[394] | 1 | // Copyright (C) 2006, International Business Machines |
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| 2 | // Corporation and others. All Rights Reserved. |
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| 3 | #if defined(_MSC_VER) |
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| 4 | // Turn off compiler warning about long names |
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| 5 | # pragma warning(disable:4786) |
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| 6 | #endif |
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| 7 | |
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| 8 | #include <cassert> |
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| 9 | |
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| 10 | // For Branch and bound |
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| 11 | #include "OsiClpSolverInterface.hpp" |
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| 12 | #include "CbcModel.hpp" |
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| 13 | #include "CbcCutGenerator.hpp" |
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| 14 | #include "CoinHelperFunctions.hpp" |
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| 15 | #include "CbcStrategy.hpp" |
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| 16 | |
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| 17 | // Need stored cuts |
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| 18 | |
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| 19 | #include "CglStored.hpp" |
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| 20 | |
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| 21 | // For saying about solution validity |
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| 22 | #include "OsiAuxInfo.hpp" |
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| 23 | |
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| 24 | |
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| 25 | // Time |
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| 26 | #include "CoinTime.hpp" |
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| 27 | // Class to disallow strong branching solutions |
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| 28 | #include "CbcFeasibilityBase.hpp" |
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| 29 | class CbcFeasibilityNoStrong : public CbcFeasibilityBase{ |
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| 30 | public: |
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| 31 | // Default Constructor |
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[706] | 32 | CbcFeasibilityNoStrong () {} |
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[394] | 33 | |
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[706] | 34 | virtual ~CbcFeasibilityNoStrong() {} |
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[394] | 35 | // Copy constructor |
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[706] | 36 | CbcFeasibilityNoStrong ( const CbcFeasibilityNoStrong &rhs) {} |
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[394] | 37 | |
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| 38 | // Assignment operator |
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| 39 | CbcFeasibilityNoStrong & operator=( const CbcFeasibilityNoStrong& rhs) |
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[706] | 40 | { return * this;} |
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[394] | 41 | |
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| 42 | /// Clone |
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| 43 | virtual CbcFeasibilityBase * clone() const |
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[706] | 44 | { return new CbcFeasibilityNoStrong();} |
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[394] | 45 | |
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| 46 | /** |
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| 47 | On input mode: |
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| 48 | 0 - called after a solve but before any cuts |
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| 49 | -1 - called after strong branching |
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| 50 | Returns : |
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| 51 | 0 - no opinion |
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| 52 | -1 pretend infeasible |
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| 53 | 1 pretend integer solution |
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| 54 | */ |
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| 55 | virtual int feasible(CbcModel * model, int mode) |
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[706] | 56 | {return mode;} |
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[394] | 57 | }; |
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| 58 | |
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| 59 | |
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| 60 | /************************************************************************ |
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| 61 | |
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| 62 | This main program solves the following 0-1 problem: |
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| 63 | |
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| 64 | min -x0 - 2x1 - 3x2 - 4x3 |
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| 65 | |
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| 66 | subject to |
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| 67 | |
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| 68 | x0 + x1 + x2 + x3 <= 2 |
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| 69 | |
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| 70 | and quadratic constraints with positive random numbers |
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| 71 | |
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| 72 | It does it creating extra yij variables and constraints xi + xj -1 <= yij |
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| 73 | and putting quadratic elements on y |
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| 74 | |
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| 75 | The extra constraints are treated as stored cuts. |
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| 76 | |
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| 77 | This is to show how to keep branching even if we have a solution |
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| 78 | |
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| 79 | ************************************************************************/ |
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| 80 | |
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| 81 | int main (int argc, const char *argv[]) |
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| 82 | { |
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| 83 | |
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| 84 | // Define a Solver which inherits from OsiClpsolverInterface -> OsiSolverInterface |
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| 85 | |
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| 86 | OsiClpSolverInterface solver1; |
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| 87 | |
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| 88 | int nX=4; |
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| 89 | |
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| 90 | int nY = (nX * (nX-1)/2); |
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| 91 | // All columns |
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| 92 | double * obj = new double [nX+nY]; |
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| 93 | double * clo = new double[nX+nY]; |
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| 94 | double * cup = new double[nX+nY]; |
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| 95 | int i; |
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| 96 | for (i=0;i<nX;i++) { |
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| 97 | obj[i] = -(i+1); |
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| 98 | clo[i]=0.0; |
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| 99 | cup[i]=1.0; |
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| 100 | } |
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| 101 | for (i=nX;i<nX+nY;i++) { |
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| 102 | obj[i] = 0.0; |
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| 103 | clo[i]=0.0; |
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| 104 | cup[i]=1.0; |
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| 105 | } |
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| 106 | // Just ordinary rows |
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| 107 | int nRow = 1+nX; |
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| 108 | double * rlo = new double[nRow]; |
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| 109 | double * rup = new double[nRow]; |
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| 110 | for (i=0;i<nRow;i++) { |
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| 111 | rlo[i]=-COIN_DBL_MAX; |
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| 112 | rup[i]=1.0; |
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| 113 | } |
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| 114 | // and first row |
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| 115 | rup[0]=nX/2.0; |
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| 116 | // Matrix |
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| 117 | int nEl = nX+nX*nX; |
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| 118 | int * row = new int[nEl]; |
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| 119 | int * col = new int[nEl]; |
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| 120 | double * el = new double[nEl]; |
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| 121 | // X |
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| 122 | nEl=0; |
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| 123 | // May need scale to make plausible |
