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bug corrected on some Ctors

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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@1215 331e1502-861f-0410-8da2-ba01fb791d7f
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liefooga 2008-06-26 14:00:52 +00:00
commit 9f24113e1c
1 changed files with 96 additions and 65 deletions
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trunk/paradiseo-moeo/src/algo/moeoIBEA.h
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@ -38,8 +38,8 @@
#ifndef MOEOIBEA_H_ #ifndef MOEOIBEA_H_
#define MOEOIBEA_H_ #define MOEOIBEA_H_
#include <eoBreed.h> #include <eoBreed.h>
#include <eoCloneOps.h>
#include <eoContinue.h> #include <eoContinue.h>
#include <eoEvalFunc.h> #include <eoEvalFunc.h>
#include <eoGenContinue.h> #include <eoGenContinue.h>
@ -55,140 +55,171 @@
#include <selection/moeoDetTournamentSelect.h> #include <selection/moeoDetTournamentSelect.h>
/** /**
* IBEA (Indicator-Based Evolutionary Algorithm) as described in: * IBEA (Indicator-Based Evolutionary Algorithm).
* E. Zitzler, S. Künzli, "Indicator-Based Selection in Multiobjective Search", Proc. 8th International Conference on Parallel Problem Solving from Nature (PPSN VIII), pp. 832-842, Birmingham, UK (2004). * E. Zitzler, S. Künzli, "Indicator-Based Selection in Multiobjective Search", Proc. 8th International Conference on Parallel Problem Solving from Nature (PPSN VIII), pp. 832-842, Birmingham, UK (2004).
* This class builds the IBEA algorithm only by using the fine-grained components of the ParadisEO-MOEO framework. * This class builds the IBEA algorithm only by using the fine-grained components of the ParadisEO-MOEO framework.
*/ */
template < class MOEOT > template < class MOEOT >
class moeoIBEA : public moeoEA < MOEOT > class moeoIBEA : public moeoEA < MOEOT >
{ {
public: public:
/** The type of objective vector */ /** The type of objective vector */
typedef typename MOEOT::ObjectiveVector ObjectiveVector; typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/** /**
* Simple ctor with a eoGenOp. * Ctor with a crossover, a mutation and their corresponding rates.
* @param _maxGen number of generations before stopping * @param _maxGen maximum number of generations before stopping
* @param _eval evaluation function * @param _eval evaluation function
* @param _op variation operator * @param _crossover crossover
* @param _metric metric * @param _pCross crossover probability
* @param _kappa scaling factor kappa * @param _mutation mutation
*/ * @param _pMut mutation probability
moeoIBEA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) : * @param _metric metric
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), popEval(_eval), select(2), * @param _kappa scaling factor kappa
fitnessAssignment(_metric, _kappa), replace(fitnessAssignment, dummyDiversityAssignment), 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 _metric metric
* @param _kappa scaling factor kappa
*/
moeoIBEA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _op, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), popEval(_eval), select(2),
fitnessAssignment(_metric, _kappa), replace(fitnessAssignment, dummyDiversityAssignment), 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 _metric metric
* @param _kappa scaling factor kappa
*/
moeoIBEA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) : moeoIBEA (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), popEval(_eval), select (2), defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select (2), selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut), genBreed (select, defaultSGAGenOp), breed (genBreed), fitnessAssignment(_metric, _kappa), replace (fitnessAssignment, diversityAssignment)
fitnessAssignment(_metric, _kappa), replace (fitnessAssignment, dummyDiversityAssignment), defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut),
genBreed (select, defaultSGAGenOp), breed (genBreed)
{} {}
/** /**
* Ctor with a continuator (instead of _maxGen) and a eoGenOp. * Ctor with a eoContinue and a eoGenOp.
* @param _continuator stopping criteria * @param _continuator stopping criteria
* @param _eval evaluation function * @param _eval evaluation function
* @param _op variation operator * @param _op variation operators
* @param _metric metric * @param _metric metric
* @param _kappa scaling factor kappa * @param _kappa scaling factor kappa
*/ */
moeoIBEA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) : moeoIBEA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
continuator(_continuator), popEval(_eval), select(2), defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select(2),
fitnessAssignment(_metric, _kappa), replace(fitnessAssignment, dummyDiversityAssignment), genBreed(select, _op), breed(genBreed) selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), fitnessAssignment(_metric, _kappa), replace (fitnessAssignment, diversityAssignment)
{} {}
/** /**
* Ctor with a continuator (instead of _maxGen) and a eoTransform. * Ctor with a eoContinue, a eoPopEval and a eoGenOp.
