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Modifies PhyloMOEA clases in order to compile to last Paradiseo-MOEO svn version

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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@1363 331e1502-861f-0410-8da2-ba01fb791d7f
This commit is contained in:
wcancino 2009-01-23 11:31:18 +00:00
commit 68ec20fd66
6 changed files with 125 additions and 96 deletions
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7
contribution/branches/PhyloMOEA/PhyloMOEA/PhyloMOEA.cpp
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@ -7,7 +7,8 @@
#include <PhyloMOEO_archive.h>
#include <PhyloMOEOProbMatrixContainerUpdater.h>
#include <moeoNSGAII2.h>
#include <moeoObjVecStat.h>
#include <utils/moeoBestObjVecStat.h>
#include <utils/moeoAverageObjVecStat.h>
#include <PhyloMOEOPartitionStat.h>
#include <eoCountedFileMonitor.h>
#include <eoSingleFileCountedStateSaver.h>
@ -165,7 +166,7 @@ int main(int argc, char *argv[])
cout << " done\n";
PhyloMOEOFinalSolutionsArchive finalsolutions;
finalsolutions.update(population);
finalsolutions.operator()(population);
//remove_final_solutions( population );
// optimize remaining solutions
@ -202,7 +203,7 @@ int main(int argc, char *argv[])
cout << "\nCalculating Pareto-optimal Solutions...";
PhyloMOEOParetoSolutionsArchive paretosolutions;
paretosolutions.update(finalsolutions);
paretosolutions.operator()(finalsolutions);
paretosolutions.save_scores(path + datafile + "_pareto_scores_" + expid + ".txt","#Pareto Solutions Scores");
paretosolutions.save_trees(path + datafile + "_pareto_trees_" + expid + ".txt");
cout << " done\n";

2
contribution/branches/PhyloMOEA/PhyloMOEA/PhyloMOEOPartitionStat.h
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@ -20,7 +20,7 @@
#ifndef PHYLOMOEOPARTITONSTAT_H_
#define PHYLOMOEOPARTITONSTAT_H_
#include <PhyloMOEA/moeoObjVecStat.h>
#include <moeoObjVecStat.h>
#include <PhyloMOEO.h>
//#include <utils.h>

12
contribution/branches/PhyloMOEA/PhyloMOEA/PhyloMOEO_archive.h
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@ -20,7 +20,7 @@
#ifndef PHYLOMOEO_ARCHIVE_H
#define PHYLOMOEO_ARCHIVE_H
#include <PhyloMOEA/PhyloMOEO.h>
#include <PhyloMOEO.h>
typedef moeoArchive<PhyloMOEO> PhyloMOEOArchive;
typedef PhyloMOEOArchive PhyloMOEOPFArchive;
@ -28,7 +28,7 @@ typedef PhyloMOEOArchive PhyloMOEOPFArchive;
class PhyloMOEOParetoSolutionsArchive:public moeoArchive<PhyloMOEO>
class PhyloMOEOParetoSolutionsArchive:public moeoUnboundedArchive<PhyloMOEO>
{
public:
void save_trees( std::string filename, string title="" )
@ -65,6 +65,7 @@ class PhyloMOEOParetoSolutionsArchive:public moeoArchive<PhyloMOEO>
class PhyloMOEODummyArchive:public PhyloMOEOParetoSolutionsArchive
{
public:
void update(const eoPop < PhyloMOEO > & _pop)
{
std::copy(_pop.begin(), _pop.end(), back_inserter(*this) );
@ -74,8 +75,15 @@ class PhyloMOEODummyArchive:public PhyloMOEOParetoSolutionsArchive
class PhyloMOEOFinalSolutionsArchive: public PhyloMOEOParetoSolutionsArchive
{
public:
// overwrite the default operator
void operator()(const eoPop < PhyloMOEO > & _pop) { update(_pop); }
protected:
void update(const eoPop < PhyloMOEO > & _pop)
{
std::copy(_pop.begin(), _pop.end(), back_inserter(*this) );
moeoParetoObjectiveVectorComparator < ObjectiveVector > paretoComparator;

2
contribution/branches/PhyloMOEA/PhyloMOEA/moeoElitistReplacement2.h
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@ -44,7 +44,7 @@
#include <diversity/moeoDummyDiversityAssignment.h>
#include <fitness/moeoFitnessAssignment.h>
#include <replacement/moeoReplacement.h>
#include <PhyloMOEA/vectorSortIndex.h>
#include <vectorSortIndex.h>
/**
* Elitist replacement strategy that consists in keeping the N best individuals.

