1 | /* $Id: CbcHeuristic.hpp 1675 2011-06-19 17:23:14Z stefan $ */ |
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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 | // This code is licensed under the terms of the Eclipse Public License (EPL). |
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5 | |
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6 | #ifndef CbcHeuristic_H |
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7 | #define CbcHeuristic_H |
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8 | |
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9 | #include <string> |
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10 | #include <vector> |
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11 | #include "CoinPackedMatrix.hpp" |
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12 | #include "OsiCuts.hpp" |
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13 | #include "CoinHelperFunctions.hpp" |
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14 | #include "OsiBranchingObject.hpp" |
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15 | |
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16 | class OsiSolverInterface; |
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17 | |
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18 | class CbcModel; |
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19 | |
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20 | //############################################################################# |
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21 | |
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22 | class CbcHeuristicNodeList; |
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23 | class CbcBranchingObject; |
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24 | |
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25 | /** A class describing the branching decisions that were made to get |
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26 | to the node where a heuristic was invoked from */ |
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27 | |
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28 | class CbcHeuristicNode { |
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29 | private: |
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30 | void gutsOfConstructor(CbcModel& model); |
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31 | CbcHeuristicNode(); |
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32 | CbcHeuristicNode& operator=(const CbcHeuristicNode&); |
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33 | private: |
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34 | /// The number of branching decisions made |
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35 | int numObjects_; |
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36 | /** The indices of the branching objects. Note: an index may be |
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37 | listed multiple times. E.g., a general integer variable that has |
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38 | been branched on multiple times. */ |
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39 | CbcBranchingObject** brObj_; |
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40 | public: |
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41 | CbcHeuristicNode(CbcModel& model); |
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42 | |
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43 | CbcHeuristicNode(const CbcHeuristicNode& rhs); |
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44 | ~CbcHeuristicNode(); |
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45 | double distance(const CbcHeuristicNode* node) const; |
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46 | double minDistance(const CbcHeuristicNodeList& nodeList) const; |
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47 | bool minDistanceIsSmall(const CbcHeuristicNodeList& nodeList, |
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48 | const double threshold) const; |
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49 | double avgDistance(const CbcHeuristicNodeList& nodeList) const; |
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50 | }; |
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51 | |
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52 | class CbcHeuristicNodeList { |
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53 | private: |
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54 | void gutsOfDelete(); |
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55 | void gutsOfCopy(const CbcHeuristicNodeList& rhs); |
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56 | private: |
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57 | std::vector<CbcHeuristicNode*> nodes_; |
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58 | public: |
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59 | CbcHeuristicNodeList() {} |
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60 | CbcHeuristicNodeList(const CbcHeuristicNodeList& rhs); |
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61 | CbcHeuristicNodeList& operator=(const CbcHeuristicNodeList& rhs); |
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62 | ~CbcHeuristicNodeList(); |
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63 | |
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64 | void append(CbcHeuristicNode*& node); |
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65 | void append(const CbcHeuristicNodeList& nodes); |
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66 | inline const CbcHeuristicNode* node(int i) const { |
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67 | return nodes_[i]; |
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68 | } |
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69 | inline int size() const { |
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70 | return static_cast<int>(nodes_.size()); |
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71 | } |
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72 | }; |
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73 | |
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74 | //############################################################################# |
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75 | /** Heuristic base class */ |
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76 | |
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77 | class CbcHeuristic { |
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78 | private: |
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79 | void gutsOfDelete() {} |
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80 | void gutsOfCopy(const CbcHeuristic & rhs); |
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81 | |
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82 | public: |
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83 | // Default Constructor |
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84 | CbcHeuristic (); |
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85 | |
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86 | // Constructor with model - assumed before cuts |
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87 | CbcHeuristic (CbcModel & model); |
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88 | |
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89 | // Copy constructor |
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90 | CbcHeuristic ( const CbcHeuristic &); |
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91 | |
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92 | virtual ~CbcHeuristic(); |
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93 | |
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94 | /// Clone |
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95 | virtual CbcHeuristic * clone() const = 0; |
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96 | |
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97 | /// Assignment operator |
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98 | CbcHeuristic & operator=(const CbcHeuristic& rhs); |
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99 | |
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100 | /// update model (This is needed if cliques update matrix etc) |