* @param _continuator stopping criteria * @param _continuator stopping criteria
* @param _eval evaluation function * @param _popEval population evaluation function
* @param _op variation operator * @param _op variation operators
* @param _metric metric * @param _metric metric
* @param _kappa scaling factor kappa * @param _kappa scaling factor kappa
*/ */
moeoIBEA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _op, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) : moeoIBEA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoGenOp < MOEOT > & _op, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
continuator(_continuator), popEval(_eval), select(2), defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval), select(2),
fitnessAssignment(_metric, _kappa), replace(fitnessAssignment, dummyDiversityAssignment), genBreed(select, _op), breed(genBreed) selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), fitnessAssignment(_metric, _kappa), replace (fitnessAssignment, diversityAssignment)
{} {}
/** /**
* Apply a few generation of evolution to the population _pop until the stopping criteria is verified. * Ctor with a eoContinue and a eoTransform.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _transform variation operator
* @param _metric metric
* @param _kappa scaling factor kappa
*/
moeoIBEA (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _transform, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval),
select(2), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), fitnessAssignment(_metric, _kappa), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue, a eoPopEval and a eoTransform.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _transform variation operator
* @param _metric metric
* @param _kappa scaling factor kappa
*/
moeoIBEA (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoTransform < MOEOT > & _transform, moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & _metric, const double _kappa=0.05) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval),
select(2), selectMany(select, 1.0), selectTransform(selectMany, _transform), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0), genBreed(select, defaultSGAGenOp), breed(selectTransform), fitnessAssignment(_metric, _kappa), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Apply the algorithm to the population _pop until the stopping criteria is satified.
* @param _pop the population * @param _pop the population
*/ */
virtual void operator () (eoPop < MOEOT > &_pop) virtual void operator () (eoPop < MOEOT > &_pop)
{ {
eoPop < MOEOT > offspring, empty_pop; eoPop < MOEOT > offspring, empty_pop;
popEval (empty_pop, _pop); // a first eval of _pop popEval (empty_pop, _pop); // a first eval of _pop
// evaluate fitness and diversity // evaluate fitness and diversity
fitnessAssignment(_pop); fitnessAssignment(_pop);
dummyDiversityAssignment(_pop); diversityAssignment(_pop);
do do
{ {
// generate offspring, worths are recalculated if necessary // generate offspring, worths are recalculated if necessary
breed (_pop, offspring); breed (_pop, offspring);
// eval of offspring // eval of offspring
popEval (_pop, offspring); popEval (_pop, offspring);
// after replace, the new pop is in _pop. Worths are recalculated if necessary // after replace, the new pop is in _pop. Worths are recalculated if necessary
replace (_pop, offspring); replace (_pop, offspring);
} }
while (continuator (_pop)); while (continuator (_pop));
} }
protected: protected:
/** a continuator based on the number of generations (used as default) */ /** a continuator based on the number of generations (used as default) */
eoGenContinue < MOEOT > defaultGenContinuator; eoGenContinue < MOEOT > defaultGenContinuator;
/** stopping criteria */ /** stopping criteria */
eoContinue < MOEOT > & continuator; eoContinue < MOEOT > & continuator;
/** default eval */
class DummyEval : public eoEvalFunc < MOEOT >
{
public:
void operator()(MOEOT &) {}
}
defaultEval;
/** evaluation function */
eoEvalFunc < MOEOT > & eval;
/** default popEval */
eoPopLoopEval < MOEOT > defaultPopEval;
/** evaluation function used to evaluate the whole population */ /** evaluation function used to evaluate the whole population */
eoPopLoopEval < MOEOT > popEval; eoPopEvalFunc < MOEOT > & popEval;
/** default select */
class DummySelect : public eoSelect < MOEOT >
{
public :
void operator()(const eoPop<MOEOT>&, eoPop<MOEOT>&) {}
}
defaultSelect;
/** binary tournament selection */ /** binary tournament selection */
moeoDetTournamentSelect < MOEOT > select; moeoDetTournamentSelect < MOEOT > select;
/** fitness assignment used in IBEA */ /** default select many */
moeoExpBinaryIndicatorBasedFitnessAssignment < MOEOT > fitnessAssignment; eoSelectMany < MOEOT > selectMany;
/** dummy diversity assignment */ /** select transform */
moeoDummyDiversityAssignment < MOEOT > dummyDiversityAssignment; eoSelectTransform < MOEOT > selectTransform;
/** elitist replacement */ /** a default crossover */
moeoEnvironmentalReplacement < MOEOT > replace; eoQuadCloneOp < MOEOT > defaultQuadOp;
/** a default mutation */
eoMonCloneOp < MOEOT > defaultMonOp;
/** an object for genetic operators (used as default) */ /** an object for genetic operators (used as default) */
eoSGAGenOp < MOEOT > defaultSGAGenOp; eoSGAGenOp < MOEOT > defaultSGAGenOp;
/** default transform */
class DummyTransform : public eoTransform < MOEOT >
{
public :
void operator()(eoPop<MOEOT>&) {}
}
defaultTransform;
/** general breeder */ /** general breeder */
eoGeneralBreeder < MOEOT > genBreed; eoGeneralBreeder < MOEOT > genBreed;
/** breeder */ /** breeder */
eoBreed < MOEOT > & breed; eoBreed < MOEOT > & breed;
/** fitness assignment used in IBEA */
moeoExpBinaryIndicatorBasedFitnessAssignment < MOEOT > fitnessAssignment;
/** dummy diversity assignment */
moeoDummyDiversityAssignment < MOEOT > diversityAssignment;
/** environmental replacement */
moeoEnvironmentalReplacement < MOEOT > replace;
}; };
#endif /*MOEOIBEA_H_*/ #endif /*MOEOIBEA_H_*/