// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*- //----------------------------------------------------------------------------- // moeoNSGA.h // (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007 /* This library... Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr */ //----------------------------------------------------------------------------- #ifndef MOEONSGA_H_ #define MOEONSGA_H_ #include #include #include #include #include #include #include #include #include #include #include #include #include /** * NSGA (Non-dominated Sorting Genetic Algorithm) as described in: * N. Srinivas, K. Deb, "Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms". * Evolutionary Computation, Vol. 2(3), No 2, pp. 221-248 (1994). * This class builds the NSGA algorithm only by using the fine-grained components of the ParadisEO-MOEO framework. */ template < class MOEOT > class moeoNSGA: public moeoEA < MOEOT > { public: /** * Simple ctor with a eoGenOp. * @param _maxGen number of generations before stopping * @param _eval evaluation function * @param _op variation operator * @param _nicheSize niche size */ moeoNSGA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, double _nicheSize = 0.5) : defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), popEval(_eval), select(2), diversityAssignment(_nicheSize), replace(fitnessAssignment, diversityAssignment), genBreed(select, _op), breed(genBreed) {} /** * Simple ctor with a eoTransform. * @param _maxGen number of generations before stopping * @param _eval evaluation function * @param _op variation operator * @param _nicheSize niche size */ moeoNSGA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _op, double _nicheSize = 0.5) : defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), popEval(_eval), select(2), diversityAssignment(_nicheSize), replace(fitnessAssignment, diversityAssignment), genBreed(select, _op), breed(genBreed) {} /** * Ctor with a crossover, a mutation and their corresponding rates. * @param _maxGen number of generations before stopping * @param _eval evaluation function * @param _crossover crossover * @param _pCross crossover probability * @param _mutation mutation * @param _pMut mutation probability * @param _nicheSize niche size */ moeoNSGA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, double _nicheSize = 0.5) : defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), popEval(_eval), select (2), diversityAssignment(_nicheSize), replace (fitnessAssignment, diversityAssignment), defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut), genBreed (select, defaultSGAGenOp), breed (genBreed) {} /** * Ctor with a continuator (instead of _maxGen) and a eoGenOp. * @param _continuator stopping criteria * @param _eval evaluation function * @param _op variation operator * @param _nicheSize niche size */ moeoNSGA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, double _nicheSize = 0.5) : continuator(_continuator), popEval(_eval), select(2), diversityAssignment(_nicheSize), replace(fitnessAssignment, diversityAssignment), genBreed(select, _op), breed(genBreed) {} /** * Ctor with a continuator (instead of _maxGen) and a eoTransform. * @param _continuator stopping criteria * @param _eval evaluation function * @param _op variation operator * @param _nicheSize niche size */ moeoNSGA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _op, double _nicheSize = 0.5) : continuator(_continuator), popEval(_eval), select(2), diversityAssignment(_nicheSize), replace(fitnessAssignment, diversityAssignment), genBreed(select, _op), breed(genBreed) {} /** * Apply a few generation of evolution to the population _pop until the stopping criteria is verified. * @param _pop the population */ virtual void operator () (eoPop < MOEOT > &_pop) { eoPop < MOEOT > offspring, empty_pop; popEval (empty_pop, _pop); // a first eval of _pop // evaluate fitness and diversity fitnessAssignment(_pop); diversityAssignment(_pop); do { // generate offspring, worths are recalculated if necessary breed (_pop, offspring); // eval of offspring popEval (_pop, offspring); // after replace, the new pop is in _pop. Worths are recalculated if necessary replace (_pop, offspring); } while (continuator (_pop)); } protected: /** a continuator based on the number of generations (used as default) */ eoGenContinue < MOEOT > defaultGenContinuator; /** stopping criteria */ eoContinue < MOEOT > & continuator; /** evaluation function used to evaluate the whole population */ eoPopLoopEval < MOEOT > popEval; /** binary tournament selection */ moeoDetTournamentSelect < MOEOT > select; /** fitness assignment used in NSGA-II */ moeoFastNonDominatedSortingFitnessAssignment < MOEOT > fitnessAssignment; /** diversity assignment used in NSGA-II */ moeoFrontByFrontSharingDiversityAssignment < MOEOT > diversityAssignment; /** elitist replacement */ moeoElitistReplacement < MOEOT > replace; /** an object for genetic operators (used as default) */ eoSGAGenOp < MOEOT > defaultSGAGenOp; /** general breeder */ eoGeneralBreeder < MOEOT > genBreed; /** breeder */ eoBreed < MOEOT > & breed; }; #endif /*MOEONSGAII_H_*/