[1633] | 1 | #ifndef LEMON_SIMANN_H |
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| 2 | #define LEMON_SIMANN_H |
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| 3 | |
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| 4 | /// \ingroup experimental |
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| 5 | /// \file |
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| 6 | /// \brief Simulated annealing framework. |
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| 7 | /// \author Akos Ladanyi |
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| 8 | |
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| 9 | #include <cstdlib> |
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| 10 | #include <cmath> |
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| 11 | #include <lemon/time_measure.h> |
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| 12 | |
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| 13 | namespace lemon { |
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| 14 | |
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| 15 | /// \addtogroup experimental |
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| 16 | /// @{ |
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| 17 | |
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| 18 | /*! \brief A base class for controllers. */ |
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| 19 | class ControllerBase { |
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| 20 | friend class SimAnnBase; |
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| 21 | public: |
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| 22 | /*! \brief Pointer to the simulated annealing base class. */ |
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| 23 | SimAnnBase *simann; |
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| 24 | /*! \brief Initializes the controller. */ |
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| 25 | virtual void init() {} |
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| 26 | /*! \brief This is called when a neighbouring state gets accepted. */ |
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| 27 | virtual void acceptEvent() {} |
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| 28 | /*! \brief This is called when the accepted neighbouring state's cost is |
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| 29 | * less than the best found one's. |
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| 30 | */ |
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| 31 | virtual void improveEvent() {} |
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| 32 | /*! \brief This is called when a neighbouring state gets rejected. */ |
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| 33 | virtual void rejectEvent() {} |
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| 34 | /*! \brief Decides whether to continue the annealing process or not. */ |
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| 35 | virtual bool next() = 0; |
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| 36 | /*! \brief Decides whether to accept the current solution or not. */ |
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| 37 | virtual bool accept() = 0; |
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| 38 | }; |
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| 39 | |
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| 40 | /*! \brief Skeleton of an entity class. */ |
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| 41 | class EntityBase { |
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| 42 | public: |
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| 43 | /*! \brief Makes a minor change to the entity. |
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| 44 | * \return the new cost |
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| 45 | */ |
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| 46 | virtual double mutate() = 0; |
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| 47 | /*! \brief Restores the entity to its previous state i.e. reverts the |
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| 48 | * effects of the last mutate(). |
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| 49 | */ |
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| 50 | virtual void revert() = 0; |
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| 51 | /*! \brief Makes a copy of the entity. */ |
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| 52 | virtual EntityBase* clone() = 0; |
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| 53 | /*! \brief Makes a major change to the entity. */ |
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| 54 | virtual void randomize() = 0; |
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| 55 | }; |
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| 56 | |
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| 57 | /*! \brief Simulated annealing base class. */ |
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| 58 | class SimAnnBase { |
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| 59 | private: |
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| 60 | /*! Pointer to the controller. */ |
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| 61 | ControllerBase *controller; |
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| 62 | /*! \brief Cost of the current solution. */ |
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| 63 | double curr_cost; |
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| 64 | /*! \brief Cost of the best solution. */ |
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| 65 | double best_cost; |
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| 66 | /*! \brief Cost of the previous solution. */ |
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| 67 | double prev_cost; |
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| 68 | /*! \brief Cost of the solution preceding the previous one. */ |
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| 69 | double prev_prev_cost; |
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| 70 | /*! \brief Number of iterations. */ |
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| 71 | long iter; |
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| 72 | /*! \brief Number of iterations which did not improve the solution since |
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| 73 | * the last improvement. */ |
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| 74 | long last_impr; |
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| 75 | protected: |
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| 76 | /*! \brief Step to a neighbouring state. */ |
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| 77 | virtual double mutate() = 0; |
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| 78 | /*! \brief Reverts the last mutate(). */ |
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| 79 | virtual void revert() = 0; |
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| 80 | /*! \brief Saves the current solution as the best one. */ |
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| 81 | virtual void saveAsBest() = 0; |
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| 82 | /*! \brief Does initializations before each run. */ |
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| 83 | virtual void init() { |
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| 84 | controller->init(); |
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| 85 | curr_cost = prev_cost = prev_prev_cost = best_cost = |
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| 86 | std::numeric_limits<double>::infinity(); |
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| 87 | iter = last_impr = 0; |
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| 88 | } |
