001 /*
002 * Java Genetic Algorithm Library (jenetics-1.6.0).
003 * Copyright (c) 2007-2014 Franz Wilhelmstötter
004 *
005 * Licensed under the Apache License, Version 2.0 (the "License");
006 * you may not use this file except in compliance with the License.
007 * You may obtain a copy of the License at
008 *
009 * http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 *
017 * Author:
018 * Franz Wilhelmstötter (franz.wilhelmstoetter@gmx.at)
019 */
020 package org.jenetics;
021
022 import java.util.Random;
023
024 import org.jenetics.util.MSeq;
025 import org.jenetics.util.RandomRegistry;
026
027 /**
028 * <p>
029 * Performs a <a href="http://en.wikipedia.org/wiki/Crossover_%28genetic_algorithm%29">
030 * Crossover</a> of two {@link Chromosome}.
031 * </p>
032 * <p>
033 * The order ({@link #getOrder()}) of this Recombination implementation is two.
034 * </p>
035 *
036 * @param <G> the gene type.
037 *
038 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
039 * @since 1.0
040 * @version 1.0 — <em>$Date: 2014-02-15 $</em>
041 */
042 public abstract class Crossover<G extends Gene<?, G>> extends Recombinator<G> {
043
044 /**
045 * Constructs an alterer with a given recombination probability.
046 *
047 * @param probability The recombination probability.
048 * @throws IllegalArgumentException if the {@code probability} is not in the
049 * valid range of {@code [0, 1]}.
050 */
051 protected Crossover(final double probability) {
052 super(probability, 2);
053 }
054
055 @Override
056 protected final <C extends Comparable<? super C>> int recombine(
057 final Population<G, C> population,
058 final int[] individuals,
059 final int generation
060 ) {
061 final Random random = RandomRegistry.getRandom();
062
063 final Phenotype<G, C> pt1 = population.get(individuals[0]);
064 final Phenotype<G, C> pt2 = population.get(individuals[1]);
065 final Genotype<G> gt1 = pt1.getGenotype();
066 final Genotype<G> gt2 = pt2.getGenotype();
067
068 //Choosing the Chromosome for crossover.
069 final int chIndex = random.nextInt(gt1.length());
070
071 final MSeq<Chromosome<G>> chroms1 = gt1.toSeq().copy();
072 final MSeq<Chromosome<G>> chroms2 = gt2.toSeq().copy();
073 final MSeq<G> genes1 = chroms1.get(chIndex).toSeq().copy();
074 final MSeq<G> genes2 = chroms2.get(chIndex).toSeq().copy();
075
076 crossover(genes1, genes2);
077
078 chroms1.set(chIndex, chroms1.get(chIndex).newInstance(genes1.toISeq()));
079 chroms2.set(chIndex, chroms2.get(chIndex).newInstance(genes2.toISeq()));
080
081 //Creating two new Phenotypes and exchanging it with the old.
082 population.set(
083 individuals[0],
084 pt1.newInstance(gt1.newInstance(chroms1.toISeq()), generation)
085 );
086 population.set(
087 individuals[1],
088 pt2.newInstance(gt1.newInstance(chroms2.toISeq()), generation)
089 );
090
091 return getOrder();
092 }
093
094
095 /**
096 * Template method which performs the crossover. The arguments given are
097 * mutable non null arrays of the same length.
098 */
099 protected abstract int crossover(final MSeq<G> that, final MSeq<G> other);
100
101
102 }
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