1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
|
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.math3.genetics;
import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.NumberIsTooLargeException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.random.RandomGenerator;
import java.util.ArrayList;
import java.util.List;
/**
* N-point crossover policy. For each iteration a random crossover point is selected and the first
* part from each parent is copied to the corresponding child, and the second parts are copied
* crosswise.
*
* <p>Example (2-point crossover):
*
* <pre>
* -C- denotes a crossover point
* -C- -C- -C- -C-
* p1 = (1 0 | 1 0 0 1 | 0 1 1) X p2 = (0 1 | 1 0 1 0 | 1 1 1)
* \----/ \-------/ \-----/ \----/ \--------/ \-----/
* || (*) || || (**) ||
* VV (**) VV VV (*) VV
* /----\ /--------\ /-----\ /----\ /--------\ /-----\
* c1 = (1 0 | 1 0 1 0 | 0 1 1) X c2 = (0 1 | 1 0 0 1 | 0 1 1)
* </pre>
*
* This policy works only on {@link AbstractListChromosome}, and therefore it is parameterized by T.
* Moreover, the chromosomes must have same lengths.
*
* @param <T> generic type of the {@link AbstractListChromosome}s for crossover
* @since 3.1
*/
public class NPointCrossover<T> implements CrossoverPolicy {
/** The number of crossover points. */
private final int crossoverPoints;
/**
* Creates a new {@link NPointCrossover} policy using the given number of points.
*
* <p><b>Note</b>: the number of crossover points must be < <code>chromosome length - 1
* </code>. This condition can only be checked at runtime, as the chromosome length is not known
* in advance.
*
* @param crossoverPoints the number of crossover points
* @throws NotStrictlyPositiveException if the number of {@code crossoverPoints} is not strictly
* positive
*/
public NPointCrossover(final int crossoverPoints) throws NotStrictlyPositiveException {
if (crossoverPoints <= 0) {
throw new NotStrictlyPositiveException(crossoverPoints);
}
this.crossoverPoints = crossoverPoints;
}
/**
* Returns the number of crossover points used by this {@link CrossoverPolicy}.
*
* @return the number of crossover points
*/
public int getCrossoverPoints() {
return crossoverPoints;
}
/**
* Performs a N-point crossover. N random crossover points are selected and are used to divide
* the parent chromosomes into segments. The segments are copied in alternate order from the two
* parents to the corresponding child chromosomes.
*
* <p>Example (2-point crossover):
*
* <pre>
* -C- denotes a crossover point
* -C- -C- -C- -C-
* p1 = (1 0 | 1 0 0 1 | 0 1 1) X p2 = (0 1 | 1 0 1 0 | 1 1 1)
* \----/ \-------/ \-----/ \----/ \--------/ \-----/
* || (*) || || (**) ||
* VV (**) VV VV (*) VV
* /----\ /--------\ /-----\ /----\ /--------\ /-----\
* c1 = (1 0 | 1 0 1 0 | 0 1 1) X c2 = (0 1 | 1 0 0 1 | 0 1 1)
* </pre>
*
* @param first first parent (p1)
* @param second second parent (p2)
* @return pair of two children (c1,c2)
* @throws MathIllegalArgumentException iff one of the chromosomes is not an instance of {@link
* AbstractListChromosome}
* @throws DimensionMismatchException if the length of the two chromosomes is different
*/
@SuppressWarnings("unchecked") // OK because of instanceof checks
public ChromosomePair crossover(final Chromosome first, final Chromosome second)
throws DimensionMismatchException, MathIllegalArgumentException {
if (!(first instanceof AbstractListChromosome<?>
&& second instanceof AbstractListChromosome<?>)) {
throw new MathIllegalArgumentException(
LocalizedFormats.INVALID_FIXED_LENGTH_CHROMOSOME);
}
return mate((AbstractListChromosome<T>) first, (AbstractListChromosome<T>) second);
}
/**
* Helper for {@link #crossover(Chromosome, Chromosome)}. Performs the actual crossover.
*
* @param first the first chromosome
* @param second the second chromosome
* @return the pair of new chromosomes that resulted from the crossover
* @throws DimensionMismatchException if the length of the two chromosomes is different
* @throws NumberIsTooLargeException if the number of crossoverPoints is too large for the
* actual chromosomes
*/
private ChromosomePair mate(
final AbstractListChromosome<T> first, final AbstractListChromosome<T> second)
throws DimensionMismatchException, NumberIsTooLargeException {
final int length = first.getLength();
if (length != second.getLength()) {
throw new DimensionMismatchException(second.getLength(), length);
}
if (crossoverPoints >= length) {
throw new NumberIsTooLargeException(crossoverPoints, length, false);
}
// array representations of the parents
final List<T> parent1Rep = first.getRepresentation();
final List<T> parent2Rep = second.getRepresentation();
// and of the children
final List<T> child1Rep = new ArrayList<T>(length);
final List<T> child2Rep = new ArrayList<T>(length);
final RandomGenerator random = GeneticAlgorithm.getRandomGenerator();
List<T> c1 = child1Rep;
List<T> c2 = child2Rep;
int remainingPoints = crossoverPoints;
int lastIndex = 0;
for (int i = 0; i < crossoverPoints; i++, remainingPoints--) {
// select the next crossover point at random
final int crossoverIndex =
1 + lastIndex + random.nextInt(length - lastIndex - remainingPoints);
// copy the current segment
for (int j = lastIndex; j < crossoverIndex; j++) {
c1.add(parent1Rep.get(j));
c2.add(parent2Rep.get(j));
}
// swap the children for the next segment
List<T> tmp = c1;
c1 = c2;
c2 = tmp;
lastIndex = crossoverIndex;
}
// copy the last segment
for (int j = lastIndex; j < length; j++) {
c1.add(parent1Rep.get(j));
c2.add(parent2Rep.get(j));
}
return new ChromosomePair(
first.newFixedLengthChromosome(child1Rep),
second.newFixedLengthChromosome(child2Rep));
}
}
|
