 1104 | #endif |
---|
[1286] | 1105 | } |
---|
| 1106 | } |
---|
[640] | 1107 | #ifdef CBC_DEBUG |
---|
[1286] | 1108 | { |
---|
| 1109 | int numberRowCutsAfter = cs.sizeRowCuts() ; |
---|
| 1110 | int k ; |
---|
| 1111 | int nBad = 0; |
---|
| 1112 | for (k = numberRowCutsBefore; k < numberRowCutsAfter; k++) { |
---|
| 1113 | OsiRowCut thisCut = cs.rowCut(k) ; |
---|
| 1114 | if (thisCut.lb() > thisCut.ub() || |
---|
| 1115 | thisCut.lb() > 1.0e8 || |
---|
| 1116 | thisCut.ub() < -1.0e8) |
---|
| 1117 | printf("cut from %s has bounds %g and %g!\n", |
---|
| 1118 | generatorName_, thisCut.lb(), thisCut.ub()); |
---|
| 1119 | if (thisCut.lb() <= thisCut.ub()) { |
---|
| 1120 | /* check size of elements. |
---|
| 1121 | We can allow smaller but this helps debug generators as it |
---|
| 1122 | is unsafe to have small elements */ |
---|
| 1123 | int n = thisCut.row().getNumElements(); |
---|
| 1124 | const int * column = thisCut.row().getIndices(); |
---|
| 1125 | const double * element = thisCut.row().getElements(); |
---|
| 1126 | assert (n); |
---|
| 1127 | for (int i = 0; i < n; i++) { |
---|
| 1128 | double value = element[i]; |
---|
| 1129 | if (fabs(value) <= 1.0e-12 || fabs(value) >= 1.0e20) |
---|
| 1130 | nBad++; |
---|
| 1131 | } |
---|
| 1132 | } |
---|
| 1133 | if (nBad) |
---|
| 1134 | printf("Cut generator %s produced %d cuts of which %d had tiny or large elements\n", |
---|
| 1135 | generatorName_, numberRowCutsAfter - numberRowCutsBefore, nBad); |
---|
| 1136 | } |
---|
| 1137 | } |
---|
[640] | 1138 | #endif |
---|
[1880] | 1139 | int numberRowCutsAfter = cs.sizeRowCuts() ; |
---|
| 1140 | int numberColumnCutsAfter = cs.sizeColCuts() ; |
---|
| 1141 | if (numberRowCutsBefore < numberRowCutsAfter) { |
---|
| 1142 | for (int k = numberRowCutsBefore; k < numberRowCutsAfter; k++) { |
---|
| 1143 | OsiRowCut thisCut = cs.rowCut(k) ; |
---|
| 1144 | int n = thisCut.row().getNumElements(); |
---|
| 1145 | numberElements_ += n; |
---|
| 1146 | } |
---|
[1393] | 1147 | #ifdef JJF_ZERO |
---|
[1880] | 1148 | printf("generator %s generated %d row cuts\n", |
---|
| 1149 | generatorName_, numberRowCutsAfter - numberRowCutsBefore); |
---|
[1271] | 1150 | #endif |
---|
[1880] | 1151 | numberCuts_ += numberRowCutsAfter - numberRowCutsBefore; |
---|
| 1152 | } |
---|
| 1153 | if (numberColumnCutsBefore < numberColumnCutsAfter) { |
---|
[1393] | 1154 | #ifdef JJF_ZERO |
---|
[1880] | 1155 | printf("generator %s generated %d column cuts\n", |
---|
| 1156 | generatorName_, numberColumnCutsAfter - numberColumnCutsBefore); |
---|
[1271] | 1157 | #endif |
---|
[1880] | 1158 | numberColumnCuts_ += numberColumnCutsAfter - numberColumnCutsBefore; |
---|
[1286] | 1159 | } |
---|
| 1160 | if (timing()) |
---|
| 1161 | timeInCutGenerator_ += CoinCpuTime() - time1; |
---|