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101 | virtual void setModel(CbcModel * model); |
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102 | |
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103 | /// Resets stuff if model changes |
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104 | virtual void resetModel(CbcModel * model) = 0; |
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105 | |
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106 | /** returns 0 if no solution, 1 if valid solution |
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107 | with better objective value than one passed in |
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108 | Sets solution values if good, sets objective value |
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109 | This is called after cuts have been added - so can not add cuts |
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110 | */ |
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111 | virtual int solution(double & objectiveValue, |
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112 | double * newSolution) = 0; |
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113 | |
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114 | /** returns 0 if no solution, 1 if valid solution, -1 if just |
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115 | returning an estimate of best possible solution |
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116 | with better objective value than one passed in |
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117 | Sets solution values if good, sets objective value (only if nonzero code) |
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118 | This is called at same time as cut generators - so can add cuts |
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119 | Default is do nothing |
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120 | */ |
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121 | virtual int solution2(double & /*objectiveValue*/, |
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122 | double * /*newSolution*/, |
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123 | OsiCuts & /*cs*/) { |
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124 | return 0; |
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125 | } |
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126 | |
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127 | /// Validate model i.e. sets when_ to 0 if necessary (may be NULL) |
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128 | virtual void validate() {} |
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129 | |
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130 | /** Sets "when" flag - 0 off, 1 at root, 2 other than root, 3 always. |
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131 | If 10 added then don't worry if validate says there are funny objects |
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132 | as user knows it will be fine |
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133 | */ |
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134 | inline void setWhen(int value) { |
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135 | when_ = value; |
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136 | } |
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137 | /// Gets "when" flag - 0 off, 1 at root, 2 other than root, 3 always |
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138 | inline int when() const { |
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139 | return when_; |
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140 | } |
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141 | |
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142 | /// Sets number of nodes in subtree (default 200) |
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143 | inline void setNumberNodes(int value) { |
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144 | numberNodes_ = value; |
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145 | } |
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146 | /// Gets number of nodes in a subtree (default 200) |
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147 | inline int numberNodes() const { |
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148 | return numberNodes_; |
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149 | } |
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150 | /** Switches (does not apply equally to all heuristics) |
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151 | 1 bit - stop once allowable gap on objective reached |
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152 | 2 bit - always do given number of passes |
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153 | 4 bit - weaken cutoff by 5% every 50 passes? |
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154 | 8 bit - if has cutoff and suminf bobbling for 20 passes then |
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155 | first try halving distance to best possible then |
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156 | try keep halving distance to known cutoff |
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157 | 1024 bit - stop all heuristics on max time |
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158 | */ |
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159 | inline void setSwitches(int value) { |
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160 | switches_ = value; |
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161 | } |
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162 | /** Switches (does not apply equally to all heuristics) |
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163 | 1 bit - stop once allowable gap on objective reached |
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164 | 2 bit - always do given number of passes |
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165 | 4 bit - weaken cutoff by 5% every 50 passes? |
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166 | 8 bit - if has cutoff and suminf bobbling for 20 passes then |
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167 | first try halving distance to best possible then |
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168 | try keep halving distance to known cutoff |
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169 | 1024 bit - stop all heuristics on max time |
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170 | */ |
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171 | inline int switches() const { |
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172 | return switches_; |
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173 | } |
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174 | /// Whether to exit at once on gap |
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175 | bool exitNow(double bestObjective) const; |
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176 | /// Sets feasibility pump options (-1 is off) |
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177 | inline void setFeasibilityPumpOptions(int value) { |
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178 | feasibilityPumpOptions_ = value; |
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179 | } |
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180 | /// Gets feasibility pump options (-1 is off) |
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181 | inline int feasibilityPumpOptions() const { |
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182 | return feasibilityPumpOptions_; |
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183 | } |
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184 | /// Just set model - do not do anything else |
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185 | inline void setModelOnly(CbcModel * model) { |
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186 | model_ = model; |
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187 | } |
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188 | |
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189 | |
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190 | /// Sets fraction of new(rows+columns)/old(rows+columns) before doing small branch and bound (default 1.0) |
