1 | /* -*- C++ -*- |
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2 | * |
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3 | * This file is a part of LEMON, a generic C++ optimization library |
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4 | * |
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5 | * Copyright (C) 2003-2008 |
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6 | * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport |
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7 | * (Egervary Research Group on Combinatorial Optimization, EGRES). |
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8 | * |
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9 | * Permission to use, modify and distribute this software is granted |
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10 | * provided that this copyright notice appears in all copies. For |
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11 | * precise terms see the accompanying LICENSE file. |
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12 | * |
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13 | * This software is provided "AS IS" with no warranty of any kind, |
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14 | * express or implied, and with no claim as to its suitability for any |
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15 | * purpose. |
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16 | * |
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17 | */ |
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18 | |
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19 | #ifndef LEMON_SIMANN_H |
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20 | #define LEMON_SIMANN_H |
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21 | |
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22 | /// \ingroup experimental |
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23 | /// \file |
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24 | /// \brief Simulated annealing framework. |
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25 | /// |
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26 | /// \todo A test and some demo should be added |
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27 | /// \todo Doc should be improved |
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28 | /// \author Akos Ladanyi |
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29 | |
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30 | #include <cstdlib> |
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31 | #include <cmath> |
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32 | #include <limits> |
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33 | #include <lemon/time_measure.h> |
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34 | #include <lemon/random.h> |
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35 | |
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36 | namespace lemon { |
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37 | |
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38 | class SimAnnBase; |
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39 | |
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40 | /// \brief A base class for controllers. |
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41 | class ControllerBase { |
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42 | public: |
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43 | friend class SimAnnBase; |
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44 | /// \brief Pointer to the simulated annealing base class. |
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45 | SimAnnBase *simann; |
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46 | /// \brief Initializes the controller. |
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47 | virtual void init() {} |
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48 | /// \brief This is called by the simulated annealing class when a |
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49 | /// neighbouring state gets accepted. |
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50 | virtual void acceptEvent() {} |
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51 | /// \brief This is called by the simulated annealing class when the |
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52 | /// accepted neighbouring state's cost is less than the best found one's. |
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53 | virtual void improveEvent() {} |
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54 | /// \brief This is called by the simulated annealing class when a |
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55 | /// neighbouring state gets rejected. |
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56 | virtual void rejectEvent() {} |
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57 | /// \brief Decides whether to continue the annealing process or not. |
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58 | virtual bool next() = 0; |
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59 | /// \brief Decides whether to accept the current solution or not. |
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60 | virtual bool accept() = 0; |
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61 | /// \brief Destructor. |
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62 | virtual ~ControllerBase() {} |
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63 | }; |
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64 | |
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65 | /// \brief Skeleton of an entity class. |
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66 | class EntityBase { |
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67 | public: |
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68 | /// \brief Makes a minor change to the entity. |
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69 | /// \return the new cost |
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70 | virtual double mutate() = 0; |
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71 | /// \brief Restores the entity to its previous state i.e. reverts the |
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72 | /// effects of the last mutate(). |
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73 | virtual void revert() = 0; |
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74 | /// \brief Makes a copy of the entity. |
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75 | virtual EntityBase* clone() = 0; |
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76 | /// \brief Makes a major change to the entity. |
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77 | virtual void randomize() = 0; |
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78 | /// \brief Destructor. |
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79 | virtual ~EntityBase() {} |
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80 | }; |
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81 | |
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82 | /// \brief Simulated annealing abstract base class. |
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83 | /// |
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84 | /// Can be used to derive a custom simulated annealing class if \ref SimAnn |
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85 | /// doesn't fit your needs. |
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86 | class SimAnnBase { |
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87 | private: |
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88 | /// \brief Pointer to the controller. |
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89 | ControllerBase *controller; |
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90 | /// \brief Cost of the current solution. |
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91 | double curr_cost; |
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92 | /// \brief Cost of the best solution. |
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93 | double best_cost; |
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94 | /// \brief Cost of the previous solution. |
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95 | double prev_cost; |
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96 | /// \brief Cost of the solution preceding the previous one. |