| 1162 | // switch off if first time and no good |
---|
[1880] | 1163 | if (node == NULL && !pass ) { |
---|
| 1164 | if (numberRowCutsAfter - numberRowCutsBefore |
---|
| 1165 | < switchOffIfLessThan_ /*&& numberCuts_ < switchOffIfLessThan_*/) { |
---|
| 1166 | // switch off |
---|
| 1167 | maximumTries_ = 0; |
---|
| 1168 | whenCutGenerator_=-100; |
---|
| 1169 | //whenCutGenerator_ = -100; |
---|
| 1170 | //whenCutGeneratorInSub_ = -200; |
---|
[1286] | 1171 | } |
---|
| 1172 | } |
---|
[1880] | 1173 | if (maximumTries_>0) { |
---|
| 1174 | maximumTries_--; |
---|
| 1175 | if (!maximumTries_) |
---|
| 1176 | whenCutGenerator_=-100; |
---|
| 1177 | } |
---|
[202] | 1178 | } |
---|
[1286] | 1179 | return returnCode; |
---|
[2] | 1180 | } |
---|
[1286] | 1181 | void |
---|
| 1182 | CbcCutGenerator::setHowOften(int howOften) |
---|
[2] | 1183 | { |
---|
[1286] | 1184 | |
---|
| 1185 | if (howOften >= 1000000) { |
---|
| 1186 | // leave Probing every SCANCUTS_PROBING |
---|
| 1187 | howOften = howOften % 1000000; |
---|
| 1188 | CglProbing* generator = |
---|
| 1189 | dynamic_cast<CglProbing*>(generator_); |
---|
| 1190 | |
---|
| 1191 | if (generator && howOften > SCANCUTS_PROBING) |
---|
| 1192 | howOften = SCANCUTS_PROBING + 1000000; |
---|
| 1193 | else |
---|
| 1194 | howOften += 1000000; |
---|
| 1195 | } |
---|
| 1196 | whenCutGenerator_ = howOften; |
---|
[2] | 1197 | } |
---|
[1286] | 1198 | void |
---|
| 1199 | CbcCutGenerator::setWhatDepth(int value) |
---|
[13] | 1200 | { |
---|
[1286] | 1201 | depthCutGenerator_ = value; |
---|
[13] | 1202 | } |
---|
[1286] | 1203 | void |
---|
| 1204 | CbcCutGenerator::setWhatDepthInSub(int value) |
---|
[13] | 1205 | { |
---|
[1286] | 1206 | depthCutGeneratorInSub_ = value; |
---|
[13] | 1207 | } |
---|
[1839] | 1208 | // Add in statistics from other |
---|
| 1209 | void |
---|
| 1210 | CbcCutGenerator::addStatistics(const CbcCutGenerator * other) |
---|
| 1211 | { |
---|
| 1212 | // Time in cut generator |
---|
| 1213 | timeInCutGenerator_ += other->timeInCutGenerator_; |
---|
| 1214 | // Number times cut generator entered |
---|
| 1215 | numberTimes_ += other->numberTimes_; |
---|
| 1216 | // Total number of cuts added |
---|
| 1217 | numberCuts_ += other->numberCuts_; |
---|
| 1218 | // Total number of elements added |
---|
| 1219 | numberElements_ += other->numberElements_; |
---|
| 1220 | // Total number of column cuts added |
---|
| 1221 | numberColumnCuts_ += other->numberColumnCuts_; |
---|
| 1222 | // Total number of cuts active after (at end of n cut passes at each node) |
---|
| 1223 | numberCutsActive_ += other->numberCutsActive_; |
---|
| 1224 | // Number of cuts generated at root |
---|
| 1225 | numberCutsAtRoot_ += other->numberCutsAtRoot_; |
---|
| 1226 | // Number of cuts active at root |
---|