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191 | inline void setFractionSmall(double value) { |
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192 | fractionSmall_ = value; |
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193 | } |
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194 | /// Gets fraction of new(rows+columns)/old(rows+columns) before doing small branch and bound (default 1.0) |
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195 | inline double fractionSmall() const { |
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196 | return fractionSmall_; |
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197 | } |
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198 | /// Get how many solutions the heuristic thought it got |
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199 | inline int numberSolutionsFound() const { |
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200 | return numberSolutionsFound_; |
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201 | } |
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202 | /// Increment how many solutions the heuristic thought it got |
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203 | inline void incrementNumberSolutionsFound() { |
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204 | numberSolutionsFound_++; |
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205 | } |
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206 | |
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207 | /** Do mini branch and bound - return |
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208 | 0 not finished - no solution |
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209 | 1 not finished - solution |
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210 | 2 finished - no solution |
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211 | 3 finished - solution |
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212 | (could add global cut if finished) |
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213 | -1 returned on size |
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214 | -2 time or user event |
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215 | */ |
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216 | int smallBranchAndBound(OsiSolverInterface * solver, int numberNodes, |
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217 | double * newSolution, double & newSolutionValue, |
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218 | double cutoff , std::string name) const; |
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219 | /// Create C++ lines to get to current state |
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220 | virtual void generateCpp( FILE * ) {} |
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221 | /// Create C++ lines to get to current state - does work for base class |
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222 | void generateCpp( FILE * fp, const char * heuristic) ; |
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223 | /// Returns true if can deal with "odd" problems e.g. sos type 2 |
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224 | virtual bool canDealWithOdd() const { |
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225 | return false; |
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226 | } |
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227 | /// return name of heuristic |
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228 | inline const char *heuristicName() const { |
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229 | return heuristicName_.c_str(); |
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230 | } |
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231 | /// set name of heuristic |
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232 | inline void setHeuristicName(const char *name) { |
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233 | heuristicName_ = name; |
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234 | } |
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235 | /// Set random number generator seed |
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236 | void setSeed(int value); |
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237 | /// Sets decay factor (for howOften) on failure |
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238 | inline void setDecayFactor(double value) { |
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239 | decayFactor_ = value; |
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240 | } |
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241 | /// Set input solution |
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242 | void setInputSolution(const double * solution, double objValue); |
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243 | /* Runs if bit set |
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244 | 0 - before cuts at root node (or from doHeuristics) |
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245 | 1 - during cuts at root |
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246 | 2 - after root node cuts |
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247 | 3 - after cuts at other nodes |
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248 | 4 - during cuts at other nodes |
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249 | 8 added if previous heuristic in loop found solution |
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250 | */ |
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251 | inline void setWhereFrom(int value) { |
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252 | whereFrom_ = value; |
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253 | } |
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254 | inline int whereFrom() const { |
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255 | return whereFrom_; |
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256 | } |
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257 | /** Upto this depth we call the tree shallow and the heuristic can be called |
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258 | multiple times. That is, the test whether the current node is far from |
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259 | the others where the jeuristic was invoked will not be done, only the |
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260 | frequency will be tested. After that depth the heuristic will can be |
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261 | invoked only once per node, right before branching. That's when it'll be |
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262 | tested whether the heur should run at all. */ |
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263 | inline void setShallowDepth(int value) { |
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264 | shallowDepth_ = value; |
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265 | } |
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266 | /** How often to invoke the heuristics in the shallow part of the tree */ |
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267 | inline void setHowOftenShallow(int value) { |
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268 | howOftenShallow_ = value; |
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269 | } |
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270 | /** How "far" should this node be from every other where the heuristic was |
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271 | run in order to allow the heuristic to run in this node, too. Currently |
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272 | this is tested, but we may switch to avgDistanceToRun_ in the future. */ |
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273 | inline void setMinDistanceToRun(int value) { |
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274 | minDistanceToRun_ = value; |
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275 | } |
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276 | |
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277 | /** Check whether the heuristic should run at all |
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278 | 0 - before cuts at root node (or from doHeuristics) |
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279 | 1 - during cuts at root |
