Crossover.java
/*
* Java Genetic Algorithm Library (@__identifier__@).
* Copyright (c) @__year__@ Franz Wilhelmstötter
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* Author:
* Franz Wilhelmstötter (franz.wilhelmstoetter@gmx.at)
*/
package org.jenetics;
import java.util.Random;
import org.jenetics.util.MSeq;
import org.jenetics.util.RandomRegistry;
/**
* <p>
* Performs a <a href="http://en.wikipedia.org/wiki/Crossover_%28genetic_algorithm%29">
* Crossover</a> of two {@link Chromosome}.
* </p>
* <p>
* The order ({@link #getOrder()}) of this Recombination implementation is two.
* </p>
*
* @param <G> the gene type.
*
* @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
* @since 1.0
* @version 1.0 — <em>$Date: 2014-02-15 $</em>
*/
public abstract class Crossover<G extends Gene<?, G>> extends Recombinator<G> {
/**
* Constructs an alterer with a given recombination probability.
*
* @param probability The recombination probability.
* @throws IllegalArgumentException if the {@code probability} is not in the
* valid range of {@code [0, 1]}.
*/
protected Crossover(final double probability) {
super(probability, 2);
}
@Override
protected final <C extends Comparable<? super C>> int recombine(
final Population<G, C> population,
final int[] individuals,
final int generation
) {
final Random random = RandomRegistry.getRandom();
final Phenotype<G, C> pt1 = population.get(individuals[0]);
final Phenotype<G, C> pt2 = population.get(individuals[1]);
final Genotype<G> gt1 = pt1.getGenotype();
final Genotype<G> gt2 = pt2.getGenotype();
//Choosing the Chromosome for crossover.
final int chIndex = random.nextInt(gt1.length());
final MSeq<Chromosome<G>> chroms1 = gt1.toSeq().copy();
final MSeq<Chromosome<G>> chroms2 = gt2.toSeq().copy();
final MSeq<G> genes1 = chroms1.get(chIndex).toSeq().copy();
final MSeq<G> genes2 = chroms2.get(chIndex).toSeq().copy();
crossover(genes1, genes2);
chroms1.set(chIndex, chroms1.get(chIndex).newInstance(genes1.toISeq()));
chroms2.set(chIndex, chroms2.get(chIndex).newInstance(genes2.toISeq()));
//Creating two new Phenotypes and exchanging it with the old.
population.set(
individuals[0],
pt1.newInstance(gt1.newInstance(chroms1.toISeq()), generation)
);
population.set(
individuals[1],
pt2.newInstance(gt1.newInstance(chroms2.toISeq()), generation)
);
return getOrder();
}
/**
* Template method which performs the crossover. The arguments given are
* mutable non null arrays of the same length.
*/
protected abstract int crossover(final MSeq<G> that, final MSeq<G> other);
}