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97 | double prev_prev_cost; |
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98 | /// \brief Number of iterations. |
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99 | long iter; |
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100 | /// \brief Number of iterations which did not improve the solution since |
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101 | /// the last improvement. |
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102 | long last_impr; |
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103 | protected: |
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104 | /// \brief Step to a neighbouring state. |
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105 | virtual double mutate() = 0; |
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106 | /// \brief Reverts the last mutate(). |
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107 | virtual void revert() = 0; |
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108 | /// \brief Saves the current solution as the best one. |
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109 | virtual void saveAsBest() = 0; |
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110 | /// \brief Does initializations before each run. |
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111 | virtual void init() { |
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112 | controller->init(); |
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113 | curr_cost = prev_cost = prev_prev_cost = best_cost = |
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114 | std::numeric_limits<double>::infinity(); |
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115 | iter = last_impr = 0; |
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116 | } |
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117 | public: |
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118 | /// \brief Sets the controller class to use. |
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119 | void setController(ControllerBase &_controller) { |
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120 | controller = &_controller; |
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121 | controller->simann = this; |
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122 | } |
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123 | /// \brief Returns the cost of the current solution. |
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124 | double getCurrCost() const { return curr_cost; } |
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125 | /// \brief Returns the cost of the previous solution. |
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126 | double getPrevCost() const { return prev_cost; } |
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127 | /// \brief Returns the cost of the best solution. |
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128 | double getBestCost() const { return best_cost; } |
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129 | /// \brief Returns the number of iterations done. |
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130 | long getIter() const { return iter; } |
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131 | /// \brief Returns the ordinal number of the last iteration when the |
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132 | /// solution was improved. |
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133 | long getLastImpr() const { return last_impr; } |
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134 | /// \brief Performs one iteration. |
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135 | bool step() { |
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136 | iter++; |
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137 | prev_prev_cost = prev_cost; |
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138 | prev_cost = curr_cost; |
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139 | curr_cost = mutate(); |
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140 | if (controller->accept()) { |
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141 | controller->acceptEvent(); |
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142 | last_impr = iter; |
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143 | if (curr_cost < best_cost) { |
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144 | best_cost = curr_cost; |
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145 | saveAsBest(); |
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146 | controller->improveEvent(); |
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147 | } |
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148 | } |
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149 | else { |
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150 | revert(); |
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151 | curr_cost = prev_cost; |
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152 | prev_cost = prev_prev_cost; |
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153 | controller->rejectEvent(); |
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154 | } |
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155 | return controller->next(); |
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156 | } |
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157 | /// \brief Performs a given number of iterations. |
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158 | /// \param n the number of iterations |
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159 | bool step(int n) { |
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160 | for(; n > 0 && step(); --n) ; |
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161 | return !n; |
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162 | } |
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163 | /// \brief Starts the annealing process. |
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164 | void run() { |
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165 | init(); |
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166 | do { } while (step()); |
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167 | } |
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168 | /// \brief Destructor. |
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169 | virtual ~SimAnnBase() {} |
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170 | }; |
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171 | |
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172 | /// \ingroup metah |
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173 | /// |
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174 | /// \brief Simulated annealing class. |
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175 | class SimAnn : public SimAnnBase { |
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176 | private: |
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177 | /// \brief Pointer to the current entity. |
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178 | EntityBase *curr_ent; |
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179 | /// \brief Pointer to the best entity. |
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180 | EntityBase *best_ent; |
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181 | /// \brief Does initializations before each run. |
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182 | void init() { |
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183 | SimAnnBase::init(); |
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184 | if (best_ent) delete best_ent; |
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185 | best_ent = NULL; |
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186 | curr_ent->randomize(); |
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187 | } |
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188 | public: |
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189 | /// \brief Constructor. |
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190 | SimAnn() : curr_ent(NULL), best_ent(NULL) {} |
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191 | /// \brief Destructor. |
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192 | virtual ~SimAnn() { |
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193 | if (best_ent) delete best_ent; |
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194 | } |