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280 | 2 - after root node cuts |
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281 | 3 - after cuts at other nodes |
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282 | 4 - during cuts at other nodes |
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283 | 8 added if previous heuristic in loop found solution |
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284 | */ |
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285 | virtual bool shouldHeurRun(int whereFrom); |
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286 | /** Check whether the heuristic should run this time */ |
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287 | bool shouldHeurRun_randomChoice(); |
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288 | void debugNodes(); |
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289 | void printDistanceToNodes(); |
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290 | /// how many times the heuristic has actually run |
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291 | inline int numRuns() const { |
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292 | return numRuns_; |
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293 | } |
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294 | |
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295 | /// How many times the heuristic could run |
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296 | inline int numCouldRun() const { |
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297 | return numCouldRun_; |
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298 | } |
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299 | /*! \brief Clone, but ... |
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300 | |
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301 | If type is |
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302 | - 0 clone the solver for the model, |
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303 | - 1 clone the continuous solver for the model |
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304 | - Add 2 to say without integer variables which are at low priority |
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305 | - Add 4 to say quite likely infeasible so give up easily (clp only). |
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306 | */ |
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307 | OsiSolverInterface * cloneBut(int type); |
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308 | protected: |
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309 | |
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310 | /// Model |
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311 | CbcModel * model_; |
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312 | /// When flag - 0 off, 1 at root, 2 other than root, 3 always |
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313 | int when_; |
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314 | /// Number of nodes in any sub tree |
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315 | int numberNodes_; |
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316 | /// Feasibility pump options (-1 is off) |
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317 | int feasibilityPumpOptions_; |
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318 | /// Fraction of new(rows+columns)/old(rows+columns) before doing small branch and bound |
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319 | mutable double fractionSmall_; |
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320 | /// Thread specific random number generator |
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321 | CoinThreadRandom randomNumberGenerator_; |
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322 | /// Name for printing |
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323 | std::string heuristicName_; |
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324 | |
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325 | /// How often to do (code can change) |
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326 | int howOften_; |
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327 | /// How much to increase how often |
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328 | double decayFactor_; |
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329 | /** Switches (does not apply equally to all heuristics) |
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330 | 1 bit - stop once allowable gap on objective reached |
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331 | 2 bit - always do given number of passes |
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332 | 4 bit - weaken cutoff by 5% every 50 passes? |
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333 | 8 bit - if has cutoff and suminf bobbling for 20 passes then |
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334 | first try halving distance to best possible then |
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335 | try keep halving distance to known cutoff |
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336 | 1024 bit - stop all heuristics on max time |
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337 | */ |
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338 | mutable int switches_; |
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339 | /* Runs if bit set |
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340 | 0 - before cuts at root node (or from doHeuristics) |
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341 | 1 - during cuts at root |
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342 | 2 - after root node cuts |
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343 | 3 - after cuts at other nodes |
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344 | 4 - during cuts at other nodes |
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345 | 8 added if previous heuristic in loop found solution |
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346 | */ |
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347 | int whereFrom_; |
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348 | /** Upto this depth we call the tree shallow and the heuristic can be called |
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349 | multiple times. That is, the test whether the current node is far from |
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350 | the others where the jeuristic was invoked will not be done, only the |
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351 | frequency will be tested. After that depth the heuristic will can be |
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352 | invoked only once per node, right before branching. That's when it'll be |
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353 | tested whether the heur should run at all. */ |
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354 | int shallowDepth_; |
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355 | /** How often to invoke the heuristics in the shallow part of the tree */ |
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356 | int howOftenShallow_; |
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357 | /** How many invocations happened within the same node when in a shallow |
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358 | part of the tree. */ |
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359 | int numInvocationsInShallow_; |
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360 | /** How many invocations happened when in the deep part of the tree. For |
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361 | every node we count only one invocation. */ |
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362 | int numInvocationsInDeep_; |
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363 | /** After how many deep invocations was the heuristic run last time */ |
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364 | int lastRunDeep_; |
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365 | /// how many times the heuristic has actually run |
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366 | int numRuns_; |
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367 | /** How "far" should this node be from every other where the heuristic was |
