1 | /* $Id: CbcHeuristic.hpp 1393 2009-12-11 00:29:38Z lou $ */ |
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2 | // Copyright (C) 2002, International Business Machines |
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3 | // Corporation and others. All Rights Reserved. |
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4 | #ifndef CbcHeuristic_H |
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5 | #define CbcHeuristic_H |
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6 | |
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7 | #include <string> |
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8 | #include <vector> |
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9 | #include "CoinPackedMatrix.hpp" |
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10 | #include "OsiCuts.hpp" |
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11 | #include "CoinHelperFunctions.hpp" |
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12 | #include "OsiBranchingObject.hpp" |
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13 | |
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14 | class OsiSolverInterface; |
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15 | |
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16 | class CbcModel; |
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17 | |
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18 | //############################################################################# |
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19 | |
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20 | class CbcHeuristicNodeList; |
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21 | class CbcBranchingObject; |
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22 | |
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23 | /** A class describing the branching decisions that were made to get |
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24 | to the node where a heuristics was invoked from */ |
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25 | |
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26 | class CbcHeuristicNode { |
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27 | private: |
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28 | void gutsOfConstructor(CbcModel& model); |
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29 | CbcHeuristicNode(); |
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30 | CbcHeuristicNode& operator=(const CbcHeuristicNode&); |
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31 | private: |
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32 | /// The number of branching decisions made |
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33 | int numObjects_; |
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34 | /** The indices of the branching objects. Note: an index may be |
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35 | listed multiple times. E.g., a general integer variable that has |
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36 | been branched on multiple times. */ |
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37 | CbcBranchingObject** brObj_; |
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38 | public: |
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39 | CbcHeuristicNode(CbcModel& model); |
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40 | |
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41 | CbcHeuristicNode(const CbcHeuristicNode& rhs); |
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42 | ~CbcHeuristicNode(); |
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43 | double distance(const CbcHeuristicNode* node) const; |
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44 | double minDistance(const CbcHeuristicNodeList& nodeList) const; |
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45 | bool minDistanceIsSmall(const CbcHeuristicNodeList& nodeList, |
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46 | const double threshold) const; |
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47 | double avgDistance(const CbcHeuristicNodeList& nodeList) const; |
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48 | }; |
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49 | |
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50 | class CbcHeuristicNodeList { |
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51 | private: |
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52 | void gutsOfDelete(); |
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53 | void gutsOfCopy(const CbcHeuristicNodeList& rhs); |
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54 | private: |
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55 | std::vector<CbcHeuristicNode*> nodes_; |
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56 | public: |
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57 | CbcHeuristicNodeList() {} |
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58 | CbcHeuristicNodeList(const CbcHeuristicNodeList& rhs); |
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59 | CbcHeuristicNodeList& operator=(const CbcHeuristicNodeList& rhs); |
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60 | ~CbcHeuristicNodeList(); |
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61 | |
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62 | void append(CbcHeuristicNode*& node); |
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63 | void append(const CbcHeuristicNodeList& nodes); |
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64 | inline const CbcHeuristicNode* node(int i) const { |
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65 | return nodes_[i]; |
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66 | } |
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67 | inline int size() const { |
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68 | return nodes_.size(); |
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69 | } |
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70 | }; |
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71 | |
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72 | //############################################################################# |
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73 | /** Heuristic base class */ |
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74 | |
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75 | class CbcHeuristic { |
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76 | private: |
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77 | void gutsOfDelete() {} |
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78 | void gutsOfCopy(const CbcHeuristic & rhs); |
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79 | |
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80 | public: |
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81 | // Default Constructor |
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82 | CbcHeuristic (); |
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83 | |
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84 | // Constructor with model - assumed before cuts |
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85 | CbcHeuristic (CbcModel & model); |
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86 | |
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87 | // Copy constructor |
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88 | CbcHeuristic ( const CbcHeuristic &); |
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89 | |
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90 | virtual ~CbcHeuristic(); |
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91 | |
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92 | /// Clone |
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93 | virtual CbcHeuristic * clone() const = 0; |
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94 | |
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95 | /// Assignment operator |
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96 | CbcHeuristic & operator=(const CbcHeuristic& rhs); |
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97 | |
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98 | /// update model (This is needed if cliques update matrix etc) |