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195 | /// \brief Step to a neighbouring state. |
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196 | double mutate() { |
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197 | return curr_ent->mutate(); |
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198 | } |
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199 | /// \brief Reverts the last mutate(). |
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200 | void revert() { |
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201 | curr_ent->revert(); |
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202 | } |
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203 | /// \brief Saves the current solution as the best one. |
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204 | void saveAsBest() { |
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205 | if (best_ent) delete best_ent; |
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206 | best_ent = curr_ent->clone(); |
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207 | } |
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208 | /// \brief Sets the current entity. |
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209 | void setEntity(EntityBase &_ent) { |
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210 | curr_ent = &_ent; |
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211 | } |
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212 | /// \brief Returns a copy of the best found entity. |
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213 | EntityBase* getBestEntity() { return best_ent->clone(); } |
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214 | }; |
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215 | |
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216 | /// \brief A simple controller for the simulated annealing class. |
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217 | /// |
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218 | /// This controller starts from a given initial temperature and evenly |
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219 | /// decreases it. |
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220 | class SimpleController : public ControllerBase { |
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221 | private: |
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222 | /// \brief Maximum number of iterations. |
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223 | long max_iter; |
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224 | /// \brief Maximum number of iterations which do not improve the |
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225 | /// solution. |
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226 | long max_no_impr; |
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227 | /// \brief Temperature. |
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228 | double temp; |
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229 | /// \brief Annealing factor. |
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230 | double ann_fact; |
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231 | /// \brief Constructor. |
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232 | /// \param _max_iter maximum number of iterations |
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233 | /// \param _max_no_impr maximum number of consecutive iterations which do |
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234 | /// not yield a better solution |
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235 | /// \param _temp initial temperature |
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236 | /// \param _ann_fact annealing factor |
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237 | public: |
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238 | SimpleController(long _max_iter = 500000, long _max_no_impr = 20000, |
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239 | double _temp = 1000.0, double _ann_fact = 0.9999) : max_iter(_max_iter), |
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240 | max_no_impr(_max_no_impr), temp(_temp), ann_fact(_ann_fact) |
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241 | { |
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242 | } |
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243 | /// \brief This is called when a neighbouring state gets accepted. |
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244 | void acceptEvent() {} |
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245 | /// \brief This is called when the accepted neighbouring state's cost is |
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246 | /// less than the best found one's. |
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247 | void improveEvent() {} |
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248 | /// \brief This is called when a neighbouring state gets rejected. |
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249 | void rejectEvent() {} |
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250 | /// \brief Decides whether to continue the annealing process or not. Also |
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251 | /// decreases the temperature. |
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252 | bool next() { |
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253 | temp *= ann_fact; |
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254 | bool quit = (simann->getIter() > max_iter) || |
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255 | (simann->getIter() - simann->getLastImpr() > max_no_impr); |
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256 | return !quit; |
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257 | } |
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258 | /// \brief Decides whether to accept the current solution or not. |
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259 | bool accept() { |
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260 | double cost_diff = simann->getCurrCost() - simann->getPrevCost(); |
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261 | return (rnd() <= exp(-(cost_diff / temp))); |
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262 | } |
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263 | /// \brief Destructor. |
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264 | virtual ~SimpleController() {} |
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265 | }; |
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266 | |
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267 | /// \brief A controller with preset running time for the simulated annealing |
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268 | /// class. |
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269 | /// |
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270 | /// With this controller you can set the running time of the annealing |
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271 | /// process in advance. It works the following way: the controller measures |
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272 | /// a kind of divergence. The divergence is the difference of the average |
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273 | /// cost of the recently found solutions the cost of the best found one. In |
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274 | /// case this divergence is greater than a given threshold, then we decrease |
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275 | /// the annealing factor, that is we cool the system faster. In case the |
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276 | /// divergence is lower than the threshold, then we increase the temperature. |
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277 | /// The threshold is a function of the elapsed time which reaches zero at the |
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278 | /// desired end time. |
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279 | class AdvancedController : public ControllerBase { |
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280 | private: |
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281 | /// \brief Timer class to measure the elapsed time. |
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282 | Timer timer; |
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283 | /// \brief Calculates the threshold value. |