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368 | run in order to allow the heuristic to run in this node, too. Currently |
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369 | this is tested, but we may switch to avgDistanceToRun_ in the future. */ |
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370 | int minDistanceToRun_; |
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371 | |
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372 | /// The description of the nodes where this heuristic has been applied |
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373 | CbcHeuristicNodeList runNodes_; |
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374 | |
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375 | /// How many times the heuristic could run |
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376 | int numCouldRun_; |
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377 | |
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378 | /// How many solutions the heuristic thought it got |
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379 | int numberSolutionsFound_; |
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380 | |
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381 | // Input solution - so can be used as seed |
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382 | double * inputSolution_; |
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383 | |
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384 | |
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385 | #ifdef JJF_ZERO |
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386 | /// Lower bounds of last node where the heuristic found a solution |
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387 | double * lowerBoundLastNode_; |
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388 | /// Upper bounds of last node where the heuristic found a solution |
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389 | double * upperBoundLastNode_; |
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390 | #endif |
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391 | }; |
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392 | /** Rounding class |
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393 | */ |
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394 | |
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395 | class CbcRounding : public CbcHeuristic { |
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396 | public: |
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397 | |
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398 | // Default Constructor |
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399 | CbcRounding (); |
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400 | |
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401 | // Constructor with model - assumed before cuts |
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402 | CbcRounding (CbcModel & model); |
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403 | |
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404 | // Copy constructor |
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405 | CbcRounding ( const CbcRounding &); |
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406 | |
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407 | // Destructor |
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408 | ~CbcRounding (); |
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409 | |
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410 | /// Assignment operator |
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411 | CbcRounding & operator=(const CbcRounding& rhs); |
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412 | |
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413 | /// Clone |
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414 | virtual CbcHeuristic * clone() const; |
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415 | /// Create C++ lines to get to current state |
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416 | virtual void generateCpp( FILE * fp) ; |
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417 | |
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418 | /// Resets stuff if model changes |
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419 | virtual void resetModel(CbcModel * model); |
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420 | |
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421 | /// update model (This is needed if cliques update matrix etc) |
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422 | virtual void setModel(CbcModel * model); |
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423 | |
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424 | using CbcHeuristic::solution ; |
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425 | /** returns 0 if no solution, 1 if valid solution |
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426 | with better objective value than one passed in |
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427 | Sets solution values if good, sets objective value (only if good) |
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428 | This is called after cuts have been added - so can not add cuts |
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429 | */ |
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430 | virtual int solution(double & objectiveValue, |
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431 | double * newSolution); |
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432 | /** returns 0 if no solution, 1 if valid solution |
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433 | with better objective value than one passed in |
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434 | Sets solution values if good, sets objective value (only if good) |
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435 | This is called after cuts have been added - so can not add cuts |
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436 | Use solutionValue rather than solvers one |
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437 | */ |
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438 | virtual int solution(double & objectiveValue, |
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439 | double * newSolution, |
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440 | double solutionValue); |
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441 | /// Validate model i.e. sets when_ to 0 if necessary (may be NULL) |
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442 | virtual void validate(); |
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443 | |
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444 | |
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445 | /// Set seed |
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446 | void setSeed(int value) { |
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447 | seed_ = value; |
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448 | } |
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449 | |
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450 | protected: |
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451 | // Data |
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452 | |
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453 | // Original matrix by column |
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454 | CoinPackedMatrix matrix_; |
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455 | |
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456 | // Original matrix by |
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457 | CoinPackedMatrix matrixByRow_; |
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458 | |
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459 | // Down locks |
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460 | unsigned short * down_; |
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461 | |
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462 | // Up locks |
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463 | unsigned short * up_; |
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464 | |
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465 | // Equality locks |
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466 | unsigned short * equal_; |