| 1227 | numberActiveCutsAtRoot_ += other->numberActiveCutsAtRoot_; |
---|
| 1228 | // Number of short cuts at root |
---|
| 1229 | numberShortCutsAtRoot_ += other->numberShortCutsAtRoot_; |
---|
| 1230 | } |
---|
| 1231 | // Scale back statistics by factor |
---|
| 1232 | void |
---|
| 1233 | CbcCutGenerator::scaleBackStatistics(int factor) |
---|
| 1234 | { |
---|
| 1235 | // leave time |
---|
| 1236 | // Number times cut generator entered |
---|
| 1237 | numberTimes_ = (numberTimes_+factor-1)/factor; |
---|
| 1238 | // Total number of cuts added |
---|
| 1239 | numberCuts_ = (numberCuts_+factor-1)/factor; |
---|
| 1240 | // Total number of elements added |
---|
| 1241 | numberElements_ = (numberElements_+factor-1)/factor; |
---|
| 1242 | // Total number of column cuts added |
---|
| 1243 | numberColumnCuts_ = (numberColumnCuts_+factor-1)/factor; |
---|
| 1244 | // Total number of cuts active after (at end of n cut passes at each node) |
---|
| 1245 | numberCutsActive_ = (numberCutsActive_+factor-1)/factor; |
---|
| 1246 | // Number of cuts generated at root |
---|
| 1247 | numberCutsAtRoot_ = (numberCutsAtRoot_+factor-1)/factor; |
---|
| 1248 | // Number of cuts active at root |
---|
| 1249 | numberActiveCutsAtRoot_ = (numberActiveCutsAtRoot_+factor-1)/factor; |
---|
| 1250 | // Number of short cuts at root |
---|
| 1251 | numberShortCutsAtRoot_ = (numberShortCutsAtRoot_+factor-1)/factor; |
---|
| 1252 | } |
---|
[1271] | 1253 | // Create C++ lines to get to current state |
---|
[1286] | 1254 | void |
---|
| 1255 | CbcCutGenerator::generateTuning( FILE * fp) |
---|
[1271] | 1256 | { |
---|
[1286] | 1257 | fprintf(fp, "// Cbc tuning for generator %s\n", generatorName_); |
---|
| 1258 | fprintf(fp, " generator->setHowOften(%d);\n", whenCutGenerator_); |
---|
| 1259 | fprintf(fp, " generator->setSwitchOffIfLessThan(%d);\n", switchOffIfLessThan_); |
---|
| 1260 | fprintf(fp, " generator->setWhatDepth(%d);\n", depthCutGenerator_); |
---|
| 1261 | fprintf(fp, " generator->setInaccuracy(%d);\n", inaccuracy_); |
---|
| 1262 | if (timing()) |
---|
| 1263 | fprintf(fp, " generator->setTiming(true);\n"); |
---|
| 1264 | if (normal()) |
---|
| 1265 | fprintf(fp, " generator->setNormal(true);\n"); |
---|
| 1266 | if (atSolution()) |
---|
| 1267 | fprintf(fp, " generator->setAtSolution(true);\n"); |
---|
| 1268 | if (whenInfeasible()) |
---|
| 1269 | fprintf(fp, " generator->setWhenInfeasible(true);\n"); |
---|
| 1270 | if (needsOptimalBasis()) |
---|
| 1271 | fprintf(fp, " generator->setNeedsOptimalBasis(true);\n"); |
---|
| 1272 | if (mustCallAgain()) |
---|
| 1273 | fprintf(fp, " generator->setMustCallAgain(true);\n"); |
---|
| 1274 | if (whetherToUse()) |
---|
| 1275 | fprintf(fp, " generator->setWhetherToUse(true);\n"); |
---|
[1271] | 1276 | } |
---|
[640] | 1277 | |
---|
| 1278 | |
---|
| 1279 | |
---|