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| 124 | double scaleFactor = 1.0; |
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| 125 | for (i=0;i<nX;i++) { |
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| 126 | row[nEl]=0; |
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| 127 | col[nEl]=i; |
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| 128 | el[nEl++]=1.0; |
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| 129 | // and diagonal |
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| 130 | row[nEl]=i+1; |
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| 131 | col[nEl]=i; |
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| 132 | double value = CoinDrand48()*scaleFactor; |
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| 133 | // make reasonable (so multiples of 0.000001) |
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| 134 | value *= 1.0e6; |
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| 135 | int iValue = (int) (value+1.0); |
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| 136 | value = iValue; |
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| 137 | value *= 1.0e-6; |
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| 138 | el[nEl++]=value; |
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| 139 | } |
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| 140 | // Y |
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| 141 | nY = nX; |
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| 142 | // And stored cuts |
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| 143 | CglStored stored; |
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| 144 | double cutEls[3]={1.0,1.0,-1.0}; |
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| 145 | int cutIndices[3]; |
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| 146 | for (i=0;i<nX;i++) { |
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| 147 | cutIndices[0]=i; |
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| 148 | for (int j=i+1;j<nX;j++) { |
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| 149 | cutIndices[1]=j; |
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| 150 | cutIndices[2]=nY; |
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| 151 | // add cut |
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| 152 | stored.addCut(-COIN_DBL_MAX,1.0,3,cutIndices,cutEls); |
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| 153 | row[nEl]=i+1; |
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| 154 | col[nEl]=nY; |
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| 155 | double value = CoinDrand48()*scaleFactor; |
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| 156 | // multiply to make ones with most negative objective violated |
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| 157 | // make reasonable (so multiples of 0.000001) |
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| 158 | value *= 1.0e6+1.0e6*j; |
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| 159 | int iValue = (int) (value+1.0); |
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| 160 | value = iValue; |
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| 161 | value *= 1.0e-6; |
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| 162 | el[nEl++]=value; |
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| 163 | // and other |
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| 164 | if (i!=j) { |
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| 165 | row[nEl]=j+1; |
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| 166 | col[nEl]=nY; |
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| 167 | el[nEl++]=value; |
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| 168 | } |
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| 169 | nY++; |
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| 170 | } |
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| 171 | } |
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| 172 | // Create model |
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| 173 | CoinPackedMatrix matrix(true, row, col, el, nEl); |
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| 174 | solver1.loadProblem(matrix, clo, cup, obj, rlo, rup); |
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| 175 | delete [] obj; |
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| 176 | delete [] clo; |
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| 177 | delete [] cup; |
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| 178 | delete [] rlo; |
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| 179 | delete [] rup; |
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| 180 | delete [] row; |
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| 181 | delete [] col; |
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| 182 | delete [] el; |
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| 183 | // Integers |
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| 184 | for (i=0;i<nX;i++) |
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| 185 | solver1.setInteger(i); |
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| 186 | // Reduce printout |
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| 187 | solver1.setHintParam(OsiDoReducePrint,true,OsiHintTry); |
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| 188 | // This clones solver |
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| 189 | CbcModel model(solver1); |
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[640] | 190 | // Add stored cuts (making sure at all depths) |
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| 191 | model.addCutGenerator(&stored,1,"Stored",true,false,false,-100,1,-1); |
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[394] | 192 | /* You need the next few lines - |
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| 193 | a) so that cut generator will always be called again if it generated cuts |
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| 194 | b) it is known that matrix is not enough to define problem so do cuts even |
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| 195 | if it looks integer feasible at continuous optimum. |
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[640] | 196 | c) a solution found by strong branching will be ignored. |
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| 197 | d) don't recompute a solution once found |
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[394] | 198 | */ |
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| 199 | // Make sure cut generator called correctly (a) |
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| 200 | model.cutGenerator(0)->setMustCallAgain(true); |
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| 201 | // Say cuts needed at continuous (b) |
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| 202 | OsiBabSolver oddCuts; |
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| 203 | oddCuts.setSolverType(4); |
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| 204 | model.passInSolverCharacteristics(&oddCuts); |
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| 205 | // Say no to all solutions by strong branching (c) |
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| 206 | CbcFeasibilityNoStrong noStrong; |
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| 207 | model.setProblemFeasibility(noStrong); |
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[640] | 208 | // Say don't recompute solution d) |
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| 209 | model.setSpecialOptions(4); |
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[394] | 210 | |
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| 211 | double time1 = CoinCpuTime(); |
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| 212 | |
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| 213 | // Do complete search |
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| 214 | |
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| 215 | model.branchAndBound(); |
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| 216 | |
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| 217 | std::cout<<argv[1]<<" took "<<CoinCpuTime()-time1<<" seconds, " |
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| 218 | <<model.getNodeCount()<<" nodes with objective " |
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| 219 | <<model.getObjValue() |
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| 220 | <<(!model.status() ? " Finished" : " Not finished") |
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| 221 | <<std::endl; |
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| 222 | |
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| 223 | // Print solution if finished - we can't get names from Osi! |
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| 224 | |
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| 225 | if (!model.status()&&model.getMinimizationObjValue()<1.0e50) { |
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| 226 | int numberColumns = model.solver()->getNumCols(); |
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| 227 | |
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| 228 | //const double * solution = model.bestSolution(); |
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| 229 | const double * solution = model.solver()->getColSolution(); |
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| 230 | |
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| 231 | int iColumn; |
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| 232 | for (iColumn=0;iColumn<numberColumns;iColumn++) { |
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| 233 | double value=solution[iColumn]; |
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| 234 | if (fabs(value)>1.0e-7&&model.solver()->isInteger(iColumn)) |
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| 235 | printf("Column %d has value %g\n",iColumn,value); |
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| 236 | } |
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| 237 | } |
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| 238 | return 0; |
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| 239 | } |
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