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467 | |
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468 | // Seed for random stuff |
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469 | int seed_; |
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470 | }; |
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471 | |
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472 | /** Partial solution class |
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473 | If user knows a partial solution this tries to get an integer solution |
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474 | it uses hotstart information |
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475 | */ |
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476 | |
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477 | class CbcHeuristicPartial : public CbcHeuristic { |
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478 | public: |
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479 | |
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480 | // Default Constructor |
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481 | CbcHeuristicPartial (); |
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482 | |
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483 | /** Constructor with model - assumed before cuts |
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484 | Fixes all variables with priority <= given |
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485 | and does given number of nodes |
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486 | */ |
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487 | CbcHeuristicPartial (CbcModel & model, int fixPriority = 10000, int numberNodes = 200); |
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488 | |
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489 | // Copy constructor |
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490 | CbcHeuristicPartial ( const CbcHeuristicPartial &); |
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491 | |
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492 | // Destructor |
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493 | ~CbcHeuristicPartial (); |
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494 | |
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495 | /// Assignment operator |
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496 | CbcHeuristicPartial & operator=(const CbcHeuristicPartial& rhs); |
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497 | |
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498 | /// Clone |
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499 | virtual CbcHeuristic * clone() const; |
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500 | /// Create C++ lines to get to current state |
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501 | virtual void generateCpp( FILE * fp) ; |
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502 | |
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503 | /// Resets stuff if model changes |
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504 | virtual void resetModel(CbcModel * model); |
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505 | |
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506 | /// update model (This is needed if cliques update matrix etc) |
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507 | virtual void setModel(CbcModel * model); |
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508 | |
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509 | using CbcHeuristic::solution ; |
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510 | /** returns 0 if no solution, 1 if valid solution |
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511 | with better objective value than one passed in |
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512 | Sets solution values if good, sets objective value (only if good) |
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513 | This is called after cuts have been added - so can not add cuts |
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514 | */ |
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515 | virtual int solution(double & objectiveValue, |
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516 | double * newSolution); |
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517 | /// Validate model i.e. sets when_ to 0 if necessary (may be NULL) |
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518 | virtual void validate(); |
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519 | |
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520 | |
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521 | /// Set priority level |
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522 | void setFixPriority(int value) { |
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523 | fixPriority_ = value; |
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524 | } |
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525 | |
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526 | /** Check whether the heuristic should run at all */ |
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527 | virtual bool shouldHeurRun(int whereFrom); |
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528 | |
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529 | protected: |
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530 | // Data |
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531 | |
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532 | // All variables with abs priority <= this will be fixed |
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533 | int fixPriority_; |
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534 | }; |
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535 | |
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536 | /** heuristic - just picks up any good solution |
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537 | found by solver - see OsiBabSolver |
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538 | */ |
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539 | |
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540 | class CbcSerendipity : public CbcHeuristic { |
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541 | public: |
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542 | |
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543 | // Default Constructor |
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544 | CbcSerendipity (); |
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545 | |
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546 | /* Constructor with model |
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547 | */ |
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548 | CbcSerendipity (CbcModel & model); |
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549 | |
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550 | // Copy constructor |
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551 | CbcSerendipity ( const CbcSerendipity &); |
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552 | |
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553 | // Destructor |
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554 | ~CbcSerendipity (); |
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555 | |
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556 | /// Assignment operator |
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557 | CbcSerendipity & operator=(const CbcSerendipity& rhs); |
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558 | |
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559 | /// Clone |
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560 | virtual CbcHeuristic * clone() const; |
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561 | /// Create C++ lines to get to current state |
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562 | virtual void generateCpp( FILE * fp) ; |
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563 | |
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564 | /// update model |
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565 | virtual void setModel(CbcModel * model); |
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566 | |
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567 | using CbcHeuristic::solution ; |
