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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@211 331e1502-861f-0410-8da2-ba01fb791d7f
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liefooga 2007-04-12 08:26:52 +00:00
commit db21384417
17 changed files with 620 additions and 546 deletions
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branches/paradiseo-moeo-1.0/src/moeoIndicatorBasedFitnessAssignment.h
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@ -20,26 +20,31 @@
#include <metric/moeoNormalizedSolutionVsSolutionBinaryMetric.h>
/**
* Default is exponential
* Fitness assignment sheme based an Indicator proposed in:
* 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 strategy is, for instance, used in IBEA.
*/
template < class MOEOT >
class moeoIndicatorBasedFitnessAssignment : public moeoFitnessAssignment < MOEOT >
class moeoIndicatorBasedFitnessAssignment : public moeoParetoBasedFitnessAssignment < MOEOT >
{
public:
/** The type of objective vector */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Ctor
* @param ...
* Ctor.
* @param _metric the quality indicator
* @param _kappa the scaling factor
*/
moeoIndicatorBasedFitnessAssignment(moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > * _metric, const double _kappa) : metric(_metric), kappa(_kappa)
{}
/**
*
* Sets the fitness values for every solution contained in the population _pop
* @param _pop the population
*/
void operator()(eoPop < MOEOT > & _pop)
{
@ -52,26 +57,12 @@ public:
}
/////////////////////////////////////////////////////////////////////
// A SIMPLIFIER ! => utiliser la fonction d'en dessous ;-)
void updateByDeleting(eoPop < MOEOT > & _pop, MOEOT & _moeo)
{
vector < double > v;
v.resize(_pop.size());
for (unsigned i=0; i<_pop.size(); i++)
{
v[i] = (*metric)(_moeo.objectiveVector(), _pop[i].objectiveVector());
}
for (unsigned i=0; i<_pop.size(); i++)
{
_pop[i].fitness( _pop[i].fitness() + exp(-v[i]/kappa) );
}
}
void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
/**
* Updates the fitness values of the whole population _pop by taking the deletion of the objective vector _objVec into account.
* @param _pop the population
* @param _objecVec the objective vector
*/
void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
{
vector < double > v;
v.resize(_pop.size());
@ -84,40 +75,15 @@ public:
_pop[i].fitness( _pop[i].fitness() + exp(-v[i]/kappa) );
}
}
// IDEM !
void updateByAdding(eoPop < MOEOT > & _pop, MOEOT & _moeo)
{
vector < double > v;
// update every fitness values to take the new individual into account
v.resize(_pop.size());
for (unsigned i=0; i<_pop.size(); i++)
{
v[i] = (*metric)(_moeo.objectiveVector(), _pop[i].objectiveVector());
}
for (unsigned i=0; i<_pop.size(); i++)
{
_pop[i].fitness( _pop[i].fitness() - exp(-v[i]/kappa) );
}
// compute the fitness of the new individual
v.clear();
v.resize(_pop.size());
for (unsigned i=0; i<_pop.size(); i++)
{
v[i] = (*metric)(_pop[i].objectiveVector(), _moeo.objectiveVector());
}
double fitness = 0;
for (unsigned i=0; i<v.size(); i++)
{
fitness -= exp(-v[i]/kappa);
}
_moeo.fitness(fitness);
}
// update _pop et retourne la valeur de fitness de _objVec
double updateByAdding(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
/**
* Updates the fitness values of the whole population _pop by taking the adding of the objective vector _objVec into account
* and returns the fitness value of _objVec.
* @param _pop the population
* @param _objecVec the objective vector
*/
double updateByAdding(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
{
vector < double > v;
// update every fitness values to take the new individual into account
@ -146,12 +112,13 @@ public:
}
/////////////////////////////////////////////////////////////////////
protected:
/** the quality indicator */
moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > * metric;
/** the scaling factor */
double kappa;
/** the computed indicator values */
std::vector < std::vector<double> > values;
@ -176,9 +143,10 @@ protected:
}
}
/**
* Compute every indicator value : values[i] = I(_v[i], _o) !!!!!!!!!!!
* @param ...
* Compute every indicator value in values (values[i] = I(_v[i], _o))
* @param _pop the population
*/
void computeValues(const eoPop < MOEOT > & _pop)
{
@ -197,6 +165,11 @@ protected:
}
}
/**
* Sets the fitness value of the whple population
* @param _pop the population
*/
void setFitnesses(eoPop < MOEOT > & _pop)
{
for (unsigned i=0; i<_pop.size(); i++)
@ -205,6 +178,11 @@ protected:
}
}
/**
* Returns the fitness value of the _idx th individual of the population
* @param _idx the index
*/
double computeFitness(const unsigned _idx)
{
double result = 0;
@ -217,6 +195,7 @@ protected:
}
return result;
}
};
#endif /*MOEOINDICATORBASEDFITNESSASSIGNMENT_H_*/