001 /*
002 * Java Genetic Algorithm Library (jenetics-3.0.0).
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 3.0 — <em>$Date: 2014-12-28 $</em>
041 */
042 public abstract class Crossover<
043 G extends Gene<?, G>,
044 C extends Comparable<? super C>
045 >
046 extends Recombinator<G, C>
047 {
048
049 /**
050 * Constructs an alterer with a given recombination probability.
051 *
052 * @param probability The recombination probability.
053 * @throws IllegalArgumentException if the {@code probability} is not in the
054 * valid range of {@code [0, 1]}.
055 */
056 protected Crossover(final double probability) {
057 super(probability, 2);
058 }
059
060 @Override
061 protected final int recombine(
062 final Population<G, C> population,
063 final int[] individuals,
064 final long generation
065 ) {
066 final Random random = RandomRegistry.getRandom();
067
068 final Phenotype<G, C> pt1 = population.get(individuals[0]);
069 final Phenotype<G, C> pt2 = population.get(individuals[1]);
070 final Genotype<G> gt1 = pt1.getGenotype();
071 final Genotype<G> gt2 = pt2.getGenotype();
072
073 //Choosing the Chromosome for crossover.
074 final int chIndex = random.nextInt(gt1.length());
075
076 final MSeq<Chromosome<G>> c1 = gt1.toSeq().copy();
077 final MSeq<Chromosome<G>> c2 = gt2.toSeq().copy();
078 final MSeq<G> genes1 = c1.get(chIndex).toSeq().copy();
079 final MSeq<G> genes2 = c2.get(chIndex).toSeq().copy();
080
081 crossover(genes1, genes2);
082
083 c1.set(chIndex, c1.get(chIndex).newInstance(genes1.toISeq()));
084 c2.set(chIndex, c2.get(chIndex).newInstance(genes2.toISeq()));
085
086 //Creating two new Phenotypes and exchanging it with the old.
087 population.set(
088 individuals[0],
089 pt1.newInstance(gt1.newInstance(c1.toISeq()), generation)
090 );
091 population.set(
092 individuals[1],
093 pt2.newInstance(gt1.newInstance(c2.toISeq()), generation)
094 );
095
096 return getOrder();
097 }
098
099
100 /**
101 * Template method which performs the crossover. The arguments given are
102 * mutable non null arrays of the same length.
103 *
104 * @param that the genes of the first chromosome
105 * @param other the genes of the other chromosome
106 * @return the number of altered genes
107 */
108 protected abstract int crossover(final MSeq<G> that, final MSeq<G> other);
109
110
111 }
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