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Add hyper volume continuators & metrics handling feasibility constraint on objectives

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This commit is contained in:
Johann Dreo 2013-06-11 13:29:57 +02:00 • committed by LPTK
commit df4db4d623
4 changed files with 262 additions and 47 deletions
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119
moeo/src/continue/moeoHypContinue.h
View file

@ -46,11 +46,11 @@
#include <archive/moeoUnboundedArchive.h>
/**
Continues until the optimum ParetoSet level is reached.
Continues until the given ParetoSet level is reached.
@ingroup Continuators
*/
template< class MOEOT>
template< class MOEOT, class MetricT = moeoHyperVolumeDifferenceMetric<typename MOEOT::ObjectiveVector> >
class moeoHypContinue: public eoContinue<MOEOT>
{
public:
@ -71,8 +71,20 @@ public:
vectorToParetoSet(_OptimVec);
}
/** Returns false when a ParetoSet is reached. */
virtual bool operator() ( const eoPop<MOEOT>& _pop )
{
std::vector<ObjectiveVector> bestCurrentParetoSet = pareto( arch );
return is_null_hypervolume( bestCurrentParetoSet );
}
virtual std::string className(void) const { return "moeoHypContinue"; }
protected:
std::vector<ObjectiveVector> pareto( moeoArchive<MOEOT> & _archive )
{
std::vector < ObjectiveVector > bestCurrentParetoSet;
@ -80,7 +92,12 @@ public:
bestCurrentParetoSet.push_back(arch[i].objectiveVector());
}
double hypervolume= metric(bestCurrentParetoSet,OptimSet );
return bestCurrentParetoSet;
}
bool is_null_hypervolume( std::vector<ObjectiveVector>& bestCurrentParetoSet )
{
double hypervolume= metric( bestCurrentParetoSet, OptimSet );
if (hypervolume==0) {
eo::log << eo::logging << "STOP in moeoHypContinue: Best ParetoSet has been reached "
@ -91,7 +108,7 @@ public:
}
/** Translate a vector given as param to the ParetoSet that should be reached. */
void vectorToParetoSet(const std::vector<AtomType> & _OptimVec)
virtual void vectorToParetoSet(const std::vector<AtomType> & _OptimVec)
{
unsigned dim = (unsigned)(_OptimVec.size()/ObjectiveVector::Traits::nObjectives());
OptimSet.resize(dim);
@ -104,12 +121,98 @@ public:
}
}
virtual std::string className(void) const { return "moeoHypContinue"; }
private:
protected:
moeoArchive <MOEOT> & arch;
moeoHyperVolumeDifferenceMetric <ObjectiveVector> metric;
MetricT metric;
std::vector <ObjectiveVector> OptimSet;
};
/**
Continues until the (feasible or unfeasible) given Pareto set is reached.
@ingroup Continuators
*/
template< class MOEOT, class MetricT = moeoDualHyperVolumeDifferenceMetric<typename MOEOT::ObjectiveVector> >
class moeoDualHypContinue: public moeoHypContinue<MOEOT, MetricT >
{
protected:
bool is_feasible;
using moeoHypContinue<MOEOT, MetricT>::arch;
using moeoHypContinue<MOEOT, MetricT>::OptimSet;
public:
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
typedef typename ObjectiveVector::Type AtomType;
/** A continuator that stops once a given Pareto front has been reached
*
* You should specify the feasibility of the targeted front.
* NOTE: the MOEOT::ObjectiveVector is supposed to implement the moeoDualRealObjectiveVector interface.
*
*/
moeoDualHypContinue<MOEOT, MetricT>( const std::vector<AtomType> & _OptimVec, bool _is_feasible, moeoArchive < MOEOT > & _archive, bool _normalize=true, double _rho=1.1 )
: moeoHypContinue<MOEOT, MetricT>( _OptimVec, _archive, _normalize, _rho ), is_feasible(_is_feasible)
{
assert( _OptimVec.size() > 0);
vectorToParetoSet(_OptimVec);
}
/** A continuator that stops once a given Pareto front has been reached
*
* You should specify the feasibility of the targeted front.
* NOTE: the MOEOT::ObjectiveVector is supposed to implement the moeoDualRealObjectiveVector interface.
*
*/
moeoDualHypContinue<MOEOT, MetricT>( const std::vector<AtomType> & _OptimVec, bool _is_feasible, moeoArchive < MOEOT > & _archive, bool _normalize=true, ObjectiveVector& _ref_point=NULL )
: moeoHypContinue<MOEOT, MetricT>( _OptimVec, _archive, _normalize, _ref_point ), is_feasible(_is_feasible)
{
assert( _OptimVec.size() > 0);
vectorToParetoSet(_OptimVec);
}
/** Returns false when a ParetoSet is reached. */
virtual bool operator() ( const eoPop<MOEOT>& _pop )
{
std::vector<ObjectiveVector> bestCurrentParetoSet = pareto( arch );
#ifndef NDEBUG
assert( bestCurrentParetoSet.size() > 0 );
for( unsigned int i=1; i<bestCurrentParetoSet.size(); ++i ) {
assert( bestCurrentParetoSet[i].is_feasible() == bestCurrentParetoSet[0].is_feasible() );
}
#endif
// The current Pareto front is either feasible or unfeasible.
// It could not contains both kind of objective vectors, because a feasible solution always dominates an unfeasible front.
if( bestCurrentParetoSet[0].is_feasible() != OptimSet[0].is_feasible() ) {
return false;
}
return is_null_hypervolume( bestCurrentParetoSet );
}
protected:
using moeoHypContinue<MOEOT, MetricT>::pareto;
using moeoHypContinue<MOEOT, MetricT>::is_null_hypervolume;
/** Translate a vector given as param to the ParetoSet that should be reached. */
virtual void vectorToParetoSet(const std::vector<AtomType> & _OptimVec)
{
unsigned dim = (unsigned)(_OptimVec.size()/ObjectiveVector::Traits::nObjectives());
OptimSet.resize(dim);
unsigned k=0;
for(size_t i=0; i < dim; i++) {
for (size_t j=0; j < ObjectiveVector::Traits::nObjectives(); j++) {
// Use the feasibility declaration of an eoDualFitness
OptimSet[i][j] = AtomType(_OptimVec[k++], is_feasible);
}
}
}
};
#endif