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568 | /** returns 0 if no solution, 1 if valid solution. |
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569 | Sets solution values if good, sets objective value (only if good) |
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570 | We leave all variables which are at one at this node of the |
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571 | tree to that value and will |
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572 | initially set all others to zero. We then sort all variables in order of their cost |
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573 | divided by the number of entries in rows which are not yet covered. We randomize that |
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574 | value a bit so that ties will be broken in different ways on different runs of the heuristic. |
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575 | We then choose the best one and set it to one and repeat the exercise. |
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576 | |
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577 | */ |
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578 | virtual int solution(double & objectiveValue, |
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579 | double * newSolution); |
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580 | /// Resets stuff if model changes |
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581 | virtual void resetModel(CbcModel * model); |
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582 | |
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583 | protected: |
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584 | }; |
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585 | |
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586 | /** Just One class - this chooses one at random |
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587 | */ |
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588 | |
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589 | class CbcHeuristicJustOne : public CbcHeuristic { |
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590 | public: |
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591 | |
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592 | // Default Constructor |
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593 | CbcHeuristicJustOne (); |
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594 | |
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595 | // Constructor with model - assumed before cuts |
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596 | CbcHeuristicJustOne (CbcModel & model); |
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597 | |
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598 | // Copy constructor |
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599 | CbcHeuristicJustOne ( const CbcHeuristicJustOne &); |
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600 | |
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601 | // Destructor |
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602 | ~CbcHeuristicJustOne (); |
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603 | |
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604 | /// Clone |
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605 | virtual CbcHeuristicJustOne * clone() const; |
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606 | |
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607 | /// Assignment operator |
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608 | CbcHeuristicJustOne & operator=(const CbcHeuristicJustOne& rhs); |
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609 | |
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610 | /// Create C++ lines to get to current state |
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611 | virtual void generateCpp( FILE * fp) ; |
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612 | |
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613 | /** returns 0 if no solution, 1 if valid solution |
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614 | with better objective value than one passed in |
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615 | Sets solution values if good, sets objective value (only if good) |
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616 | This is called after cuts have been added - so can not add cuts |
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617 | This does Fractional Diving |
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618 | */ |
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619 | virtual int solution(double & objectiveValue, |
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620 | double * newSolution); |
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621 | /// Resets stuff if model changes |
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622 | virtual void resetModel(CbcModel * model); |
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623 | |
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624 | /// update model (This is needed if cliques update matrix etc) |
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625 | virtual void setModel(CbcModel * model); |
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626 | /// Selects the next variable to branch on |
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627 | /** Returns true if all the fractional variables can be trivially |
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628 | rounded. Returns false, if there is at least one fractional variable |
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629 | that is not trivially roundable. In this case, the bestColumn |
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630 | returned will not be trivially roundable. |
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631 | This is dummy as never called |
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632 | */ |
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633 | virtual bool selectVariableToBranch(OsiSolverInterface* /*solver*/, |
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634 | const double* /*newSolution*/, |
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635 | int& /*bestColumn*/, |
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636 | int& /*bestRound*/) { |
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637 | return true; |
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638 | } |
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639 | /// Validate model i.e. sets when_ to 0 if necessary (may be NULL) |
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640 | virtual void validate(); |
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641 | /// Adds an heuristic with probability |
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642 | void addHeuristic(const CbcHeuristic * heuristic, double probability); |
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643 | /// Normalize probabilities |
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644 | void normalizeProbabilities(); |
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645 | protected: |
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646 | // Data |
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647 | |
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648 | // Probability of running a heuristic |
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649 | double * probabilities_; |
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650 | |
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651 | // Heuristics |
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652 | CbcHeuristic ** heuristic_; |
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653 | |
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654 | // Number of heuristics |
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655 | int numberHeuristics_; |
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656 | |
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657 | }; |
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658 | |
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659 | #endif |
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660 | |
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