110 lines
3.4 KiB
C++
110 lines
3.4 KiB
C++
// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
|
|
|
|
//-----------------------------------------------------------------------------
|
|
// eoStochasticUniversalSelect.h
|
|
// (c) Maarten Keijzer 2003
|
|
/*
|
|
This library is free software; you can redistribute it and/or
|
|
modify it under the terms of the GNU Lesser General Public
|
|
License as published by the Free Software Foundation; either
|
|
version 2 of the License, or (at your option) any later version.
|
|
|
|
This library is distributed in the hope that it will be useful,
|
|
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
|
|
Lesser General Public License for more details.
|
|
|
|
You should have received a copy of the GNU Lesser General Public
|
|
License along with this library; if not, write to the Free Software
|
|
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
|
|
|
|
Contact: todos@geneura.ugr.es, http://geneura.ugr.es
|
|
Marc.Schoenauer@polytechnique.fr
|
|
mkeijzer@cs.vu.nl
|
|
*/
|
|
//-----------------------------------------------------------------------------
|
|
|
|
#ifndef eoStochasticUniversalSelect_h
|
|
#define eoStochasticUniversalSelect_h
|
|
|
|
//-----------------------------------------------------------------------------
|
|
|
|
#include "utils/eoRNG.h"
|
|
#include "eoSelectOne.h"
|
|
#include "utils/selectors.h"
|
|
#include "eoPop.h"
|
|
|
|
/** eoStochasticUniversalSelect: select an individual proportional to her stored fitness
|
|
value, but in contrast with eoStochasticUniversalSelect, get rid of most finite sampling effects
|
|
by doing all selections in one go, using a single random number.
|
|
|
|
@ingroup Selectors
|
|
*/
|
|
template <class EOT> class eoStochasticUniversalSelect: public eoSelectOne<EOT>
|
|
{
|
|
public:
|
|
/// Sanity check
|
|
eoStochasticUniversalSelect(/*const eoPop<EOT>& pop = eoPop<EOT>()*/)
|
|
{
|
|
if (minimizing_fitness<EOT>())
|
|
throw eoException("eoStochasticUniversalSelect: minimizing fitness");
|
|
}
|
|
|
|
void setup(const eoPop<EOT>& _pop)
|
|
{
|
|
if (_pop.size() == 0) return;
|
|
|
|
std::vector<typename EOT::Fitness> cumulative(_pop.size());
|
|
|
|
cumulative[0] = _pop[0].fitness();
|
|
for (unsigned i = 1; i < _pop.size(); ++i)
|
|
{
|
|
cumulative[i] = _pop[i].fitness() + cumulative[i-1];
|
|
}
|
|
|
|
indices.reserve(_pop.size());
|
|
indices.resize(0);
|
|
|
|
double fortune = rng.uniform() * cumulative.back();
|
|
double step = cumulative.back() / double(_pop.size());
|
|
|
|
unsigned i = std::upper_bound(cumulative.begin(), cumulative.end(), fortune) - cumulative.begin();
|
|
|
|
while (indices.size() < _pop.size()) {
|
|
|
|
while (cumulative[i] < fortune) {i++;} // linear search is good enough as we average one step each time
|
|
|
|
indices.push_back(i);
|
|
fortune += step;
|
|
if (fortune >= cumulative.back()) { // start at the beginning
|
|
fortune -= cumulative.back();
|
|
i = 0;
|
|
}
|
|
}
|
|
// shuffle
|
|
for (int i = indices.size() - 1; i > 0; --i) {
|
|
int j = rng.random(i+1);
|
|
std::swap(indices[i], indices[j]);
|
|
}
|
|
}
|
|
|
|
/** do the selection,
|
|
*/
|
|
const EOT& operator()(const eoPop<EOT>& _pop)
|
|
{
|
|
if (indices.empty()) setup(_pop);
|
|
|
|
unsigned index = indices.back();
|
|
indices.pop_back();
|
|
return _pop[index];
|
|
}
|
|
|
|
private :
|
|
|
|
typedef std::vector<unsigned> IndexVec;
|
|
IndexVec indices;
|
|
};
|
|
/** @example t-eoRoulette.cpp
|
|
*/
|
|
|
|
#endif
|