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| 89 | public: |
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| 90 | /*! \brief Sets the controller class to use. */ |
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| 91 | void setController(ControllerBase &_controller) { |
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| 92 | controller = &_controller; |
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| 93 | controller->simann = this; |
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| 94 | } |
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| 95 | /*! \brief Returns the cost of the current solution. */ |
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| 96 | double getCurrCost() const { return curr_cost; } |
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| 97 | /*! \brief Returns the cost of the previous solution. */ |
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| 98 | double getPrevCost() const { return prev_cost; } |
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| 99 | /*! \brief Returns the cost of the best solution. */ |
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| 100 | double getBestCost() const { return best_cost; } |
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| 101 | /*! \brief Returns the number of iterations. */ |
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| 102 | long getIter() const { return iter; } |
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| 103 | /*! \brief Returns the number of the last iteration when the solution was |
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| 104 | * improved. |
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| 105 | */ |
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| 106 | long getLastImpr() const { return last_impr; } |
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| 107 | /*! \brief Performs one iteration. */ |
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| 108 | bool step() { |
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| 109 | iter++; |
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| 110 | prev_prev_cost = prev_cost; |
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| 111 | prev_cost = curr_cost; |
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| 112 | curr_cost = mutate(); |
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| 113 | if (controller->accept()) { |
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| 114 | controller->acceptEvent(); |
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| 115 | last_impr = iter; |
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| 116 | if (curr_cost < best_cost) { |
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| 117 | best_cost = curr_cost; |
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| 118 | saveAsBest(); |
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| 119 | controller->improveEvent(); |
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| 120 | } |
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| 121 | } |
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| 122 | else { |
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| 123 | revert(); |
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| 124 | curr_cost = prev_cost; |
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| 125 | prev_cost = prev_prev_cost; |
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| 126 | controller->rejectEvent(); |
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| 127 | } |
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| 128 | return controller->next(); |
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| 129 | } |
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| 130 | /*! \brief Performs a given number of iterations. |
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| 131 | * \param n the number of iterations |
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| 132 | */ |
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| 133 | bool step(int n) { |
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| 134 | for(; n > 0 && step(); --n) ; |
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| 135 | return !n; |
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| 136 | } |
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| 137 | /*! \brief Starts the annealing process. */ |
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| 138 | void run() { |
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| 139 | init(); |
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| 140 | do { } while (step()); |
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| 141 | } |
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| 142 | }; |
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| 143 | |
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| 144 | /*! \brief Simulated annealing class. */ |
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| 145 | class SimAnn : public SimAnnBase { |
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| 146 | private: |
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| 147 | /*! \brief Pointer to the current entity. */ |
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| 148 | EntityBase *curr_ent; |
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| 149 | /*! \brief Pointer to the best entity. */ |
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| 150 | EntityBase *best_ent; |
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| 151 | /*! \brief Does initializations before each run. */ |
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| 152 | void init() { |
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| 153 | SimAnnBase::init(); |
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| 154 | if (best_ent) delete best_ent; |
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| 155 | best_ent = NULL; |
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| 156 | curr_ent->randomize(); |
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| 157 | } |
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| 158 | public: |
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| 159 | /*! \brief Constructor. */ |
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| 160 | SimAnn() : curr_ent(NULL), best_ent(NULL) {} |
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| 161 | /*! \brief Destructor. */ |
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| 162 | virtual ~SimAnn() { |
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| 163 | if (best_ent) delete best_ent; |
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| 164 | } |
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| 165 | /*! \brief Step to a neighbouring state. */ |
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| 166 | double mutate() { |
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| 167 | return curr_ent->mutate(); |
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| 168 | } |
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| 169 | /*! \brief Reverts the last mutate(). */ |
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| 170 | void revert() { |
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| 171 | curr_ent->revert(); |
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| 172 | } |
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| 173 | /*! \brief Saves the current solution as the best one. */ |
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| 174 | void saveAsBest() { |
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| 175 | if (best_ent) delete best_ent; |
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| 176 | best_ent = curr_ent->clone(); |
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| 177 | } |
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| 178 | /*! \brief Sets the current entity. */ |