18
contribution/branches/PhyloMOEA/PhyloMOEA/moeoFrontByFrontCrowdingDiversityAssignment2.h
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@ -40,7 +40,7 @@
#include <diversity/moeoCrowdingDiversityAssignment.h>
#include <comparator/moeoFitnessThenDiversityComparator.h>
#include <PhyloMOEA/moeoPtrComparator.h>
#include <moeoPtrComparator.h>
/**
@ -91,12 +91,12 @@ class moeoFrontByFrontCrowdingDiversityAssignment2 : public moeoCrowdingDiversit
}
// sort the whole pop according to fitness values
moeoFitnessThenDiversityComparator < MOEOT > fitnessComparator;
std::vector<const MOEOT *> sortedptrpop;
std::vector<MOEOT *> sortedptrpop;
sortedptrpop.resize(_pop.size());
// due to intensive sort operations for this diversity assignment,
// it is more efficient to perform sorts using only pointers to the
// population members in order to avoid copy of individuals
std::transform( _pop.begin(), _pop.end(), sortedptrpop.begin(), typename eoPop<MOEOT>::Ref());
for(int i=0; i< _pop.size(); i++) sortedptrpop[i] = & (_pop[i]);
//sort the pointers to population members
moeoPtrComparator<MOEOT> cmp2( fitnessComparator);
std::sort(sortedptrpop.begin(), sortedptrpop.end(), cmp2);
@ -111,7 +111,7 @@ class moeoFrontByFrontCrowdingDiversityAssignment2 : public moeoCrowdingDiversit
{
for (unsigned int i=a; i<=b; i++)
{
((MOEOT *)sortedptrpop[i])->diversity(inf());
sortedptrpop[i]->diversity(inf());
//_pop[i].diversity(inf());
}
}
@ -136,13 +136,13 @@ class moeoFrontByFrontCrowdingDiversityAssignment2 : public moeoCrowdingDiversit
max += tiny();
}
// set the diversity value to infiny for min and max
((MOEOT *)sortedptrpop[a])->diversity(inf());
((MOEOT *)sortedptrpop[b])->diversity(inf());
sortedptrpop[a]->diversity(inf());
sortedptrpop[b]->diversity(inf());
// set the diversity values for the other individuals
for (unsigned int i=a+1; i<b; i++)
{
distance = ( (sortedptrpop[i-1])->objectiveVector()[obj] - (sortedptrpop[i+1])->objectiveVector()[obj]) / (max-min);
((MOEOT *)sortedptrpop[i])->diversity(sortedptrpop[i]->diversity() + distance);
distance = ( sortedptrpop[i-1]->objectiveVector()[obj] - sortedptrpop[i+1]->objectiveVector()[obj] ) / (max-min);
sortedptrpop[i]->diversity(sortedptrpop[i]->diversity() + distance);
}
}
}
@ -159,7 +159,7 @@ class moeoFrontByFrontCrowdingDiversityAssignment2 : public moeoCrowdingDiversit
* @param _start the index to start from
*/
unsigned int lastIndex (std::vector<const MOEOT *> & _pop, unsigned int _start)
unsigned int lastIndex (std::vector<MOEOT *> & _pop, unsigned int _start)
{
unsigned int i=_start;
while ( (i<_pop.size()-1) && (_pop[i]->fitness()==_pop[i+1]->fitness()) )

202
contribution/branches/PhyloMOEA/PhyloMOEA/moeoNSGAII2.h
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@ -1,7 +1,7 @@
/*
* <moeoNSGAII.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2008
* (C) OPAC Team, LIFL, 2002-2008
*
* Arnaud Liefooghe
*
@ -39,6 +39,7 @@
#define MOEONSGAII2_H_
#include <eoBreed.h>
#include <eoCloneOps.h>
#include <eoContinue.h>
#include <eoEvalFunc.h>
#include <eoGenContinue.h>
@ -47,144 +48,163 @@
#include <eoPopEvalFunc.h>
#include <eoSGAGenOp.h>
#include <algo/moeoEA.h>
