/*
* JENES
* A time and memory efficient Java library for genetic algorithms and more
* Copyright (C) 2011 Intelligentia srl
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU 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 General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package jenes.tutorials.problem3;
import jenes.Fitness;
import jenes.GeneticAlgorithm;
import jenes.utils.Random;
import jenes.chromosome.IntegerChromosome;
import jenes.population.Individual;
import jenes.population.Population;
/**
* Tutorial showing how to implement problem specific operators.
* The problem faced in this example is the well known Tavel Salesman Problem (TSP)
*
* This class implements the algorithm.
*
* @author Luigi Troiano
*
* @version 1.0
* @since 1.0
*/
public class TSPGA extends GeneticAlgorithm<IntegerChromosome> {
private double[][] matrix;
private TSPFitness fitness;
public TSPGA(double[][] matrix, Population<IntegerChromosome> pop, int genlimit) {
super(null, pop, genlimit);
this.matrix = matrix;
fitness = new TSPFitness();
this.setFitness(fitness);
}
@Override
protected void randomizeIndividual(Individual<IntegerChromosome> individual) {
Random rand = Random.getInstance();
int len = individual.getChromosomeLength();
for( int i = 0; i < 100; ++i ) {
int j = rand.nextInt(len);
int k = rand.nextInt(len);
individual.getChromosome().swap(j, k);
}
}
public class TSPFitness extends Fitness<IntegerChromosome> {
public TSPFitness() {
super(false);
}
@Override
public void evaluate(Individual<IntegerChromosome> individual) {
IntegerChromosome chrom = individual.getChromosome();
double count = 0;
int size = chrom.length();
for (int i = 0; i < size - 1; i++) {
int val1 = chrom.getValue(i);
int val2 = chrom.getValue(i + 1);
count += matrix[val1][val2];
}
count += matrix[size - 1][0];
individual.setScore(count);
}
}
}
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