001/* 002 * Java Genetic Algorithm Library (jenetics-7.2.0). 003 * Copyright (c) 2007-2023 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 */ 020package io.jenetics; 021 022import static java.lang.Math.min; 023 024import io.jenetics.util.MSeq; 025import 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 */ 045public 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}