#include <PhyloMOEA/moeoFrontByFrontCrowdingDiversityAssignment2.h>
#include <fitness/moeoFastNonDominatedSortingFitnessAssignment.h>
#include <PhyloMOEA/moeoElitistReplacement2.h>
#include <moeoFrontByFrontCrowdingDiversityAssignment2.h>
#include <fitness/moeoDominanceDepthFitnessAssignment.h>
#include <replacement/moeoElitistReplacement.h>
#include <selection/moeoDetTournamentSelect.h>
#include <eoCloneOps.h>
/**
* NSGA-II (Non-dominated Sorting Genetic Algorithm II) as described in:
* Deb, K., S. Agrawal, A. Pratap, and T. Meyarivan : "A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II".
* In IEEE Transactions on Evolutionary Computation, Vol. 6, No 2, pp 182-197 (April 2002).
* NSGA-II (Non-dominated Sorting Genetic Algorithm II).
* Deb, K., S. Agrawal, A. Pratap, and T. Meyarivan. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. IEEE Transactions on Evolutionary Computation, Vol. 6, No 2, pp 182-197 (2002).
* This class builds the NSGA-II algorithm only by using the fine-grained components of the ParadisEO-MOEO framework.
*/
template < class MOEOT >
class moeoNSGAII2: public moeoEA < MOEOT >
{
public:
/**
* Simple ctor with a eoGenOp.
* @param _maxGen number of generations before stopping
* @param _eval evaluation function
* @param _op variation operator
*/
moeoNSGAII2 (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), popEval(_eval), select(2),
replace(fitnessAssignment, diversityAssignment), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0),
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
*/
moeoNSGAII2 (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _op) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), popEval(_eval), select(2),
replace(fitnessAssignment, diversityAssignment), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0),
genBreed(select, _op), breed(genBreed)
{}
{
public:
/**
* 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 _maxGen maximum number of generations before stopping
* @param _eval evaluation function
* @param _crossover crossover
* @param _pCross crossover probability
* @param _mutation mutation
* @param _pMut mutation probability
*/
moeoNSGAII2 (unsigned int _maxGen, eoEvalFunc < MOEOT > & _eval, eoQuadOp < MOEOT > & _crossover, double _pCross, eoMonOp < MOEOT > & _mutation, double _pMut) :
defaultGenContinuator(_maxGen), continuator(defaultGenContinuator), popEval(_eval), select (2),
replace (fitnessAssignment, diversityAssignment), defaultSGAGenOp(_crossover, _pCross, _mutation, _pMut),
genBreed (select, defaultSGAGenOp), breed (genBreed)
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), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a continuator (instead of _maxGen) and a eoGenOp.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _op variation operator
*/
moeoNSGAII2 (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op) :
defaultGenContinuator(0), continuator(_continuator), popEval(_eval), select(2),
replace(fitnessAssignment, diversityAssignment), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0),
genBreed(select, _op), breed(genBreed)
{}
/**
* Ctor with a continuator (instead of _maxGen) and a eoTransform.
