/*  * Encog Neural Network and Bot Library for Java  * http://www.heatonresearch.com/encog/  * http://code.google.com/p/encog-java/  *   * Copyright 2008, Heaton Research Inc., and individual contributors.  * See the copyright.txt in the distribution for a full listing of   * individual contributors.  *  * This 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 2.1 of  * the License, or (at your option) any later version.  *  * This software 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 software; if not, write to the Free  * Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  * 02110-1301 USA, or see the FSF site: http://www.fsf.org.  */package org.encog.examples.nonlinear.tsp.genetic;import org.encog.examples.nonlinear.tsp.City;import org.encog.neural.NeuralNetworkError;import org.encog.solve.genetic.GeneticAlgorithm;/** * Chapter 6: Training using a Genetic Algorithm *  * TSPGeneticAlgorithm: An implementation of the genetic algorithm that * attempts to solve the traveling salesman problem. *  * @author Jeff Heaton * @version 2.1 */public class TSPGeneticAlgorithm extends GeneticAlgorithm<Integer> {	public TSPGeneticAlgorithm(final City cities[], final int populationSize,			final double mutationPercent, final double percentToMate,			final double matingPopulationPercent, final int cutLength)			throws NeuralNetworkError {		this.setMutationPercent(mutationPercent);		this.setMatingPopulation(matingPopulationPercent);		this.setPopulationSize(populationSize);		this.setPercentToMate(percentToMate);		this.setCutLength(cutLength);		this.setPreventRepeat(true);		setChromosomes(new TSPChromosome[getPopulationSize()]);		for (int i = 0; i < getChromosomes().length; i++) {			final TSPChromosome c = new TSPChromosome(this, cities);			setChromosome(i, c);		}		sortChromosomes();	}}