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99 | virtual void setModel(CbcModel * model); |
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100 | |
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101 | /// Resets stuff if model changes |
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102 | virtual void resetModel(CbcModel * model) = 0; |
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103 | |
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104 | /** returns 0 if no solution, 1 if valid solution |
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105 | with better objective value than one passed in |
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106 | Sets solution values if good, sets objective value |
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107 | This is called after cuts have been added - so can not add cuts |
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108 | */ |
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109 | virtual int solution(double & objectiveValue, |
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110 | double * newSolution) = 0; |
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111 | |
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112 | /** returns 0 if no solution, 1 if valid solution, -1 if just |
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113 | returning an estimate of best possible solution |
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114 | with better objective value than one passed in |
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115 | Sets solution values if good, sets objective value (only if nonzero code) |
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116 | This is called at same time as cut generators - so can add cuts |
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117 | Default is do nothing |
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118 | */ |
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119 | virtual int solution2(double & /*objectiveValue*/, |
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120 | double * /*newSolution*/, |
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121 | OsiCuts & /*cs*/) { |
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122 | return 0; |
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123 | } |
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124 | |
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125 | /// Validate model i.e. sets when_ to 0 if necessary (may be NULL) |
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126 | virtual void validate() {} |
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127 | |
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128 | /** Sets "when" flag - 0 off, 1 at root, 2 other than root, 3 always. |
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129 | If 10 added then don't worry if validate says there are funny objects |
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130 | as user knows it will be fine |
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131 | */ |
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132 | inline void setWhen(int value) { |
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133 | when_ = value; |
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134 | } |
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135 | /// Gets "when" flag - 0 off, 1 at root, 2 other than root, 3 always |
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136 | inline int when() const { |
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137 | return when_; |
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138 | } |
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139 | |
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140 | /// Sets number of nodes in subtree (default 200) |
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141 | inline void setNumberNodes(int value) { |
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142 | numberNodes_ = value; |
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143 | } |
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144 | /// Gets number of nodes in a subtree (default 200) |
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145 | inline int numberNodes() const { |
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146 | return numberNodes_; |
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147 | } |
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148 | /** Switches (does not apply equally to all heuristics) |
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149 | 1 bit - stop once allowable gap on objective reached |
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150 | 2 bit - always do given number of passes |
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151 | 4 bit - weaken cutoff by 5% every 50 passes? |
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152 | 8 bit - if has cutoff and suminf bobbling for 20 passes then |
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153 | first try halving distance to best possible then |
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154 | try keep halving distance to known cutoff |
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155 | 1024 bit - stop all heuristics on max time |
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156 | */ |
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157 | inline void setSwitches(int value) { |
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158 | switches_ = value; |
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159 | } |
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160 | /** Switches (does not apply equally to all heuristics) |
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161 | 1 bit - stop once allowable gap on objective reached |
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162 | 2 bit - always do given number of passes |
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163 | 4 bit - weaken cutoff by 5% every 50 passes? |
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164 | 8 bit - if has cutoff and suminf bobbling for 20 passes then |
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165 | first try halving distance to best possible then |
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166 | try keep halving distance to known cutoff |
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167 | 1024 bit - stop all heuristics on max time |
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168 | */ |
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169 | inline int switches() const { |
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170 | return switches_; |
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171 | } |
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172 | /// Whether to exit at once on gap |
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173 | bool exitNow(double bestObjective) const; |
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174 | /// Sets feasibility pump options (-1 is off) |
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175 | inline void setFeasibilityPumpOptions(int value) { |
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176 | feasibilityPumpOptions_ = value; |
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177 | } |
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178 | /// Gets feasibility pump options (-1 is off) |
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179 | inline int feasibilityPumpOptions() const { |
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180 | return feasibilityPumpOptions_; |
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181 | } |
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182 | /// Just set model - do not do anything else |
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183 | inline void setModelOnly(CbcModel * model) { |
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184 | model_ = model; |
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185 | } |
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186 | |
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187 | |
