/*
* RapidMiner
*
* Copyright (C) 2001-2008 by Rapid-I and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapid-i.com
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program 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 Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see http://www.gnu.org/licenses/.
*/
package com.rapidminer.tools.math.optimization.ec.es;
import java.util.LinkedList;
import java.util.List;
import java.util.Random;
/**
* Performs tournaments with k participants. The winner of each tournament is
* added to the next population. This will be repeated until the desired
* population size is reached. The tournament size k represents the selection
* pressure. For small sizes (like 2) relatively bad individuals have a good
* chance to survive. If k reaches the population size, only the best individual
* will survive.
*
* @author Ingo Mierswa
* @version $Id: TournamentSelection.java,v 1.4 2006/04/05 08:57:26 ingomierswa
* Exp $
*/
public class TournamentSelection implements PopulationOperator {
private double popSize;
private double tournamentFraction;
private boolean keepBest = false;
private Random random;
public TournamentSelection(int popSize, double tournamentFraction, boolean keepBest, Random random) {
this.popSize = popSize;
this.keepBest = keepBest;
this.tournamentFraction = tournamentFraction;
this.random = random;
}
public void operate(Population population) {
List<Individual> newGeneration = new LinkedList<Individual>();
if (population.getNumberOfIndividuals() > 0) {
int tournamentSize = Math.max((int) Math.round(population.getNumberOfIndividuals() * tournamentFraction), 1);
if (keepBest && (population.getBestEver() != null)) {
newGeneration.add(population.getBestEver());
}
while (newGeneration.size() < this.popSize) {
Individual winner = null;
for (int k = 0; k < tournamentSize; k++) {
Individual current = population.get(random.nextInt(population.getNumberOfIndividuals()));
if ((winner == null) || (current.getFitnessValues()[0] > winner.getFitnessValues()[0]))
winner = current;
}
newGeneration.add(winner);
}
}
population.clear();
population.addAll(newGeneration);
}
}