moeoNDSorting for NSGAII added

git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@116 331e1502-861f-0410-8da2-ba01fb791d7f
This commit is contained in:
legrand 2006-12-21 14:01:34 +00:00
commit 9da980e853

View file

@ -0,0 +1,91 @@
// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
/* -----------------------------------------------------------------------------
moeoNDSorting.h
(c) Deneche Abdelhakim, 2006
Contact: paradiseo-help@lists.gforge.inria.fr
*/
//------------------------------------------------------------------------------
#ifndef moeoNDSorting_h
#define moeoNDSorting_h
#include <cfloat>
#include <eoNDSorting.h>
# define INF 1.0e14 // DBL_MAX
/** @brief Fast Elitist Non-Dominant Sorting Genetic Algorithm
Note : This is a corrected version of the original eoNDSorting_II class
.
@see eoNDSorting_II
*/
template <class EOT>
class moeoNDSorting_II : public eoNDSorting<EOT>
{
public:
moeoNDSorting_II(bool nasty_flag_ = false) : eoNDSorting<EOT>(nasty_flag_) {}
typedef std::pair<double, unsigned> double_index_pair;
class compare_nodes
{
public :
bool operator()(const double_index_pair& a, const double_index_pair& b) const
{
return a.first < b.first;
}
};
/// _cf points into the elements that consist of the current front
std::vector<double> niche_penalty(const std::vector<unsigned>& _cf, const eoPop<EOT>& _pop)
{
typedef typename EOT::Fitness::fitness_traits traits;
unsigned i;
std::vector<double> niche_count(_cf.size(), 0.);
unsigned nObjectives = traits::nObjectives(); //_pop[_cf[0]].fitness().size();
for (unsigned o = 0; o < nObjectives; ++o)
{
std::vector<std::pair<double, unsigned> > performance(_cf.size());
for (i =0; i < _cf.size(); ++i)
{
performance[i].first = _pop[_cf[i]].fitness()[o];
performance[i].second = i;
}
std::sort(performance.begin(), performance.end(), compare_nodes()); // a lambda operator would've been nice here
// set boundary at INF (so it will get chosen over all the others
niche_count[performance[0].second] = INF;
niche_count[performance.back().second] = INF;
if (performance[0].first != performance.back().first)
{
for (i = 1; i < _cf.size()-1; ++i)
{
if (niche_count[performance[i].second] != INF)
{
niche_count[performance[i].second] += (performance[i+1].first - performance[i-1].first)/
(performance.back().first-performance[0].first);
}
}
}
}
// transform niche_count into penality
for (i = 0; i < niche_count.size(); ++i)
{
niche_count[i] = INF - niche_count[i];
}
return niche_count;
}
};
#endif