source: src/main/java/agents/anac/y2019/harddealer/math3/genetics/CycleCrossover.java

Last change on this file was 204, checked in by Katsuhide Fujita, 5 years ago

Fixed errors of ANAC2019 agents

  • Property svn:executable set to *
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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 */
17package agents.anac.y2019.harddealer.math3.genetics;
18
19import java.util.ArrayList;
20import java.util.HashSet;
21import java.util.List;
22import java.util.Set;
23
24import agents.anac.y2019.harddealer.math3.exception.DimensionMismatchException;
25import agents.anac.y2019.harddealer.math3.exception.MathIllegalArgumentException;
26import agents.anac.y2019.harddealer.math3.exception.util.LocalizedFormats;
27
28/**
29 * Cycle Crossover [CX] builds offspring from <b>ordered</b> chromosomes by identifying cycles
30 * between two parent chromosomes. To form the children, the cycles are copied from the
31 * respective parents.
32 * <p>
33 * To form a cycle the following procedure is applied:
34 * <ol>
35 * <li>start with the first gene of parent 1</li>
36 * <li>look at the gene at the same position of parent 2</li>
37 * <li>go to the position with the same gene in parent 1</li>
38 * <li>add this gene index to the cycle</li>
39 * <li>repeat the steps 2-5 until we arrive at the starting gene of this cycle</li>
40 * </ol>
41 * The indices that form a cycle are then used to form the children in alternating order, i.e.
42 * in cycle 1, the genes of parent 1 are copied to child 1, while in cycle 2 the genes of parent 1
43 * are copied to child 2, and so forth ...
44 * </p>
45 *
46 * Example (zero-start cycle):
47 * <pre>
48 * p1 = (8 4 7 3 6 2 5 1 9 0) X c1 = (8 1 2 3 4 5 6 7 9 0)
49 * p2 = (0 1 2 3 4 5 6 7 8 9) X c2 = (0 4 7 3 6 2 5 1 8 9)
50 *
51 * cycle 1: 8 0 9
52 * cycle 2: 4 1 7 2 5 6
53 * cycle 3: 3
54 * </pre>
55 *
56 * This policy works only on {@link AbstractListChromosome}, and therefore it
57 * is parameterized by T. Moreover, the chromosomes must have same lengths.
58 *
59 * @see <a href="http://www.rubicite.com/Tutorials/GeneticAlgorithms/CrossoverOperators/CycleCrossoverOperator.aspx">
60 * Cycle Crossover Operator</a>
61 *
62 * @param <T> generic type of the {@link AbstractListChromosome}s for crossover
63 * @since 3.1
64 */
65public class CycleCrossover<T> implements CrossoverPolicy {
66
67 /** If the start index shall be chosen randomly. */
68 private final boolean randomStart;
69
70 /**
71 * Creates a new {@link CycleCrossover} policy.
72 */
73 public CycleCrossover() {
74 this(false);
75 }
76
77 /**
78 * Creates a new {@link CycleCrossover} policy using the given {@code randomStart} behavior.
79 *
80 * @param randomStart whether the start index shall be chosen randomly or be set to 0
81 */
82 public CycleCrossover(final boolean randomStart) {
83 this.randomStart = randomStart;
84 }
85
86 /**
87 * Returns whether the starting index is chosen randomly or set to zero.
88 *
89 * @return {@code true} if the starting index is chosen randomly, {@code false} otherwise
90 */
91 public boolean isRandomStart() {
92 return randomStart;
93 }
94
95 /**
96 * {@inheritDoc}
97 *
98 * @throws MathIllegalArgumentException if the chromosomes are not an instance of {@link AbstractListChromosome}
99 * @throws DimensionMismatchException if the length of the two chromosomes is different
100 */
101 @SuppressWarnings("unchecked")
102 public ChromosomePair crossover(final Chromosome first, final Chromosome second)
103 throws DimensionMismatchException, MathIllegalArgumentException {
104
105 if (!(first instanceof AbstractListChromosome<?> && second instanceof AbstractListChromosome<?>)) {
106 throw new MathIllegalArgumentException(LocalizedFormats.INVALID_FIXED_LENGTH_CHROMOSOME);
107 }
108 return mate((AbstractListChromosome<T>) first, (AbstractListChromosome<T>) second);
109 }
110
111 /**
112 * Helper for {@link #crossover(Chromosome, Chromosome)}. Performs the actual crossover.
113 *
114 * @param first the first chromosome
115 * @param second the second chromosome
116 * @return the pair of new chromosomes that resulted from the crossover
117 * @throws DimensionMismatchException if the length of the two chromosomes is different
118 */
119 protected ChromosomePair mate(final AbstractListChromosome<T> first, final AbstractListChromosome<T> second)
120 throws DimensionMismatchException {
121
122 final int length = first.getLength();
123 if (length != second.getLength()) {
124 throw new DimensionMismatchException(second.getLength(), length);
125 }
126
127 // array representations of the parents
128 final List<T> parent1Rep = first.getRepresentation();
129 final List<T> parent2Rep = second.getRepresentation();
130 // and of the children: do a crossover copy to simplify the later processing
131 final List<T> child1Rep = new ArrayList<T>(second.getRepresentation());
132 final List<T> child2Rep = new ArrayList<T>(first.getRepresentation());
133
134 // the set of all visited indices so far
135 final Set<Integer> visitedIndices = new HashSet<Integer>(length);
136 // the indices of the current cycle
137 final List<Integer> indices = new ArrayList<Integer>(length);
138
139 // determine the starting index
140 int idx = randomStart ? GeneticAlgorithm.getRandomGenerator().nextInt(length) : 0;
141 int cycle = 1;
142
143 while (visitedIndices.size() < length) {
144 indices.add(idx);
145
146 T item = parent2Rep.get(idx);
147 idx = parent1Rep.indexOf(item);
148
149 while (idx != indices.get(0)) {
150 // add that index to the cycle indices
151 indices.add(idx);
152 // get the item in the second parent at that index
153 item = parent2Rep.get(idx);
154 // get the index of that item in the first parent
155 idx = parent1Rep.indexOf(item);
156 }
157
158 // for even cycles: swap the child elements on the indices found in this cycle
159 if (cycle++ % 2 != 0) {
160 for (int i : indices) {
161 T tmp = child1Rep.get(i);
162 child1Rep.set(i, child2Rep.get(i));
163 child2Rep.set(i, tmp);
164 }
165 }
166
167 visitedIndices.addAll(indices);
168 // find next starting index: last one + 1 until we find an unvisited index
169 idx = (indices.get(0) + 1) % length;
170 while (visitedIndices.contains(idx) && visitedIndices.size() < length) {
171 idx++;
172 if (idx >= length) {
173 idx = 0;
174 }
175 }
176 indices.clear();
177 }
178
179 return new ChromosomePair(first.newFixedLengthChromosome(child1Rep),
180 second.newFixedLengthChromosome(child2Rep));
181 }
182}
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