001 /*
002 * Java Genetic Algorithm Library (jenetics-1.6.0).
003 * Copyright (c) 2007-2014 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@gmx.at)
019 */
020 package org.jenetics;
021
022 import static java.lang.String.format;
023 import static java.util.Objects.requireNonNull;
024
025 import java.util.Random;
026
027 import org.jenetics.internal.util.HashBuilder;
028
029 import org.jenetics.util.Factory;
030 import org.jenetics.util.RandomRegistry;
031
032 /**
033 * In tournament selection the best individual from a random sample of <i>s</i>
034 * individuals is chosen from the population <i>P<sub>g</sub></i>. The samples
035 * are drawn with replacement. An individual will win a tournament only if its
036 * fitness is greater than the fitness of the other <i>s-1</i> competitors.
037 * Note that the worst individual never survives, and the best individual wins
038 * in all the tournaments it participates. The selection pressure can be varied
039 * by changing the tournament size <i>s</i> . For large values of <i>s</i>, weak
040 * individuals have less chance being selected.
041 *
042 * @see <a href="http://en.wikipedia.org/wiki/Tournament_selection">Tournament selection</a>
043 *
044 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
045 * @since 1.0
046 * @version 1.0 — <em>$Date: 2014-02-27 $</em>
047 */
048 public class TournamentSelector<
049 G extends Gene<?, G>,
050 C extends Comparable<? super C>
051 >
052 implements Selector<G, C>
053 {
054
055 private final int _sampleSize;
056
057 /**
058 * Create a tournament selector with the give sample size. The sample size
059 * must be greater than one.
060 *
061 * @throws IllegalArgumentException if the sample size is smaller than two.
062 */
063 public TournamentSelector(final int sampleSize) {
064 if (sampleSize < 2) {
065 throw new IllegalArgumentException(
066 "Sample size must be greater than one, but was " + sampleSize
067 );
068 }
069 _sampleSize = sampleSize;
070 }
071
072 /**
073 * Create a tournament selector with sample size two.
074 */
075 public TournamentSelector() {
076 this(2);
077 }
078
079 /**
080 * @throws IllegalArgumentException if the sample size is greater than the
081 * population size or {@code count} is greater the the population
082 * size or the _sampleSize is greater the the population size.
083 * @throws NullPointerException if the {@code population} is {@code null}.
084 */
085 @Override
086 public Population<G, C> select(
087 final Population<G, C> population,
088 final int count,
089 final Optimize opt
090 ) {
091 requireNonNull(population, "Population");
092 requireNonNull(opt, "Optimization");
093 if (count < 0) {
094 throw new IllegalArgumentException(format(
095 "Selection count must be greater or equal then zero, but was %s",
096 count
097 ));
098 }
099 if (count > population.size()) {
100 throw new IllegalArgumentException(format(
101 "Selection size greater than population size: %s > %s",
102 count, population.size()
103 ));
104 }
105 if (_sampleSize > population.size()) {
106 throw new IllegalArgumentException(format(
107 "Tournament size is greater than the population size! %d > %d.",
108 _sampleSize, population.size()
109 ));
110 }
111
112 final Population<G, C> pop = new Population<>(count);
113 final Factory<Phenotype<G, C>> factory = factory(
114 population, opt, _sampleSize, RandomRegistry.getRandom()
115 );
116
117 return pop.fill(factory, count);
118 }
119
120 private static <
121 G extends Gene<?, G>,
122 C extends Comparable<? super C>
123 >
124 Factory<Phenotype<G, C>> factory(
125 final Population<G, C> population,
126 final Optimize opt,
127 final int sampleSize,
128 final Random random
129 ) {
130 return new Factory<Phenotype<G, C>>() {
131 @Override
132 public Phenotype<G, C> newInstance() {
133 return select(population, opt, sampleSize, random);
134 }
135 };
136 }
137
138 private static <
139 G extends Gene<?, G>,
140 C extends Comparable<? super C>
141 >
142 Phenotype<G, C> select(
143 final Population<G, C> population,
144 final Optimize opt,
145 final int sampleSize,
146 final Random random
147 ) {
148 final int N = population.size();
149 Phenotype<G, C> winner = population.get(random.nextInt(N));
150
151 for (int j = 0; j < sampleSize; ++j) {
152 final Phenotype<G, C> selection = population.get(random.nextInt(N));
153 if (opt.compare(selection, winner) > 0) {
154 winner = selection;
155 }
156 }
157 assert (winner != null);
158
159 return winner;
160 }
161
162 @Override
163 public int hashCode() {
164 return HashBuilder.of(getClass()).and(_sampleSize).value();
165 }
166
167 @Override
168 public boolean equals(final Object obj) {
169 if (obj == this) {
170 return true;
171 }
172 if (obj == null || obj.getClass() != getClass()) {
173 return false;
174 }
175
176 final TournamentSelector<?, ?> selector = (TournamentSelector<?, ?>)obj;
177 return _sampleSize == selector._sampleSize;
178 }
179
180 /**
181 * @deprecated Will be removed.
182 */
183 @Deprecated
184 public static <SG extends Gene<?, SG>, SC extends Comparable<SC>>
185 TournamentSelector<SG, SC> valueOf(final int sampleSize) {
186 return new TournamentSelector<>(sampleSize);
187 }
188
189 /**
190 * @deprecated Will be removed.
191 */
192 @Deprecated
193 public static <SG extends Gene<?, SG>, SC extends Comparable<SC>>
194 TournamentSelector<SG, SC> valueOf() {
195 return new TournamentSelector<>();
196 }
197
198 @Override
199 public String toString() {
200 return format("%s[s=%d]", getClass().getSimpleName(), _sampleSize);
201 }
202
203 }
|