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fast computation of dominance-depth corrected for minimizing objectives

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This commit is contained in:
liefooga 2013-06-25 16:28:25 +02:00
commit 6fc4d043e0
2 changed files with 22 additions and 4 deletions
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16
moeo/src/fitness/moeoDominanceDepthFitnessAssignment.h
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@ -155,7 +155,10 @@ private:
*/
bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
return cmp(_moeo2.objectiveVector(), _moeo1.objectiveVector());
if (MOEOT::ObjectiveVector::maximizing(0))
return cmp(_moeo2.objectiveVector(), _moeo1.objectiveVector());
else
return cmp(_moeo1.objectiveVector(), _moeo2.objectiveVector());
}
private:
/** the corresponding comparator for objective vectors */
@ -207,6 +210,17 @@ private:
moeoPtrComparator<MOEOT> cmp(objComparator);
std::sort(sortedptrpop.begin(), sortedptrpop.end(), cmp);
//
std::cout << std::endl << "sorted pop" << std::endl;
std::cout << "====================" << std::endl;
for(unsigned int i=0; i<_pop.size(); i++)
{
std::cout << i << " : " << (*sortedptrpop[i]) << std::endl;
}
std::cout << "====================" << std::endl;
//
// compute an upper bound on the second objective (1)
double max_obj1 = std::numeric_limits<double>::min();
for(unsigned int i=0; i<_pop.size(); i++)