bug corrected
git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@294 331e1502-861f-0410-8da2-ba01fb791d7f
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1 changed files with 73 additions and 17 deletions
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@ -40,6 +40,15 @@ public:
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}
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}
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/**
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* Returns a very small value that can be used to avoid extreme cases (where the min bound == the max bound)
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*/
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double tiny() const
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{
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return 1e-6;
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}
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/**
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/**
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* Computes diversity values for every solution contained in the population _pop
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* Computes diversity values for every solution contained in the population _pop
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* @param _pop the population
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* @param _pop the population
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@ -81,33 +90,80 @@ private:
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*/
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*/
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void setDistances (eoPop < MOEOT > & _pop)
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void setDistances (eoPop < MOEOT > & _pop)
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{
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{
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unsigned a,b;
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double min, max, distance;
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double min, max, distance;
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unsigned nObjectives = MOEOT::ObjectiveVector::nObjectives();
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unsigned nObjectives = MOEOT::ObjectiveVector::nObjectives();
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// set diversity to 0
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// set diversity to 0 for every individual
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for (unsigned i=0; i<_pop.size(); i++)
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for (unsigned i=0; i<_pop.size(); i++)
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{
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{
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_pop[i].diversity(0);
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_pop[i].diversity(0.0);
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}
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}
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// sort the whole pop according to fitness values
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moeoFitnessThenDiversityComparator < MOEOT > fitnessComparator;
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std::sort(_pop.begin(), _pop.end(), fitnessComparator);
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// compute the crowding distance values for every individual "front" by "front" (front : from a to b)
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a = 0; // the front starts at a
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while (a < _pop.size())
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{
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b = lastIndex(_pop,a); // the front ends at b
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// if there is 2 or less individuals in the front...
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if ((b-a) < 2)
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{
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for (unsigned i=a; i<=b; i++)
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{
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_pop[i].diversity(inf());
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}
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}
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// else...
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else
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{
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// for each objective
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// for each objective
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for (unsigned obj=0; obj<nObjectives; obj++)
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for (unsigned obj=0; obj<nObjectives; obj++)
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{
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{
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// comparator
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// sort in the descending order using the values of the objective 'obj'
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moeoOneObjectiveComparator < MOEOT > comp(obj);
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moeoOneObjectiveComparator < MOEOT > objComp(obj);
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// sort
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std::sort(_pop.begin()+a, _pop.begin()+b+1, objComp);
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std::sort(_pop.begin(), _pop.end(), comp);
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// min & max
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// min & max
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min = _pop[0].objectiveVector()[obj];
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min = _pop[b].objectiveVector()[obj];
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max = _pop[_pop.size()-1].objectiveVector()[obj];
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max = _pop[a].objectiveVector()[obj];
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// set the diversity value to infiny for min and max
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// avoid extreme case
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_pop[0].diversity(inf());
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if (min == max)
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_pop[_pop.size()-1].diversity(inf());
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for (unsigned i=1; i<_pop.size()-1; i++)
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{
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{
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distance = (_pop[i+1].objectiveVector()[obj] - _pop[i-1].objectiveVector()[obj]) / (max-min);
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min -= tiny();
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max += tiny();
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}
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// set the diversity value to infiny for min and max
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_pop[a].diversity(inf());
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_pop[b].diversity(inf());
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// set the diversity values for the other individuals
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for (unsigned i=a+1; i<b; i++)
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{
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distance = (_pop[i-1].objectiveVector()[obj] - _pop[i+1].objectiveVector()[obj]) / (max-min);
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_pop[i].diversity(_pop[i].diversity() + distance);
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_pop[i].diversity(_pop[i].diversity() + distance);
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}
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}
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}
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}
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}
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}
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// go to the next front
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a = b+1;
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}
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}
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/**
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* Returns the index of the last individual having the same fitness value than _pop[_start]
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* @param _pop the population
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* @param _start the index to start from
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*/
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unsigned lastIndex (eoPop < MOEOT > & _pop, unsigned _start)
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{
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unsigned i=_start;
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while ( (i<_pop.size()-1) && (_pop[i].fitness()==_pop[i+1].fitness()) )
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{
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i++;
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}
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return i;
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}
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};
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};
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