27
moeo/src/fitness/moeoExpBinaryIndicatorBasedDualFitnessAssignment.h
View file

@ -10,6 +10,9 @@ protected:
public:
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
typedef typename ObjectiveVector::Type Type;
using moeoExpBinaryIndicatorBasedFitnessAssignment<MOEOT>::values;
moeoExpBinaryIndicatorBasedDualFitnessAssignment(
moeoNormalizedSolutionVsSolutionBinaryMetric<ObjectiveVector,double> & metric,
@ -54,11 +57,33 @@ public:
this->setFitnesses(*ppop);
}
/**
* Compute every indicator value in values (values[i] = I(_v[i], _o))
* @param _pop the population
*/
void computeValues(const eoPop < MOEOT > & _pop)
{
values.clear();
values.resize(_pop.size());
for (unsigned int i=0; i<_pop.size(); i++)
{
values[i].resize(_pop.size());
// the metric may not be symetric, thus neither is the matrix
for (unsigned int j=0; j<_pop.size(); j++)
{
if (i != j)
{
values[i][j] = Type( metric(_pop[i].objectiveVector(), _pop[j].objectiveVector()), _pop[i].objectiveVector().is_feasible() );
}
}
}
}
virtual void setFitnesses(eoPop < MOEOT > & pop)
{
for (unsigned int i=0; i<pop.size(); i++) {
// We should maintain the feasibility of the fitness across computations
pop[i].fitness( this->computeFitness(i), pop[i].is_feasible() );
pop[i].fitness( this->computeFitness(i), pop[i].fitness().is_feasible() );
}
}

2
moeo/src/fitness/moeoExpBinaryIndicatorBasedFitnessAssignment.h
View file

@ -187,7 +187,7 @@ class moeoExpBinaryIndicatorBasedFitnessAssignment : public moeoBinaryIndicatorB
{
if (i != j)
{
values[i][j] = metric(_pop[i].objectiveVector(), _pop[j].objectiveVector());
values[i][j] = Type( metric(_pop[i].objectiveVector(), _pop[j].objectiveVector()) );
}
}
}

