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; 023import static io.jenetics.internal.math.Randoms.indexes; 024 025import io.jenetics.internal.util.Requires; 026import io.jenetics.util.MSeq; 027import io.jenetics.util.RandomRegistry; 028 029/** 030 * The uniform crossover uses swaps single genes between two chromosomes, instead 031 * of whole ranges as in single- and multipoint crossover. 032 * <pre> {@code 033 * +---+---+---+---+---+---+---+ 034 * | 1 | 2 | 3 | 4 | 6 | 7 | 8 | 035 * +-+-+---+-+-+-+-+---+-+-+---+ 036 * | | | | swapping 037 * +-+-+---+-+-+-+-+---+-+-+---+ 038 * | a | b | c | d | e | f | g | 039 * +---+---+---+---+---+---+---+ 040 * }</pre> 041 * The probability that two genes are swapped is controlled by the 042 * <i>swap-probability</i> ({@link #swapProbability()}), whereas the 043 * probability that a given individual is selected for crossover is defined by 044 * the <i>crossover-probability</i> ({@link #probability()}). 045 * 046 * @see <a href="https://en.wikipedia.org/wiki/Crossover_(genetic_algorithm)#Uniform_crossover_and_half_uniform_crossover"> 047 * Wikipedia: Uniform crossover</a> 048 * 049 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a> 050 * @version 6.0 051 * @since 3.7 052 */ 053public class UniformCrossover< 054 G extends Gene<?, G>, 055 C extends Comparable<? super C> 056> 057 extends Crossover<G, C> 058{ 059 060 private final double _swapProbability; 061 062 /** 063 * Create a new universal crossover instance. 064 * 065 * @param crossoverProbability the recombination probability as defined in 066 * {@link Crossover#Crossover(double)}. This is the probability that 067 * a given individual is selected for crossover. 068 * @param swapProbability the probability for swapping a given gene of 069 * a chromosome 070 * @throws IllegalArgumentException if the probabilities are not in the 071 * valid range of {@code [0, 1]} 072 */ 073 public UniformCrossover( 074 final double crossoverProbability, 075 final double swapProbability 076 ) { 077 super(crossoverProbability); 078 _swapProbability = Requires.probability(swapProbability); 079 } 080 081 /** 082 * Create a new universal crossover instance. The {@code swapProbability} is 083 * set to {@link Alterer#DEFAULT_ALTER_PROBABILITY}. 084 * 085 * @param crossoverProbability the recombination probability as defined in 086 * {@link Crossover#Crossover(double)}. This is the probability that 087 * a given individual is selected for crossover. 088 * @throws IllegalArgumentException if the probabilities are not in the 089 * valid range of {@code [0, 1]} 090 */ 091 public UniformCrossover(final double crossoverProbability) { 092 this(crossoverProbability, DEFAULT_ALTER_PROBABILITY); 093 } 094 095 /** 096 * Create a new universal crossover instance. The probabilities are set to 097 * {@link Alterer#DEFAULT_ALTER_PROBABILITY}. 098 */ 099 public UniformCrossover() { 100 this(DEFAULT_ALTER_PROBABILITY, DEFAULT_ALTER_PROBABILITY); 101 } 102 103 /** 104 * Return the probability for swapping genes of a chromosome. 105 * 106 * @return the probability for swapping genes of a chromosome 107 */ 108 public double swapProbability() { 109 return _swapProbability; 110 } 111 112 @Override 113 protected int crossover(final MSeq<G> that, final MSeq<G> other) { 114 final int length = min(that.length(), other.length()); 115 return (int)indexes(RandomRegistry.random(), length, _swapProbability) 116 .peek(i -> that.swap(i, other)) 117 .count(); 118 } 119 120}