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BUGFIX pop split everywhere in exp dual fitness assignment

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Apply the fitness assignment on both splited pop, not just one.
Apply also the partial update on splited pop.
Confine numeric valuesto double limits, to avoid overflows.
This commit is contained in:
Johann Dreo 2013-06-26 18:09:49 +02:00
commit 5b39705a20
1 changed files with 77 additions and 12 deletions
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89
moeo/src/fitness/moeoExpBinaryIndicatorBasedDualFitnessAssignment.h
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@ -57,21 +57,28 @@ public:
// separate the pop in feasible/unfeasible
_pop_split( pop );
eoPop<MOEOT>* ppop;
// if there is at least one feasible individual,
// it will supersede all the unfeasible ones
if( _pop_split.feasible().size() == 0 ) {
ppop = & _pop_split.unfeasible();
} else {
ppop = & _pop_split.feasible();
if( _pop_split.unfeasible().size() != 0 ) {
this->setup(_pop_split.unfeasible());
this->computeValues(_pop_split.unfeasible());
this->setFitnesses(_pop_split.unfeasible()); // NOTE: this alter individuals
}
this->setup(*ppop);
this->computeValues(*ppop);
this->setFitnesses(*ppop); // NOTE: this alter individuals
if( _pop_split.feasible().size() != 0 ) {
this->setup(_pop_split.feasible());
this->computeValues(_pop_split.feasible());
this->setFitnesses(_pop_split.feasible()); // NOTE: this alter individuals
}
// bring back altered individuals in the pop
pop = _pop_split.merge();
// pop = _pop_split.merge();
eoPop<MOEOT> merged = _pop_split.merge();
assert( pop.size() == merged.size());
for( unsigned int i=0; i<pop.size(); ++i ) {
pop[i] = merged[i];
}
}
@ -131,7 +138,7 @@ protected:
metric( pop[i].objectiveVector(), pop[j].objectiveVector() ),
pop[i].objectiveVector().is_feasible()
);
} else { // if i != j
} else { // if i == j
assert( i == j );
values[i][j] = Type( 0.0, pop[i].objectiveVector().is_feasible() );
}
@ -151,14 +158,72 @@ protected:
{
// Fitness result( 0.0, values[_idx][_idx].is_feasible() );
Fitness result( 0.0, values[_idx][_idx].is_feasible() );
for (unsigned int i=0; i<values.size(); i++) {
for (unsigned int i=0; i<values.size(); i++) { // i in pop.size()
if (i != _idx) {
result -= exp(-values[i][_idx]/kappa);
// result += values[i][_idx];
}
}
return result;
return confine(result);
}
/**
* 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 objVec the objective vector
*/
void updateByDeleting(eoPop < MOEOT > & pop, ObjectiveVector & objVec)
{
_pop_split(pop);
if( objVec.is_feasible() ) {
setup(_pop_split.feasible());
updateFitnessByDeleting( _pop_split.feasible(), objVec);
} else {
setup(_pop_split.unfeasible());
updateFitnessByDeleting( _pop_split.unfeasible(), objVec );
}
// pop = _pop_split.merge();
eoPop<MOEOT> merged = _pop_split.merge();
assert( pop.size() == merged.size());
for( unsigned int i=0; i<pop.size(); ++i ) {
pop[i] = merged[i];
}
}
protected:
void updateFitnessByDeleting( eoPop < MOEOT > & pop, ObjectiveVector & objVec )
{
std::vector < double > v;
v.resize(pop.size());
for (unsigned int i=0; i<pop.size(); i++)
{
v[i] = metric(objVec, pop[i].objectiveVector());
}
for (unsigned int i=0; i<pop.size(); i++)
{
pop[i].fitness( confine( pop[i].fitness() + exp(-v[i]/kappa) ), pop[i].is_feasible() );
}
}
template<class T>
T confine( T n )
{
T tmax = std::numeric_limits<typename T::Base>::max();
T tmin = -1 * tmax;
tmin.is_feasible( n.is_feasible() );
tmax.is_feasible( n.is_feasible() );
if( n < tmin ) {
return tmin;
} else if( n > tmax ) {
return tmax;
} else {
return n;
}
}
};