nojhan/paradiseo
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

New style for MOEO

Browse source 
git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@788 331e1502-861f-0410-8da2-ba01fb791d7f
This commit is contained in:
canape 2007-11-16 11:29:25 +00:00
commit 39709d3d12
103 changed files with 2607 additions and 2521 deletions
Download patch file Download diff file Expand all files Collapse all files

112
trunk/paradiseo-moeo/src/fitness/moeoExpBinaryIndicatorBasedFitnessAssignment.h
View file

@ -1,4 +1,4 @@
/*
/*
* <moeoExpBinaryIndicatorBasedFitnessAssignment.h>
* Copyright (C) DOLPHIN Project-Team, INRIA Futurs, 2006-2007
* (C) OPAC Team, LIFL, 2002-2007
@ -52,8 +52,8 @@
*/
template < class MOEOT >
class moeoExpBinaryIndicatorBasedFitnessAssignment : public moeoBinaryIndicatorBasedFitnessAssignment < MOEOT >
{
public:
{
public:
/** The type of objective vector */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
@ -74,12 +74,12 @@ public:
*/
void operator()(eoPop < MOEOT > & _pop)
{
// 1 - setting of the bounds
setup(_pop);
// 2 - computing every indicator values
computeValues(_pop);
// 3 - setting fitnesses
setFitnesses(_pop);
// 1 - setting of the bounds
setup(_pop);
// 2 - computing every indicator values
computeValues(_pop);
// 3 - setting fitnesses
setFitnesses(_pop);
}
@ -90,15 +90,15 @@ public:
*/
void updateByDeleting(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
{
std::vector < double > v;
v.resize(_pop.size());
for (unsigned int i=0; i<_pop.size(); i++)
std::vector < double > v;
v.resize(_pop.size());
for (unsigned int i=0; i<_pop.size(); i++)
{
v[i] = metric(_objVec, _pop[i].objectiveVector());
v[i] = metric(_objVec, _pop[i].objectiveVector());
}
for (unsigned int i=0; i<_pop.size(); i++)
for (unsigned int i=0; i<_pop.size(); i++)
{
_pop[i].fitness( _pop[i].fitness() + exp(-v[i]/kappa) );
_pop[i].fitness( _pop[i].fitness() + exp(-v[i]/kappa) );
}
}
@ -111,34 +111,34 @@ public:
*/
double updateByAdding(eoPop < MOEOT > & _pop, ObjectiveVector & _objVec)
{
std::vector < double > v;
// update every fitness values to take the new individual into account
v.resize(_pop.size());
for (unsigned int i=0; i<_pop.size(); i++)
std::vector < double > v;
// update every fitness values to take the new individual into account
v.resize(_pop.size());
for (unsigned int i=0; i<_pop.size(); i++)
{
v[i] = metric(_objVec, _pop[i].objectiveVector());
v[i] = metric(_objVec, _pop[i].objectiveVector());
}
for (unsigned int i=0; i<_pop.size(); i++)
for (unsigned int i=0; i<_pop.size(); i++)
{
_pop[i].fitness( _pop[i].fitness() - exp(-v[i]/kappa) );
_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 int i=0; i<_pop.size(); i++)
// compute the fitness of the new individual
v.clear();
v.resize(_pop.size());
for (unsigned int i=0; i<_pop.size(); i++)
{
v[i] = metric(_pop[i].objectiveVector(), _objVec);
v[i] = metric(_pop[i].objectiveVector(), _objVec);
}
double result = 0;
for (unsigned int i=0; i<v.size(); i++)
double result = 0;
for (unsigned int i=0; i<v.size(); i++)
{
result -= exp(-v[i]/kappa);
result -= exp(-v[i]/kappa);
}
return result;
return result;
}
protected:
protected:
/** the quality indicator */
moeoNormalizedSolutionVsSolutionBinaryMetric < ObjectiveVector, double > & metric;
@ -154,18 +154,18 @@ protected:
*/
void setup(const eoPop < MOEOT > & _pop)
{
double min, max;
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
double min, max;
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
{
min = _pop[0].objectiveVector()[i];
max = _pop[0].objectiveVector()[i];
for (unsigned int j=1; j<_pop.size(); j++)
min = _pop[0].objectiveVector()[i];
max = _pop[0].objectiveVector()[i];
for (unsigned int j=1; j<_pop.size(); j++)
{
min = std::min(min, _pop[j].objectiveVector()[i]);
max = std::max(max, _pop[j].objectiveVector()[i]);
min = std::min(min, _pop[j].objectiveVector()[i]);
max = std::max(max, _pop[j].objectiveVector()[i]);
}
// setting of the bounds for the objective i
metric.setup(min, max, i);
// setting of the bounds for the objective i
metric.setup(min, max, i);
}
}
@ -176,16 +176,16 @@ protected:
*/
void computeValues(const eoPop < MOEOT > & _pop)
{
values.clear();
values.resize(_pop.size());
for (unsigned int i=0; i<_pop.size(); i++)
values.clear();
values.resize(_pop.size());
for (unsigned int i=0; i<_pop.size(); i++)
{
values[i].resize(_pop.size());
for (unsigned int j=0; j<_pop.size(); j++)
values[i].resize(_pop.size());
for (unsigned int j=0; j<_pop.size(); j++)
{
if (i != j)
if (i != j)
{
values[i][j] = metric(_pop[i].objectiveVector(), _pop[j].objectiveVector());
values[i][j] = metric(_pop[i].objectiveVector(), _pop[j].objectiveVector());
}
}
}
@ -198,9 +198,9 @@ protected:
*/
void setFitnesses(eoPop < MOEOT > & _pop)
{
for (unsigned int i=0; i<_pop.size(); i++)
for (unsigned int i=0; i<_pop.size(); i++)
{
_pop[i].fitness(computeFitness(i));
_pop[i].fitness(computeFitness(i));
}
}
@ -211,17 +211,17 @@ protected:
*/
double computeFitness(const unsigned int _idx)
{
double result = 0;
for (unsigned int i=0; i<values.size(); i++)
double result = 0;
for (unsigned int i=0; i<values.size(); i++)
{
if (i != _idx)
if (i != _idx)
{
result -= exp(-values[i][_idx]/kappa);
result -= exp(-values[i][_idx]/kappa);
}
}
return result;
return result;
}
};
};
#endif /*MOEOEXPBINARYINDICATORBASEDFITNESSASSIGNMENT_H_*/