1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17 package org.apache.commons.math4.legacy.genetics;
18
19 import java.util.ArrayList;
20 import java.util.List;
21
22 import org.apache.commons.math4.legacy.exception.DimensionMismatchException;
23 import org.apache.commons.math4.legacy.exception.MathIllegalArgumentException;
24 import org.apache.commons.math4.legacy.exception.NotStrictlyPositiveException;
25 import org.apache.commons.math4.legacy.exception.NumberIsTooLargeException;
26 import org.apache.commons.math4.legacy.exception.util.LocalizedFormats;
27 import org.apache.commons.rng.UniformRandomProvider;
28
29 /**
30 * N-point crossover policy. For each iteration a random crossover point is
31 * selected and the first part from each parent is copied to the corresponding
32 * child, and the second parts are copied crosswise.
33 *
34 * Example (2-point crossover):
35 * <pre>
36 * -C- denotes a crossover point
37 * -C- -C- -C- -C-
38 * p1 = (1 0 | 1 0 0 1 | 0 1 1) X p2 = (0 1 | 1 0 1 0 | 1 1 1)
39 * \----/ \-------/ \-----/ \----/ \--------/ \-----/
40 * || (*) || || (**) ||
41 * VV (**) VV VV (*) VV
42 * /----\ /--------\ /-----\ /----\ /--------\ /-----\
43 * c1 = (1 0 | 1 0 1 0 | 0 1 1) X c2 = (0 1 | 1 0 0 1 | 0 1 1)
44 * </pre>
45 *
46 * This policy works only on {@link AbstractListChromosome}, and therefore it
47 * is parameterized by T. Moreover, the chromosomes must have same lengths.
48 *
49 * @param <T> generic type of the {@link AbstractListChromosome}s for crossover
50 * @since 3.1
51 */
52 public class NPointCrossover<T> implements CrossoverPolicy {
53
54 /** The number of crossover points. */
55 private final int crossoverPoints;
56
57 /**
58 * Creates a new {@link NPointCrossover} policy using the given number of points.
59 * <p>
60 * <b>Note</b>: the number of crossover points must be < <code>chromosome length - 1</code>.
61 * This condition can only be checked at runtime, as the chromosome length is not known in advance.
62 *
63 * @param crossoverPoints the number of crossover points
64 * @throws NotStrictlyPositiveException if the number of {@code crossoverPoints} is not strictly positive
65 */
66 public NPointCrossover(final int crossoverPoints) throws NotStrictlyPositiveException {
67 if (crossoverPoints <= 0) {
68 throw new NotStrictlyPositiveException(crossoverPoints);
69 }
70 this.crossoverPoints = crossoverPoints;
71 }
72
73 /**
74 * Returns the number of crossover points used by this {@link CrossoverPolicy}.
75 *
76 * @return the number of crossover points
77 */
78 public int getCrossoverPoints() {
79 return crossoverPoints;
80 }
81
82 /**
83 * Performs a N-point crossover. N random crossover points are selected and are used
84 * to divide the parent chromosomes into segments. The segments are copied in alternate
85 * order from the two parents to the corresponding child chromosomes.
86 *
87 * Example (2-point crossover):
88 * <pre>
89 * -C- denotes a crossover point
90 * -C- -C- -C- -C-
91 * p1 = (1 0 | 1 0 0 1 | 0 1 1) X p2 = (0 1 | 1 0 1 0 | 1 1 1)
92 * \----/ \-------/ \-----/ \----/ \--------/ \-----/
93 * || (*) || || (**) ||
94 * VV (**) VV VV (*) VV
95 * /----\ /--------\ /-----\ /----\ /--------\ /-----\
96 * c1 = (1 0 | 1 0 1 0 | 0 1 1) X c2 = (0 1 | 1 0 0 1 | 0 1 1)
97 * </pre>
98 *
99 * @param first first parent (p1)
100 * @param second second parent (p2)
101 * @return pair of two children (c1,c2)
102 * @throws MathIllegalArgumentException iff one of the chromosomes is
103 * not an instance of {@link AbstractListChromosome}
104 * @throws DimensionMismatchException if the length of the two chromosomes is different
105 */
106 @Override
107 @SuppressWarnings("unchecked") // OK because of instanceof checks
108 public ChromosomePair crossover(final Chromosome first, final Chromosome second)
109 throws DimensionMismatchException, MathIllegalArgumentException {
110
111 if (!(first instanceof AbstractListChromosome<?> && second instanceof AbstractListChromosome<?>)) {
112 throw new MathIllegalArgumentException(LocalizedFormats.INVALID_FIXED_LENGTH_CHROMOSOME);
113 }
114 return mate((AbstractListChromosome<T>) first, (AbstractListChromosome<T>) second);
115 }
116
117 /**
118 * Helper for {@link #crossover(Chromosome, Chromosome)}. Performs the actual crossover.
119 *
120 * @param first the first chromosome
121 * @param second the second chromosome
122 * @return the pair of new chromosomes that resulted from the crossover
123 * @throws DimensionMismatchException if the length of the two chromosomes is different
124 * @throws NumberIsTooLargeException if the number of crossoverPoints is too large for the actual chromosomes
125 */
126 private ChromosomePair mate(final AbstractListChromosome<T> first,
127 final AbstractListChromosome<T> second)
128 throws DimensionMismatchException, NumberIsTooLargeException {
129
130 final int length = first.getLength();
131 if (length != second.getLength()) {
132 throw new DimensionMismatchException(second.getLength(), length);
133 }
134 if (crossoverPoints >= length) {
135 throw new NumberIsTooLargeException(crossoverPoints, length, false);
136 }
137
138 // array representations of the parents
139 final List<T> parent1Rep = first.getRepresentation();
140 final List<T> parent2Rep = second.getRepresentation();
141 // and of the children
142 final List<T> child1Rep = new ArrayList<>(length);
143 final List<T> child2Rep = new ArrayList<>(length);
144
145 final UniformRandomProvider random = GeneticAlgorithm.getRandomGenerator();
146
147 List<T> c1 = child1Rep;
148 List<T> c2 = child2Rep;
149
150 int remainingPoints = crossoverPoints;
151 int lastIndex = 0;
152 for (int i = 0; i < crossoverPoints; i++, remainingPoints--) {
153 // select the next crossover point at random
154 final int crossoverIndex = 1 + lastIndex + random.nextInt(length - lastIndex - remainingPoints);
155
156 // copy the current segment
157 for (int j = lastIndex; j < crossoverIndex; j++) {
158 c1.add(parent1Rep.get(j));
159 c2.add(parent2Rep.get(j));
160 }
161
162 // swap the children for the next segment
163 List<T> tmp = c1;
164 c1 = c2;
165 c2 = tmp;
166
167 lastIndex = crossoverIndex;
168 }
169
170 // copy the last segment
171 for (int j = lastIndex; j < length; j++) {
172 c1.add(parent1Rep.get(j));
173 c2.add(parent2Rep.get(j));
174 }
175
176 return new ChromosomePair(first.newFixedLengthChromosome(child1Rep),
177 second.newFixedLengthChromosome(child2Rep));
178 }
179 }