1 | /* -*- mode: C++; indent-tabs-mode: nil; -*- |
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2 | * |
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3 | * This file is a part of LEMON, a generic C++ optimization library. |
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4 | * |
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5 | * Copyright (C) 2003-2009 |
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6 | * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport |
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7 | * (Egervary Research Group on Combinatorial Optimization, EGRES). |
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8 | * |
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9 | * Permission to use, modify and distribute this software is granted |
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10 | * provided that this copyright notice appears in all copies. For |
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11 | * precise terms see the accompanying LICENSE file. |
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12 | * |
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13 | * This software is provided "AS IS" with no warranty of any kind, |
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14 | * express or implied, and with no claim as to its suitability for any |
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15 | * purpose. |
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16 | * |
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17 | */ |
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18 | |
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19 | #include "test_tools.h" |
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20 | |
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21 | #ifdef HAVE_CONFIG_H |
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22 | #include <lemon/config.h> |
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23 | #endif |
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24 | |
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25 | #ifdef HAVE_CPLEX |
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26 | #include <lemon/cplex.h> |
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27 | #endif |
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28 | |
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29 | #ifdef HAVE_GLPK |
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30 | #include <lemon/glpk.h> |
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31 | #endif |
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32 | |
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33 | #ifdef HAVE_CBC |
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34 | #include <lemon/cbc.h> |
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35 | #endif |
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36 | |
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37 | |
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38 | using namespace lemon; |
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39 | |
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40 | void solveAndCheck(MipSolver& mip, MipSolver::ProblemType stat, |
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41 | double exp_opt) { |
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42 | using std::string; |
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43 | |
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44 | mip.solve(); |
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45 | //int decimal,sign; |
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46 | std::ostringstream buf; |
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47 | buf << "Type should be: " << int(stat)<<" and it is "<<int(mip.type()); |
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48 | |
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49 | |
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50 | // itoa(stat,buf1, 10); |
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51 | check(mip.type()==stat, buf.str()); |
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52 | |
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53 | if (stat == MipSolver::OPTIMAL) { |
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54 | std::ostringstream sbuf; |
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55 | buf << "Wrong optimal value: the right optimum is " << exp_opt; |
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56 | check(std::abs(mip.solValue()-exp_opt) < 1e-3, sbuf.str()); |
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57 | //+ecvt(exp_opt,2) |
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58 | } |
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59 | } |
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60 | |
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61 | void aTest(MipSolver& mip) |
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62 | { |
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63 | //The following example is very simple |
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64 | |
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65 | |
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66 | typedef MipSolver::Row Row; |
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67 | typedef MipSolver::Col Col; |
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68 | |
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69 | |
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70 | Col x1 = mip.addCol(); |
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71 | Col x2 = mip.addCol(); |
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72 | |
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73 | |
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74 | //Objective function |
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75 | mip.obj(x1); |
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76 | |
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77 | mip.max(); |
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78 | |
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79 | //Unconstrained optimization |
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80 | mip.solve(); |
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81 | //Check it out! |
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82 | |
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83 | //Constraints |
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84 | mip.addRow(2 * x1 + x2 <= 2); |
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85 | Row y2 = mip.addRow(x1 - 2 * x2 <= 0); |
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86 | |
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87 | //Nonnegativity of the variable x1 |
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88 | mip.colLowerBound(x1, 0); |
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89 | |
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90 | |
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91 | //Maximization of x1 |
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92 | //over the triangle with vertices (0,0),(4/5,2/5),(0,2) |
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93 | double expected_opt=4.0/5.0; |
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94 | solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt); |
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95 | |
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96 | |
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97 | //Restrict x2 to integer |
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98 | mip.colType(x2,MipSolver::INTEGER); |
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99 | expected_opt=1.0/2.0; |
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100 | solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt); |
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101 | |
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102 | |
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103 | //Restrict both to integer |
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104 | mip.colType(x1,MipSolver::INTEGER); |
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105 | expected_opt=0; |
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106 | solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt); |
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107 | |
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108 | //Erase a variable |
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109 | mip.erase(x2); |
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110 | mip.rowUpperBound(y2, 8); |
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111 | expected_opt=1; |
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112 | solveAndCheck(mip, MipSolver::OPTIMAL, expected_opt); |
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113 | |
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114 | } |
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115 | |
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116 | |
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117 | template<class MIP> |
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118 | void cloneTest() |
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119 | { |
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120 | |
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121 | MIP* mip = new MIP(); |
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122 | MIP* mipnew = mip->newSolver(); |
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123 | MIP* mipclone = mip->cloneSolver(); |
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124 | delete mip; |
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125 | delete mipnew; |
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126 | delete mipclone; |
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127 | } |
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128 | |
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129 | int main() |
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130 | { |
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131 | |
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132 | #ifdef HAVE_GLPK |
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133 | { |
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134 | GlpkMip mip1; |
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135 | aTest(mip1); |
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136 | cloneTest<GlpkMip>(); |
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137 | } |
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138 | #endif |
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139 | |
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140 | #ifdef HAVE_CPLEX |
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141 | try { |
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142 | CplexMip mip2; |
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143 | aTest(mip2); |
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144 | cloneTest<CplexMip>(); |
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145 | } catch (CplexEnv::LicenseError& error) { |
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146 | check(false, error.what()); |
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147 | } |
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148 | #endif |
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149 | |
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150 | #ifdef HAVE_CBC |
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151 | { |
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152 | CbcMip mip1; |
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153 | aTest(mip1); |
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154 | cloneTest<CbcMip>(); |
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155 | } |
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156 | #endif |
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157 | |
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158 | return 0; |
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159 | |
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160 | } |
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