001 /*
002 * Java Genetic Algorithm Library (jenetics-8.0.0).
003 * Copyright (c) 2007-2024 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@gmail.com)
019 */
020 package io.jenetics;
021
022 import static java.lang.Math.min;
023
024 import io.jenetics.util.MSeq;
025 import io.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}. This crossover implementation can
031 * handle genotypes with different length (different number of chromosomes). It
032 * is guaranteed that chromosomes with the the same (genotype) index are chosen
033 * for <em>crossover</em>.
034 * </p>
035 * <p>
036 * The order ({@link #order()}) of this Recombination implementation is two.
037 * </p>
038 *
039 * @param <G> the gene type.
040 *
041 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
042 * @since 1.0
043 * @version 4.0
044 */
045 public abstract class Crossover<
046 G extends Gene<?, G>,
047 C extends Comparable<? super C>
048 >
049 extends Recombinator<G, C>
050 {
051
052 /**
053 * Constructs an alterer with a given recombination probability.
054 *
055 * @param probability the recombination probability
056 * @throws IllegalArgumentException if the {@code probability} is not in the
057 * valid range of {@code [0, 1]}
058 */
059 protected Crossover(final double probability) {
060 super(probability, 2);
061 }
062
063 @Override
064 protected final int recombine(
065 final MSeq<Phenotype<G, C>> population,
066 final int[] individuals,
067 final long generation
068 ) {
069 assert individuals.length == 2 : "Required order of 2";
070
071 final var pt1 = population.get(individuals[0]);
072 final var pt2 = population.get(individuals[1]);
073 final var gt1 = pt1.genotype();
074 final var gt2 = pt2.genotype();
075
076 //Choosing the Chromosome index for crossover.
077 final int chIndex = RandomRegistry.random()
078 .nextInt(min(gt1.length(), gt2.length()));
079
080 final var c1 = MSeq.of(gt1);
081 final var c2 = MSeq.of(gt2);
082 final var genes1 = MSeq.of(c1.get(chIndex));
083 final var genes2 = MSeq.of(c2.get(chIndex));
084
085 crossover(genes1, genes2);
086
087 c1.set(chIndex, c1.get(chIndex).newInstance(genes1.toISeq()));
088 c2.set(chIndex, c2.get(chIndex).newInstance(genes2.toISeq()));
089
090 //Creating two new Phenotypes and exchanging it with the old.
091 population.set(
092 individuals[0],
093 Phenotype.of(Genotype.of(c1), generation)
094 );
095 population.set(
096 individuals[1],
097 Phenotype.of(Genotype.of(c2), generation)
098 );
099
100 return order();
101 }
102
103 /**
104 * Template method which performs the crossover. The arguments given are
105 * mutable non-null arrays of the same length.
106 *
107 * @param that the genes of the first chromosome
108 * @param other the genes of the other chromosome
109 * @return the number of altered genes
110 */
111 protected abstract int crossover(final MSeq<G> that, final MSeq<G> other);
112
113 }
|