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284 | /// \param time the elapsed time in seconds |
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285 | virtual double threshold(double time) { |
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286 | return (-1.0) * start_threshold / end_time * time + start_threshold; |
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287 | } |
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288 | /// \brief Parameter used to calculate the running average. |
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289 | double alpha; |
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290 | /// \brief Parameter used to decrease the annealing factor. |
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291 | double beta; |
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292 | /// \brief Parameter used to increase the temperature. |
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293 | double gamma; |
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294 | /// \brief The time at the end of the algorithm. |
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295 | double end_time; |
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296 | /// \brief The time at the start of the algorithm. |
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297 | double start_time; |
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298 | /// \brief Starting threshold. |
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299 | double start_threshold; |
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300 | /// \brief Average cost of recent solutions. |
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301 | double avg_cost; |
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302 | /// \brief Temperature. |
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303 | double temp; |
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304 | /// \brief Annealing factor. |
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305 | double ann_fact; |
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306 | /// \brief Initial annealing factor. |
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307 | double init_ann_fact; |
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308 | /// \brief True when the annealing process has been started. |
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309 | bool start; |
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310 | public: |
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311 | /// \brief Constructor. |
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312 | /// \param _end_time running time in seconds |
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313 | /// \param _alpha parameter used to calculate the running average |
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314 | /// \param _beta parameter used to decrease the annealing factor |
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315 | /// \param _gamma parameter used to increase the temperature |
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316 | /// \param _ann_fact initial annealing factor |
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317 | AdvancedController(double _end_time, double _alpha = 0.2, |
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318 | double _beta = 0.9, double _gamma = 1.6, double _ann_fact = 0.9999) : |
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319 | alpha(_alpha), beta(_beta), gamma(_gamma), end_time(_end_time), |
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320 | ann_fact(_ann_fact), init_ann_fact(_ann_fact), start(false) |
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321 | { |
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322 | } |
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323 | /// \brief Does initializations before each run. |
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324 | void init() { |
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325 | avg_cost = simann->getCurrCost(); |
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326 | } |
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327 | /// \brief This is called when a neighbouring state gets accepted. |
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328 | void acceptEvent() { |
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329 | avg_cost = alpha * simann->getCurrCost() + (1.0 - alpha) * avg_cost; |
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330 | if (!start) { |
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331 | static int cnt = 0; |
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332 | cnt++; |
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333 | if (cnt >= 100) { |
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334 | // calculate starting threshold and starting temperature |
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335 | start_threshold = 5.0 * fabs(simann->getBestCost() - avg_cost); |
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336 | temp = 10000.0; |
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337 | start = true; |
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338 | timer.restart(); |
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339 | } |
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340 | } |
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341 | } |
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342 | /// \brief Decides whether to continue the annealing process or not. |
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343 | bool next() { |
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344 | if (!start) { |
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345 | return true; |
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346 | } |
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347 | else { |
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348 | double elapsed_time = timer.realTime(); |
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349 | if (fabs(avg_cost - simann->getBestCost()) > threshold(elapsed_time)) { |
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350 | // decrease the annealing factor |
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351 | ann_fact *= beta; |
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352 | } |
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353 | else { |
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354 | // increase the temperature |
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355 | temp *= gamma; |
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356 | // reset the annealing factor |
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357 | ann_fact = init_ann_fact; |
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358 | } |
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359 | temp *= ann_fact; |
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360 | return elapsed_time < end_time; |
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361 | } |
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362 | } |
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363 | /// \brief Decides whether to accept the current solution or not. |
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364 | bool accept() { |
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365 | if (!start) { |
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366 | return true; |
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367 | } |
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368 | else { |
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369 | double cost_diff = simann->getCurrCost() - simann->getPrevCost(); |
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370 | return (rnd() <= exp(-(cost_diff / temp))); |
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371 | } |
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372 | } |
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373 | /// \brief Destructor. |
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374 | virtual ~AdvancedController() {} |
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375 | }; |
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376 | |
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377 | } |
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378 | |
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379 | #endif |
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