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188 | /// Sets fraction of new(rows+columns)/old(rows+columns) before doing small branch and bound (default 1.0) |
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189 | inline void setFractionSmall(double value) { |
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190 | fractionSmall_ = value; |
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191 | } |
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192 | /// Gets fraction of new(rows+columns)/old(rows+columns) before doing small branch and bound (default 1.0) |
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193 | inline double fractionSmall() const { |
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194 | return fractionSmall_; |
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195 | } |
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196 | /// Get how many solutions the heuristic thought it got |
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197 | inline int numberSolutionsFound() const { |
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198 | return numberSolutionsFound_; |
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199 | } |
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200 | /// Increment how many solutions the heuristic thought it got |
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201 | inline void incrementNumberSolutionsFound() { |
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202 | numberSolutionsFound_++; |
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203 | } |
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204 | |
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205 | /** Do mini branch and bound - return |
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206 | 0 not finished - no solution |
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207 | 1 not finished - solution |
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208 | 2 finished - no solution |
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209 | 3 finished - solution |
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210 | (could add global cut if finished) |
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211 | -1 returned on size |
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212 | -2 time or user event |
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213 | */ |
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214 | int smallBranchAndBound(OsiSolverInterface * solver, int numberNodes, |
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215 | double * newSolution, double & newSolutionValue, |
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216 | double cutoff , std::string name) const; |
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217 | /// Create C++ lines to get to current state |
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218 | virtual void generateCpp( FILE * ) {} |
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219 | /// Create C++ lines to get to current state - does work for base class |
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220 | void generateCpp( FILE * fp, const char * heuristic) ; |
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221 | /// Returns true if can deal with "odd" problems e.g. sos type 2 |
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222 | virtual bool canDealWithOdd() const { |
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223 | return false; |
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224 | } |
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225 | /// return name of heuristic |
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226 | inline const char *heuristicName() const { |
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227 | return heuristicName_.c_str(); |
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228 | } |
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229 | /// set name of heuristic |
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230 | inline void setHeuristicName(const char *name) { |
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231 | heuristicName_ = name; |
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232 | } |
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233 | /// Set random number generator seed |
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234 | void setSeed(int value); |
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235 | /// Sets decay factor (for howOften) on failure |
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236 | inline void setDecayFactor(double value) { |
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237 | decayFactor_ = value; |
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238 | } |
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239 | /// Set input solution |
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240 | void setInputSolution(const double * solution, double objValue); |
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241 | /* Runs if bit set |
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242 | 0 - before cuts at root node (or from doHeuristics) |
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243 | 1 - during cuts at root |
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244 | 2 - after root node cuts |
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245 | 3 - after cuts at other nodes |
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246 | 4 - during cuts at other nodes |
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247 | 8 added if previous heuristic in loop found solution |
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248 | */ |
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249 | inline void setWhereFrom(int value) { |
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250 | whereFrom_ = value; |
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251 | } |
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252 | /** Upto this depth we call the tree shallow and the heuristic can be called |
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253 | multiple times. That is, the test whether the current node is far from |
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254 | the others where the jeuristic was invoked will not be done, only the |
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255 | frequency will be tested. After that depth the heuristic will can be |
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256 | invoked only once per node, right before branching. That's when it'll be |
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257 | tested whether the heur should run at all. */ |
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258 | inline void setShallowDepth(int value) { |
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259 | shallowDepth_ = value; |
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260 | } |
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261 | /** How often to invoke the heuristics in the shallow part of the tree */ |
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262 | inline void setHowOftenShallow(int value) { |
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263 | howOftenShallow_ = value; |
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264 | } |
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265 | /** How "far" should this node be from every other where the heuristic was |
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266 | run in order to allow the heuristic to run in this node, too. Currently |
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267 | this is tested, but we may switch to avgDistanceToRun_ in the future. */ |
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268 | inline void setMinDistanceToRun(int value) { |
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269 | minDistanceToRun_ = value; |
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270 | } |
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271 | |
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272 | /** Check whether the heuristic should run at all |
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273 | 0 - before cuts at root node (or from doHeuristics) |
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274 | 1 - during cuts at root |
