001 /*
002 * Java Genetic Algorithm Library (jenetics-6.3.0).
003 * Copyright (c) 2007-2021 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@gmail.com)
019 */
020 package io.jenetics;
021
022 import static java.lang.Math.min;
023 import static java.lang.String.format;
024 import static io.jenetics.internal.math.Randoms.nextDouble;
025
026 import java.util.Random;
027
028 import io.jenetics.internal.util.Requires;
029 import io.jenetics.util.MSeq;
030 import io.jenetics.util.RandomRegistry;
031
032 /**
033 * This alterer takes two chromosome (treating it as vectors) and creates a
034 * linear combination of this vectors as result. The line-recombination depends
035 * on a variable <em>p</em> which determines how far out along the line (defined
036 * by the two multidimensional points/vectors) the children are allowed to be.
037 * If <em>p</em> = 0 then the children will be located along the line within the
038 * hypercube between the two points. If <em>p</em> > 0 then the children may
039 * be located anywhere on the line, even somewhat outside of the hypercube.
040 * <p>
041 * Points outside of the allowed numeric range are rejected and the original
042 * value are used instead. The strategy on how out-of-range points are handled,
043 * is the difference to the very similar {@link IntermediateCrossover}.
044 *
045 * @see <a href="https://cs.gmu.edu/~sean/book/metaheuristics/"><em>
046 * Essentials of Metaheuristic, page 42</em></a>
047 * @see IntermediateCrossover
048 *
049 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
050 * @version 3.8
051 * @since 3.8
052 */
053 public class LineCrossover<
054 G extends NumericGene<?, G>,
055 C extends Comparable<? super C>
056 >
057 extends Crossover<G, C>
058 {
059
060 private final double _p;
061
062 /**
063 * Creates a new linear-crossover with the given recombination
064 * probability and the line-scaling factor <em>p</em>.
065 *
066 * @param probability the recombination probability.
067 * @param p defines the possible location of the recombined chromosomes. If
068 * <em>p</em> = 0 then the children will be located along the line
069 * within the hypercube between the two points. If <em>p</em> > 0
070 * then the children may be located anywhere on the line, even
071 * somewhat outside of the hypercube.
072 * @throws IllegalArgumentException if the {@code probability} is not in the
073 * valid range of {@code [0, 1]} or if {@code p} is smaller then zero
074 */
075 public LineCrossover(final double probability, final double p) {
076 super(probability);
077 _p = Requires.nonNegative(p, "p");
078 }
079
080 /**
081 * Creates a new linear-crossover with the given recombination
082 * probability. The parameter <em>p</em> is set to zero, which restricts the
083 * recombined chromosomes within the hypercube of the selected chromosomes
084 * (vectors).
085 *
086 * @param probability the recombination probability.
087 * @throws IllegalArgumentException if the {@code probability} is not in the
088 * valid range of {@code [0, 1]}
089 */
090 public LineCrossover(final double probability) {
091 this(probability, 0);
092 }
093
094 /**
095 * Creates a new linear-crossover with default recombination
096 * probability ({@link #DEFAULT_ALTER_PROBABILITY}) and a <em>p</em> value
097 * of zero, which restricts the recombined chromosomes within the hypercube
098 * of the selected chromosomes (vectors).
099 */
100 public LineCrossover() {
101 this(DEFAULT_ALTER_PROBABILITY, 0);
102 }
103
104 @Override
105 protected int crossover(final MSeq<G> v, final MSeq<G> w) {
106 final Random random = RandomRegistry.random();
107
108 final double min = v.get(0).min().doubleValue();
109 final double max = v.get(0).max().doubleValue();
110
111 final double a = nextDouble(-_p, 1 + _p, random);
112 final double b = nextDouble(-_p, 1 + _p, random);
113
114 boolean changed = false;
115 for (int i = 0, n = min(v.length(), w.length()); i < n; ++i) {
116 final double vi = v.get(i).doubleValue();
117 final double wi = w.get(i).doubleValue();
118
119 final double t = a*vi + (1 - a)*wi;
120 final double s = b*wi + (1 - b)*vi;
121
122 if (t >= min && s >= min && t < max && s < max) {
123 v.set(i, v.get(i).newInstance(t));
124 w.set(i, w.get(i).newInstance(s));
125 changed = true;
126 }
127 }
128
129 return changed ? 2 : 0;
130 }
131
132 @Override
133 public String toString() {
134 return format("%s[p=%f]", getClass().getSimpleName(), _probability);
135 }
136
137 }
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