* Ctor with a eoContinue and a eoGenOp.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _op variation operator
*/
moeoNSGAII2 (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _op) :
continuator(_continuator), popEval(_eval), select(2),
replace(fitnessAssignment, diversityAssignment), defaultSGAGenOp(defaultQuadOp, 0.0, defaultMonOp, 0.0),
genBreed(select, _op), breed(genBreed)
* @param _op variation operators
*/
moeoNSGAII2 (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoGenOp < MOEOT > & _op) :
defaultGenContinuator(0), continuator(_continuator), eval(_eval), defaultPopEval(_eval), popEval(defaultPopEval), select(2),
selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Apply a few generation of evolution to the population _pop until the stopping criteria is verified.
* Ctor with a eoContinue, a eoPopEval and a eoGenOp.
* @param _continuator stopping criteria
* @param _popEval population evaluation function
* @param _op variation operators
*/
moeoNSGAII2 (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoGenOp < MOEOT > & _op) :
defaultGenContinuator(0), continuator(_continuator), eval(defaultEval), defaultPopEval(eval), popEval(_popEval), select(2),
selectMany(select,0.0), selectTransform(defaultSelect, defaultTransform), defaultSGAGenOp(defaultQuadOp, 1.0, defaultMonOp, 1.0), genBreed(select, _op), breed(genBreed), replace (fitnessAssignment, diversityAssignment)
{}
/**
* Ctor with a eoContinue and a eoTransform.
* @param _continuator stopping criteria
* @param _eval evaluation function
* @param _transform variation operator
*/
moeoNSGAII2 (eoContinue < MOEOT > & _continuator, eoEvalFunc < MOEOT > & _eval, eoTransform < MOEOT > & _transform) :
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), 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
*/
moeoNSGAII2 (eoContinue < MOEOT > & _continuator, eoPopEvalFunc < MOEOT > & _popEval, eoTransform < MOEOT > & _transform) :
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), replace(fitnessAssignment, diversityAssignment)
{}
/**
* Apply a the algorithm to the population _pop until the stopping criteria is satified.
* @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
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);
// 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));
while (continuator (_pop));
}
protected:
protected:
/** a continuator based on the number of generations (used as default) */
eoGenContinue < MOEOT > defaultGenContinuator;
/** stopping criteria */
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 */
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 */
moeoDetTournamentSelect < MOEOT > select;
/** fitness assignment used in NSGA-II */
moeoFastNonDominatedSortingFitnessAssignment < MOEOT > fitnessAssignment;
/** diversity assignment used in NSGA-II */
moeoFrontByFrontCrowdingDiversityAssignment2 < MOEOT > diversityAssignment;
/** elitist replacement */
moeoElitistReplacement2 < MOEOT > replace;
/** default select many */
eoSelectMany < MOEOT > selectMany;
/** select transform */
eoSelectTransform < MOEOT > selectTransform;
/** a default crossover */
eoQuadCloneOp < MOEOT > defaultQuadOp;
/** a default mutation */
eoMonCloneOp < MOEOT > defaultMonOp;
/** an object for genetic operators (used as default) */
eoSGAGenOp < MOEOT > defaultSGAGenOp;
/** default transform */
class DummyTransform : public eoTransform < MOEOT >
{
public :
void operator()(eoPop<MOEOT>&) {}
}
defaultTransform;
/** general breeder */
eoGeneralBreeder < MOEOT > genBreed;
/** breeder */
eoBreed < MOEOT > & breed;
/** fitness assignment used in NSGA */
moeoDominanceDepthFitnessAssignment < MOEOT > fitnessAssignment;
/** diversity assignment used in NSGA-II */
moeoFrontByFrontCrowdingDiversityAssignment2 < MOEOT > diversityAssignment;
/** elitist replacement */
moeoElitistReplacement < MOEOT > replace;
};
};
#endif /*MOEONSGAII_H_*/