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275 | 2 - after root node cuts |
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276 | 3 - after cuts at other nodes |
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277 | 4 - during cuts at other nodes |
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278 | 8 added if previous heuristic in loop found solution |
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279 | */ |
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280 | virtual bool shouldHeurRun(int whereFrom); |
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281 | /** Check whether the heuristic should run this time */ |
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282 | bool shouldHeurRun_randomChoice(); |
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283 | void debugNodes(); |
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284 | void printDistanceToNodes(); |
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285 | /// how many times the heuristic has actually run |
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286 | inline int numRuns() const { |
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287 | return numRuns_; |
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288 | } |
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289 | |
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290 | /// How many times the heuristic could run |
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291 | inline int numCouldRun() const { |
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292 | return numCouldRun_; |
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293 | } |
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294 | /** Clone but .. |
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295 | type 0 clone solver, 1 clone continuous solver |
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296 | Add 2 to say without integer variables which are at low priority |
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297 | Add 4 to say quite likely infeasible so give up easily.*/ |
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298 | OsiSolverInterface * cloneBut(int type); |
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299 | protected: |
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300 | |
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301 | /// Model |
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302 | CbcModel * model_; |
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303 | /// When flag - 0 off, 1 at root, 2 other than root, 3 always |
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304 | int when_; |
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305 | /// Number of nodes in any sub tree |
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306 | int numberNodes_; |
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307 | /// Feasibility pump options (-1 is off) |
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308 | int feasibilityPumpOptions_; |
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309 | /// Fraction of new(rows+columns)/old(rows+columns) before doing small branch and bound |
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310 | mutable double fractionSmall_; |
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311 | /// Thread specific random number generator |
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312 | CoinThreadRandom randomNumberGenerator_; |
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313 | /// Name for printing |
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314 | std::string heuristicName_; |
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315 | |
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316 | /// How often to do (code can change) |
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317 | int howOften_; |
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318 | /// How much to increase how often |
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319 | double decayFactor_; |
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320 | /** Switches (does not apply equally to all heuristics) |
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321 | 1 bit - stop once allowable gap on objective reached |
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322 | 2 bit - always do given number of passes |
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323 | 4 bit - weaken cutoff by 5% every 50 passes? |
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324 | 8 bit - if has cutoff and suminf bobbling for 20 passes then |
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325 | first try halving distance to best possible then |
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326 | try keep halving distance to known cutoff |
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327 | 1024 bit - stop all heuristics on max time |
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328 | */ |
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329 | mutable int switches_; |
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330 | /* Runs if bit set |
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331 | 0 - before cuts at root node (or from doHeuristics) |
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332 | 1 - during cuts at root |
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333 | 2 - after root node cuts |
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334 | 3 - after cuts at other nodes |
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335 | 4 - during cuts at other nodes |
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336 | 8 added if previous heuristic in loop found solution |
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337 | */ |
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338 | int whereFrom_; |
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339 | /** Upto this depth we call the tree shallow and the heuristic can be called |
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340 | multiple times. That is, the test whether the current node is far from |
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341 | the others where the jeuristic was invoked will not be done, only the |
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342 | frequency will be tested. After that depth the heuristic will can be |
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343 | invoked only once per node, right before branching. That's when it'll be |
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344 | tested whether the heur should run at all. */ |
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345 | int shallowDepth_; |
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346 | /** How often to invoke the heuristics in the shallow part of the tree */ |
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347 | int howOftenShallow_; |
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348 | /** How many invocations happened within the same node when in a shallow |
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349 | part of the tree. */ |
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350 | int numInvocationsInShallow_; |
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351 | /** How many invocations happened when in the deep part of the tree. For |
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352 | every node we count only one invocation. */ |
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353 | int numInvocationsInDeep_; |
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354 | /** After how many deep invocations was the heuristic run last time */ |
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355 | int lastRunDeep_; |
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356 | /// how many times the heuristic has actually run |
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357 | int numRuns_; |
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358 | /** How "far" should this node be from every other where the heuristic was |
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359 | run in order to allow the heuristic to run in this node, too. Currently |
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360 | this is tested, but we may switch to avgDistanceToRun_ in the future. */ |