153
moeo/src/metric/moeoHyperVolumeDifferenceMetric.h
View file

@ -86,41 +86,42 @@ class moeoHyperVolumeDifferenceMetric : public moeoVectorVsVectorBinaryMetric <
*/
double operator()(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2)
{
double hypervolume_set1;
double hypervolume_set2;
if(rho >= 1.0){
//determine bounds
setup(_set1, _set2);
//determine reference point
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++){
if(normalize){
if (ObjectiveVector::Traits::minimizing(i))
ref_point[i]= rho;
else
ref_point[i]= 1-rho;
}
else{
if (ObjectiveVector::Traits::minimizing(i))
ref_point[i]= bounds[i].maximum() * rho;
else
ref_point[i]= bounds[i].maximum() * (1-rho);
}
}
//if no normalization, reinit bounds to O..1 for
if(!normalize)
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
bounds[i] = eoRealInterval(0,1);
double hypervolume_set1;
double hypervolume_set2;
}
else if(normalize)
setup(_set1, _set2);
if(rho >= 1.0){
//determine bounds
setup(_set1, _set2);
//determine reference point
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++){
if(normalize){
if (ObjectiveVector::Traits::minimizing(i))
ref_point[i]= rho;
else
ref_point[i]= 1-rho;
}
else{
if (ObjectiveVector::Traits::minimizing(i))
ref_point[i]= bounds[i].maximum() * rho;
else
ref_point[i]= bounds[i].maximum() * (1-rho);
}
}
//if no normalization, reinit bounds to O..1 for
if(!normalize)
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
bounds[i] = eoRealInterval(0,1);
moeoHyperVolumeMetric <ObjectiveVector> unaryMetric(ref_point, bounds);
hypervolume_set1 = unaryMetric(_set1);
hypervolume_set2 = unaryMetric(_set2);
}
else if(normalize)
setup(_set1, _set2);
return hypervolume_set1 - hypervolume_set2;
moeoHyperVolumeMetric <ObjectiveVector> unaryMetric(ref_point, bounds);
hypervolume_set1 = unaryMetric(_set1);
hypervolume_set2 = unaryMetric(_set2);
return hypervolume_set1 - hypervolume_set2;
}
/**
@ -132,7 +133,7 @@ class moeoHyperVolumeDifferenceMetric : public moeoVectorVsVectorBinaryMetric <
}
/**
* method caclulate bounds for the normalization
* method calculate bounds for the normalization
* @param _set1 the vector contains all objective Vector of the first pareto front
* @param _set2 the vector contains all objective Vector of the second pareto front
*/
@ -182,7 +183,7 @@ class moeoHyperVolumeDifferenceMetric : public moeoVectorVsVectorBinaryMetric <
return 1e-6;
}
private:
protected:
/*boolean indicates if data must be normalized or not*/
bool normalize;
@ -196,4 +197,90 @@ class moeoHyperVolumeDifferenceMetric : public moeoVectorVsVectorBinaryMetric <
};
template<class ObjectiveVector>
class moeoDualHyperVolumeDifferenceMetric : public moeoHyperVolumeDifferenceMetric<ObjectiveVector>
{
protected:
using moeoHyperVolumeDifferenceMetric<ObjectiveVector>::rho;
using moeoHyperVolumeDifferenceMetric<ObjectiveVector>::normalize;
using moeoHyperVolumeDifferenceMetric<ObjectiveVector>::ref_point;
using moeoHyperVolumeDifferenceMetric<ObjectiveVector>::bounds;
public:
typedef typename ObjectiveVector::Type Type;
moeoDualHyperVolumeDifferenceMetric( bool _normalize=true, double _rho=1.1)
: moeoHyperVolumeDifferenceMetric<ObjectiveVector>(_normalize, _rho)
{
}
moeoDualHyperVolumeDifferenceMetric( bool _normalize/*=true*/, ObjectiveVector& _ref_point/*=NULL*/ )
: moeoHyperVolumeDifferenceMetric<ObjectiveVector>( _normalize, _ref_point )
{
}
/**
* calculates and returns the HyperVolume value of a pareto front
* @param _set1 the vector contains all objective Vector of the first pareto front
* @param _set2 the vector contains all objective Vector of the second pareto front
*/
double operator()(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2)
{
#ifndef NDEBUG
// the two sets must be homogeneous in feasibility
assert( _set1.size() > 0 );
for( unsigned int i=1; i<_set1.size(); ++i ) {
assert( _set1[i].is_feasible() == _set1[0].is_feasible() );
}
assert( _set2.size() > 0 );
for( unsigned int i=1; i<_set2.size(); ++i ) {
assert( _set2[i].is_feasible() == _set2[0].is_feasible() );
}
// and they must have the same feasibility
assert( _set1[0].is_feasible() == _set2[0].is_feasible() );
#endif
bool feasible = _set1[0].is_feasible();
double hypervolume_set1;
double hypervolume_set2;
if(rho >= 1.0){
//determine bounds
setup(_set1, _set2);
//determine reference point
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++){
if(normalize){
if (ObjectiveVector::Traits::minimizing(i))
ref_point[i]= Type(rho, feasible);
else
ref_point[i]= Type(1-rho, feasible);
}
else{
if (ObjectiveVector::Traits::minimizing(i))
ref_point[i]= Type(bounds[i].maximum() * rho, feasible);
else
ref_point[i]= Type(bounds[i].maximum() * (1-rho), feasible);
}
}
//if no normalization, reinit bounds to O..1 for
if(!normalize)
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
bounds[i] = eoRealInterval(0,1);
}
else if(normalize)
setup(_set1, _set2);
moeoHyperVolumeMetric <ObjectiveVector> unaryMetric(ref_point, bounds);
hypervolume_set1 = unaryMetric(_set1);
hypervolume_set2 = unaryMetric(_set2);
return hypervolume_set1 - hypervolume_set2;
}
};
#endif /*MOEOHYPERVOLUMEMETRIC_H_*/