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| 179 | void setEntity(EntityBase &_ent) { |
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| 180 | curr_ent = &_ent; |
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| 181 | } |
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| 182 | /*! \brief Returns a copy of the best found entity. */ |
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| 183 | EntityBase* getBestEntity() { return best_ent->clone(); } |
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| 184 | }; |
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| 185 | |
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| 186 | /*! \brief A simple controller for the simulated annealing class. */ |
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| 187 | class SimpleController : public ControllerBase { |
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| 188 | public: |
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| 189 | /*! \brief Maximum number of iterations. */ |
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| 190 | long max_iter; |
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| 191 | /*! \brief Maximum number of iterations which do not improve the |
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| 192 | * solution. */ |
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| 193 | long max_no_impr; |
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| 194 | /*! \brief Temperature. */ |
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| 195 | double temp; |
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| 196 | /*! \brief Annealing factor. */ |
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| 197 | double ann_fact; |
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| 198 | /*! \brief Constructor. |
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| 199 | * \param _max_iter maximum number of iterations |
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| 200 | * \param _max_no_impr maximum number of consecutive iterations which do |
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| 201 | * not yield a better solution |
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| 202 | * \param _temp initial temperature |
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| 203 | * \param _ann_fact annealing factor |
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| 204 | */ |
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| 205 | SimpleController(long _max_iter = 500000, long _max_no_impr = 20000, |
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| 206 | double _temp = 1000.0, double _ann_fact = 0.9999) : max_iter(_max_iter), |
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| 207 | max_no_impr(_max_no_impr), temp(_temp), ann_fact(_ann_fact) |
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| 208 | { |
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| 209 | srand48(time(0)); |
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| 210 | } |
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| 211 | /*! \brief This is called when a neighbouring state gets accepted. */ |
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| 212 | void acceptEvent() {} |
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| 213 | /*! \brief This is called when the accepted neighbouring state's cost is |
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| 214 | * less than the best found one's. |
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| 215 | */ |
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| 216 | void improveEvent() {} |
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| 217 | /*! \brief This is called when a neighbouring state gets rejected. */ |
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| 218 | void rejectEvent() {} |
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| 219 | /*! \brief Decides whether to continue the annealing process or not. Also |
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| 220 | * decreases the temperature. */ |
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| 221 | bool next() { |
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| 222 | temp *= ann_fact; |
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| 223 | bool quit = (simann->getIter() > max_iter) || |
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| 224 | (simann->getIter() - simann->getLastImpr() > max_no_impr); |
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| 225 | return !quit; |
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| 226 | } |
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| 227 | /*! \brief Decides whether to accept the current solution or not. */ |
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| 228 | bool accept() { |
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| 229 | double cost_diff = simann->getPrevCost() - simann->getCurrCost(); |
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| 230 | return (drand48() <= exp(cost_diff / temp)); |
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| 231 | } |
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| 232 | }; |
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| 233 | |
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| 234 | /*! \brief A controller with preset running time for the simulated annealing |
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| 235 | * class. |
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| 236 | * |
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| 237 | * With this controller you can set the running time of the annealing |
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| 238 | * process in advance. It works the following way: the controller measures |
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| 239 | * a kind of divergence. The divergence is the difference of the average |
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| 240 | * cost of the recently found solutions the cost of the best found one. In |
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| 241 | * case this divergence is greater than a given threshold, then we decrease |
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| 242 | * the annealing factor, that is we cool the system faster. In case the |
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| 243 | * divergence is lower than the threshold, then we increase the temperature. |
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| 244 | * The threshold is a function of the elapsed time which reaches zero at the |
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| 245 | * desired end time. |
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| 246 | */ |
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| 247 | class AdvancedController : public ControllerBase { |
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| 248 | private: |
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| 249 | Timer timer; |
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| 250 | /*! \param time the elapsed time in seconds */ |
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| 251 | virtual double threshold(double time) { |
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| 252 | return (-1.0) * start_threshold / end_time * time + start_threshold; |
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| 253 | } |
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| 254 | public: |
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| 255 | double alpha; |
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| 256 | double beta; |
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| 257 | double gamma; |
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| 258 | /*! \brief The time at the end of the algorithm. */ |