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361 | int minDistanceToRun_; |
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362 | |
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363 | /// The description of the nodes where this heuristic has been applied |
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364 | CbcHeuristicNodeList runNodes_; |
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365 | |
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366 | /// How many times the heuristic could run |
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367 | int numCouldRun_; |
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368 | |
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369 | /// How many solutions the heuristic thought it got |
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370 | int numberSolutionsFound_; |
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371 | |
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372 | // Input solution - so can be used as seed |
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373 | double * inputSolution_; |
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374 | |
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375 | |
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376 | #ifdef JJF_ZERO |
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377 | /// Lower bounds of last node where the heuristic found a solution |
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378 | double * lowerBoundLastNode_; |
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379 | /// Upper bounds of last node where the heuristic found a solution |
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380 | double * upperBoundLastNode_; |
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381 | #endif |
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382 | }; |
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383 | /** Rounding class |
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384 | */ |
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385 | |
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386 | class CbcRounding : public CbcHeuristic { |
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387 | public: |
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388 | |
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389 | // Default Constructor |
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390 | CbcRounding (); |
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391 | |
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392 | // Constructor with model - assumed before cuts |
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393 | CbcRounding (CbcModel & model); |
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394 | |
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395 | // Copy constructor |
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396 | CbcRounding ( const CbcRounding &); |
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397 | |
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398 | // Destructor |
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399 | ~CbcRounding (); |
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400 | |
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401 | /// Assignment operator |
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402 | CbcRounding & operator=(const CbcRounding& rhs); |
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403 | |
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404 | /// Clone |
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405 | virtual CbcHeuristic * clone() const; |
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406 | /// Create C++ lines to get to current state |
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407 | virtual void generateCpp( FILE * fp) ; |
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408 | |
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409 | /// Resets stuff if model changes |
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410 | virtual void resetModel(CbcModel * model); |
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411 | |
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412 | /// update model (This is needed if cliques update matrix etc) |
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413 | virtual void setModel(CbcModel * model); |
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414 | |
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415 | using CbcHeuristic::solution ; |
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416 | /** returns 0 if no solution, 1 if valid solution |
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417 | with better objective value than one passed in |
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418 | Sets solution values if good, sets objective value (only if good) |
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419 | This is called after cuts have been added - so can not add cuts |
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420 | */ |
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421 | virtual int solution(double & objectiveValue, |
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422 | double * newSolution); |
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423 | /** returns 0 if no solution, 1 if valid solution |
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424 | with better objective value than one passed in |
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425 | Sets solution values if good, sets objective value (only if good) |
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426 | This is called after cuts have been added - so can not add cuts |
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427 | Use solutionValue rather than solvers one |
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428 | */ |
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429 | virtual int solution(double & objectiveValue, |
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430 | double * newSolution, |
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431 | double solutionValue); |
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432 | /// Validate model i.e. sets when_ to 0 if necessary (may be NULL) |
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433 | virtual void validate(); |
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434 | |
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435 | |
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436 | /// Set seed |
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437 | void setSeed(int value) { |
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438 | seed_ = value; |
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439 | } |
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440 | |
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441 | protected: |
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442 | // Data |
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443 | |
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444 | // Original matrix by column |
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445 | CoinPackedMatrix matrix_; |
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446 | |
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447 | // Original matrix by |
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448 | CoinPackedMatrix matrixByRow_; |
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449 | |
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450 | // Down locks |
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451 | unsigned short * down_; |
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452 | |
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453 | // Up locks |
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454 | unsigned short * up_; |
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455 | |
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456 | // Equality locks |
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457 | unsigned short * equal_; |
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458 | |
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459 | // Seed for random stuff |
