001 /*
002 * Java Genetic Algorithm Library (jenetics-3.7.0).
003 * Copyright (c) 2007-2016 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 org.jenetics.internal.util.Equality;
026 import org.jenetics.internal.util.Hash;
027
028 /**
029 * In truncation selection individuals are sorted according to their fitness.
030 * Only the n best individuals are selected. The truncation selection is a very
031 * basic selection algorithm. It has it's strength in fast selecting individuals
032 * in large populations, but is not very often used in practice.
033 *
034 * @see <a href="http://en.wikipedia.org/wiki/Truncation_selection">
035 * Wikipedia: Truncation selection
036 * </a>
037 *
038 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
039 * @since 1.0
040 * @version 2.0
041 */
042 public final class TruncationSelector<
043 G extends Gene<?, G>,
044 C extends Comparable<? super C>
045 >
046 implements Selector<G, C>
047 {
048
049 /**
050 * Create a new TruncationSelector object.
051 */
052 public TruncationSelector() {
053 }
054
055 /**
056 * This method sorts the population in descending order while calculating
057 * the selection probabilities. (The method
058 * {@link Population#sortWith(java.util.Comparator)} )} is called by this
059 * method.) If the selection size is greater the the population size, the
060 * whole population is duplicated until the desired sample size is reached.
061 *
062 * @throws NullPointerException if the {@code population} is {@code null}.
063 */
064 @Override
065 public Population<G, C> select(
066 final Population<G, C> population,
067 final int count,
068 final Optimize opt
069 ) {
070 requireNonNull(population, "Population");
071 requireNonNull(opt, "Optimization");
072 if (count < 0) {
073 throw new IllegalArgumentException(format(
074 "Selection count must be greater or equal then zero, but was %s",
075 count
076 ));
077 }
078
079 final Population<G, C> selection = new Population<>(count);
080 if (count > 0 && !population.isEmpty()) {
081 final Population<G, C> copy = population.copy();
082 copy.sortWith(opt.<C>descending());
083
084 int size = count;
085 do {
086 final int length = Math.min(copy.size(), size);
087 selection.addAll(copy.subList(0, length));
088 size -= length;
089 } while (size > 0);
090 }
091
092 return selection;
093 }
094
095 @Override
096 public int hashCode() {
097 return Hash.of(getClass()).value();
098 }
099
100 @Override
101 public boolean equals(final Object obj) {
102 return Equality.ofType(this, obj);
103 }
104
105 @Override
106 public String toString() {
107 return getClass().getName();
108 }
109
110 }
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