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| 259 | double end_time; |
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| 260 | /*! \brief The time at the start of the algorithm. */ |
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| 261 | double start_time; |
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| 262 | /*! \brief Starting threshold. */ |
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| 263 | double start_threshold; |
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| 264 | /*! \brief Average cost of recent solutions. */ |
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| 265 | double avg_cost; |
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| 266 | /*! \brief Temperature. */ |
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| 267 | double temp; |
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| 268 | /*! \brief Annealing factor. */ |
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| 269 | double ann_fact; |
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| 270 | /*! \brief Initial annealing factor. */ |
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| 271 | double init_ann_fact; |
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| 272 | bool warmup; |
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| 273 | /*! \brief Constructor. |
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| 274 | * \param _end_time running time in seconds |
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| 275 | * \param _alpha parameter used to calculate the running average |
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| 276 | * \param _beta parameter used to decrease the annealing factor |
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| 277 | * \param _gamma parameter used to increase the temperature |
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| 278 | * \param _ann_fact initial annealing factor |
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| 279 | */ |
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| 280 | AdvancedController(double _end_time, double _alpha = 0.2, |
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| 281 | double _beta = 0.9, double _gamma = 1.6, double _ann_fact = 0.9999) : |
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| 282 | alpha(_alpha), beta(_beta), gamma(_gamma), end_time(_end_time), |
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| 283 | ann_fact(_ann_fact), init_ann_fact(_ann_fact), warmup(true) |
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| 284 | { |
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| 285 | srand48(time(0)); |
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| 286 | } |
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| 287 | void init() { |
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| 288 | avg_cost = simann->getCurrCost(); |
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| 289 | } |
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| 290 | /*! \brief This is called when a neighbouring state gets accepted. */ |
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| 291 | void acceptEvent() { |
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| 292 | avg_cost = alpha * simann->getCurrCost() + (1.0 - alpha) * avg_cost; |
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| 293 | if (warmup) { |
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| 294 | static int cnt = 0; |
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| 295 | cnt++; |
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| 296 | if (cnt >= 100) { |
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| 297 | // calculate starting threshold and starting temperature |
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| 298 | start_threshold = 5.0 * fabs(simann->getBestCost() - avg_cost); |
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| 299 | temp = 10000.0; |
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| 300 | warmup = false; |
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| 301 | timer.reset(); |
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| 302 | } |
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| 303 | } |
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| 304 | } |
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| 305 | /*! \brief Decides whether to continue the annealing process or not. */ |
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| 306 | bool next() { |
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| 307 | if (warmup) { |
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| 308 | return true; |
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| 309 | } |
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| 310 | else { |
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| 311 | double elapsed_time = timer.getRealTime(); |
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| 312 | if (fabs(avg_cost - simann->getBestCost()) > threshold(elapsed_time)) { |
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| 313 | // decrease the annealing factor |
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| 314 | ann_fact *= beta; |
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| 315 | } |
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| 316 | else { |
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| 317 | // increase the temperature |
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| 318 | temp *= gamma; |
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| 319 | // reset the annealing factor |
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| 320 | ann_fact = init_ann_fact; |
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| 321 | } |
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| 322 | temp *= ann_fact; |
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| 323 | return elapsed_time < end_time; |
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| 324 | } |
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| 325 | } |
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| 326 | /*! \brief Decides whether to accept the current solution or not. */ |
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| 327 | bool accept() { |
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| 328 | if (warmup) { |
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| 329 | // we accept eveything during the "warm up" phase |
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| 330 | return true; |
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| 331 | } |
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| 332 | else { |
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| 333 | double cost_diff = simann->getPrevCost() - simann->getCurrCost(); |
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| 334 | if (cost_diff < 0.0) { |
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| 335 | return (drand48() <= exp(cost_diff / temp)); |
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| 336 | } |
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| 337 | else { |
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| 338 | return true; |
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| 339 | } |
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| 340 | } |
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| 341 | } |
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| 342 | }; |
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| 343 | |
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| 344 | /// @} |
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| 345 | |
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| 346 | } |
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| 347 | |
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| 348 | #endif |
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