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460 | int seed_; |
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461 | }; |
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462 | |
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463 | /** Partial solution class |
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464 | If user knows a partial solution this tries to get an integer solution |
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465 | it uses hotstart information |
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466 | */ |
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467 | |
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468 | class CbcHeuristicPartial : public CbcHeuristic { |
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469 | public: |
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470 | |
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471 | // Default Constructor |
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472 | CbcHeuristicPartial (); |
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473 | |
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474 | /** Constructor with model - assumed before cuts |
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475 | Fixes all variables with priority <= given |
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476 | and does given number of nodes |
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477 | */ |
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478 | CbcHeuristicPartial (CbcModel & model, int fixPriority = 10000, int numberNodes = 200); |
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479 | |
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480 | // Copy constructor |
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481 | CbcHeuristicPartial ( const CbcHeuristicPartial &); |
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482 | |
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483 | // Destructor |
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484 | ~CbcHeuristicPartial (); |
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485 | |
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486 | /// Assignment operator |
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487 | CbcHeuristicPartial & operator=(const CbcHeuristicPartial& rhs); |
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488 | |
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489 | /// Clone |
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490 | virtual CbcHeuristic * clone() const; |
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491 | /// Create C++ lines to get to current state |
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492 | virtual void generateCpp( FILE * fp) ; |
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493 | |
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494 | /// Resets stuff if model changes |
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495 | virtual void resetModel(CbcModel * model); |
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496 | |
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497 | /// update model (This is needed if cliques update matrix etc) |
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498 | virtual void setModel(CbcModel * model); |
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499 | |
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500 | using CbcHeuristic::solution ; |
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501 | /** returns 0 if no solution, 1 if valid solution |
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502 | with better objective value than one passed in |
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503 | Sets solution values if good, sets objective value (only if good) |
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504 | This is called after cuts have been added - so can not add cuts |
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505 | */ |
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506 | virtual int solution(double & objectiveValue, |
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507 | double * newSolution); |
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508 | /// Validate model i.e. sets when_ to 0 if necessary (may be NULL) |
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509 | virtual void validate(); |
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510 | |
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511 | |
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512 | /// Set priority level |
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513 | void setFixPriority(int value) { |
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514 | fixPriority_ = value; |
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515 | } |
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516 | |
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517 | /** Check whether the heuristic should run at all */ |
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518 | virtual bool shouldHeurRun(int whereFrom); |
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519 | |
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520 | protected: |
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521 | // Data |
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522 | |
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523 | // All variables with abs priority <= this will be fixed |
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524 | int fixPriority_; |
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525 | }; |
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526 | |
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527 | /** heuristic - just picks up any good solution |
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528 | found by solver - see OsiBabSolver |
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529 | */ |
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530 | |
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531 | class CbcSerendipity : public CbcHeuristic { |
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532 | public: |
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533 | |
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534 | // Default Constructor |
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535 | CbcSerendipity (); |
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536 | |
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537 | /* Constructor with model |
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538 | */ |
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539 | CbcSerendipity (CbcModel & model); |
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540 | |
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541 | // Copy constructor |
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542 | CbcSerendipity ( const CbcSerendipity &); |
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543 | |
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544 | // Destructor |
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545 | ~CbcSerendipity (); |
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546 | |
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547 | /// Assignment operator |
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548 | CbcSerendipity & operator=(const CbcSerendipity& rhs); |
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549 | |
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550 | /// Clone |
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551 | virtual CbcHeuristic * clone() const; |
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552 | /// Create C++ lines to get to current state |
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553 | virtual void generateCpp( FILE * fp) ; |
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554 | |
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555 | /// update model |
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556 | virtual void setModel(CbcModel * model); |
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557 | |
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558 | using CbcHeuristic::solution ; |
