org.jenetics.Crossover Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of org.jenetics Show documentation
Jenetics - Java Genetic Algorithm Library
There is a newer version: 3.6.0
/*
 * Java Genetic Algorithm Library (jenetics-3.4.0).
 * Copyright (c) 2007-2016 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 ([email protected])
 */
package org.jenetics;

import java.util.Random;

import org.jenetics.util.MSeq;
import org.jenetics.util.RandomRegistry;

/**
 * 
 * Performs a 
 * Crossover of two {@link Chromosome}.
 * 
 * 
 * The order ({@link #getOrder()}) of this Recombination implementation is two.
 * 
 *
 * @param  the gene type.
 *
 * @author Franz Wilhelmstötter
 * @since 1.0
 * @version 3.0
 */
public abstract class Crossover<
	G extends Gene,
	C extends Comparable
>
	extends Recombinator
{

	/**
	 * 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 int recombine(
		final Population population,
		final int[] individuals,
		final long generation
	) {
		final Random random = RandomRegistry.getRandom();

		final Phenotype pt1 = population.get(individuals[0]);
		final Phenotype pt2 = population.get(individuals[1]);
		final Genotype gt1 = pt1.getGenotype();
		final Genotype gt2 = pt2.getGenotype();

		//Choosing the Chromosome for crossover.
		final int chIndex = random.nextInt(gt1.length());

		final MSeq> c1 = gt1.toSeq().copy();
		final MSeq> c2 = gt2.toSeq().copy();
		final MSeq genes1 = c1.get(chIndex).toSeq().copy();
		final MSeq genes2 = c2.get(chIndex).toSeq().copy();

		crossover(genes1, genes2);

		c1.set(chIndex, c1.get(chIndex).newInstance(genes1.toISeq()));
		c2.set(chIndex, c2.get(chIndex).newInstance(genes2.toISeq()));

		//Creating two new Phenotypes and exchanging it with the old.
		population.set(
			individuals[0],
			pt1.newInstance(gt1.newInstance(c1.toISeq()), generation)
		);
		population.set(
			individuals[1],
			pt2.newInstance(gt1.newInstance(c2.toISeq()), generation)
		);

		return getOrder();
	}


	/**
	 * Template method which performs the crossover. The arguments given are
	 * mutable non null arrays of the same length.
	 *
	 * @param that the genes of the first chromosome
	 * @param other the genes of the other chromosome
	 * @return the number of altered genes
	 */
	protected abstract int crossover(final MSeq that, final MSeq other);


}