001 /*
002 * Java Genetic Algorithm Library (jenetics-6.3.0).
003 * Copyright (c) 2007-2021 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.String.format;
023
024 import java.util.Random;
025
026 import io.jenetics.internal.math.Combinatorics;
027 import io.jenetics.util.MSeq;
028 import io.jenetics.util.RandomRegistry;
029
030 /**
031 * The {@code PartiallyMatchedCrossover} (PMX) guarantees that all {@link Gene}s
032 * are found exactly once in each chromosome. No gene is duplicated by this
033 * crossover. The PMX can be applied usefully in the TSP or other permutation
034 * problem encodings. Permutation encoding is useful for all problems where the
035 * fitness only depends on the ordering of the genes within the chromosome. This
036 * is the case in many combinatorial optimization problems. Other crossover
037 * operators for combinatorial optimization are:
038 * <ul>
039 * <li>order crossover</li>
040 * <li>cycle crossover</li>
041 * <li>edge recombination crossover</li>
042 * <li>edge assembly crossover</li>
043 * </ul>
044 * <p>
045 * The PMX is similar to the two-point crossover. A crossing region is chosen
046 * by selecting two crossing points.
047 * <pre>
048 * C1 = 012|345|6789
049 * C2 = 987|654|3210
050 * </pre>
051 * After performing the crossover we normally got two invalid chromosomes.
052 * <pre>
053 * C1 = 012|654|6789
054 * C2 = 987|345|3210
055 * </pre>
056 * Chromosome {@code C1} contains the value 6 twice and misses the value
057 * 3. On the other side chromosome {@code C2} contains the value 3 twice and
058 * misses the value 6. We can observe that this crossover is equivalent
059 * to the exchange of the values {@code 3 -> 6}, {@code 4 -> 5} and
060 * {@code 5 -> 4}. To repair the two
061 * chromosomes we have to apply this exchange outside the crossing region.
062 * <pre>
063 * C1 = 012|654|3789
064 * C2 = 987|345|6210
065 * </pre>
066 *
067 * <em>The {@code PartiallyMatchedCrossover} class requires chromosomes with the
068 * same length. An {@code IllegalArgumentException} is thrown at runtime if this
069 * requirement is not fulfilled.</em>
070 *
071 * @see PermutationChromosome
072 *
073 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
074 * @since 1.0
075 * @version 4.4
076 */
077 public class PartiallyMatchedCrossover<T, C extends Comparable<? super C>>
078 extends Crossover<EnumGene<T>, C>
079 {
080
081 public PartiallyMatchedCrossover(final double probability) {
082 super(probability);
083 }
084
085 @Override
086 protected int crossover(
087 final MSeq<EnumGene<T>> that,
088 final MSeq<EnumGene<T>> other
089 ) {
090 if (that.length() != other.length()) {
091 throw new IllegalArgumentException(format(
092 "Required chromosomes with same length: %s != %s",
093 that.length(), other.length()
094 ));
095 }
096
097 if (that.length() >= 2) {
098 final Random random = RandomRegistry.random();
099 final int[] points = Combinatorics.subset(that.length(), 2, random);
100
101 that.swap(points[0], points[1], other, points[0]);
102 repair(that, other, points[0], points[1]);
103 repair(other, that, points[0], points[1]);
104 }
105
106 return 1;
107 }
108
109 private static <T> void repair(
110 final MSeq<T> that, final MSeq<T> other,
111 final int begin, final int end
112 ) {
113 for (int i = 0; i < begin; ++i) {
114 int index = that.indexOf(that.get(i), begin, end);
115 while (index != -1) {
116 that.set(i, other.get(index));
117 index = that.indexOf(that.get(i), begin, end);
118 }
119 }
120 for (int i = end, n = that.length(); i < n; ++i) {
121 int index = that.indexOf(that.get(i), begin, end);
122 while (index != -1) {
123 that.set(i, other.get(index));
124 index = that.indexOf(that.get(i), begin, end);
125 }
126 }
127 }
128
129 @Override
130 public String toString() {
131 return format("%s[p=%f]", getClass().getSimpleName(), _probability);
132 }
133
134 }
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