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559 | /** returns 0 if no solution, 1 if valid solution. |
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560 | Sets solution values if good, sets objective value (only if good) |
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561 | We leave all variables which are at one at this node of the |
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562 | tree to that value and will |
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563 | initially set all others to zero. We then sort all variables in order of their cost |
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564 | divided by the number of entries in rows which are not yet covered. We randomize that |
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565 | value a bit so that ties will be broken in different ways on different runs of the heuristic. |
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566 | We then choose the best one and set it to one and repeat the exercise. |
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567 | |
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568 | */ |
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569 | virtual int solution(double & objectiveValue, |
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570 | double * newSolution); |
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571 | /// Resets stuff if model changes |
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572 | virtual void resetModel(CbcModel * model); |
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573 | |
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574 | protected: |
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575 | }; |
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576 | |
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577 | /** Just One class - this chooses one at random |
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578 | */ |
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579 | |
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580 | class CbcHeuristicJustOne : public CbcHeuristic { |
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581 | public: |
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582 | |
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583 | // Default Constructor |
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584 | CbcHeuristicJustOne (); |
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585 | |
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586 | // Constructor with model - assumed before cuts |
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587 | CbcHeuristicJustOne (CbcModel & model); |
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588 | |
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589 | // Copy constructor |
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590 | CbcHeuristicJustOne ( const CbcHeuristicJustOne &); |
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591 | |
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592 | // Destructor |
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593 | ~CbcHeuristicJustOne (); |
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594 | |
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595 | /// Clone |
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596 | virtual CbcHeuristicJustOne * clone() const; |
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597 | |
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598 | /// Assignment operator |
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599 | CbcHeuristicJustOne & operator=(const CbcHeuristicJustOne& rhs); |
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600 | |
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601 | /// Create C++ lines to get to current state |
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602 | virtual void generateCpp( FILE * fp) ; |
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603 | |
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604 | /** returns 0 if no solution, 1 if valid solution |
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605 | with better objective value than one passed in |
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606 | Sets solution values if good, sets objective value (only if good) |
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607 | This is called after cuts have been added - so can not add cuts |
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608 | This does Fractional Diving |
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609 | */ |
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610 | virtual int solution(double & objectiveValue, |
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611 | double * newSolution); |
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612 | /// Resets stuff if model changes |
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613 | virtual void resetModel(CbcModel * model); |
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614 | |
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615 | /// update model (This is needed if cliques update matrix etc) |
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616 | virtual void setModel(CbcModel * model); |
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617 | /// Selects the next variable to branch on |
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618 | /** Returns true if all the fractional variables can be trivially |
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619 | rounded. Returns false, if there is at least one fractional variable |
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620 | that is not trivially roundable. In this case, the bestColumn |
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621 | returned will not be trivially roundable. |
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622 | This is dummy as never called |
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623 | */ |
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624 | virtual bool selectVariableToBranch(OsiSolverInterface* /*solver*/, |
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625 | const double* /*newSolution*/, |
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626 | int& /*bestColumn*/, |
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627 | int& /*bestRound*/) { |
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628 | return true; |
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629 | } |
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630 | /// Validate model i.e. sets when_ to 0 if necessary (may be NULL) |
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631 | virtual void validate(); |
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632 | /// Adds an heuristic with probability |
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633 | void addHeuristic(const CbcHeuristic * heuristic, double probability); |
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634 | /// Normalize probabilities |
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635 | void normalizeProbabilities(); |
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636 | protected: |
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637 | // Data |
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638 | |
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639 | // Probability of running a heuristic |
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640 | double * probabilities_; |
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641 | |
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642 | // Heuristics |
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643 | CbcHeuristic ** heuristic_; |
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644 | |
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645 | // Number of heuristics |
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646 | int numberHeuristics_; |
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647 | |
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648 | }; |
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649 | |
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650 | #endif |
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