001/*
002 * Java Genetic Algorithm Library (jenetics-8.1.0).
003 * Copyright (c) 2007-2024 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 */
020package io.jenetics;
021
022import static java.lang.Double.compare;
023import static java.lang.Math.pow;
024import static java.lang.String.format;
025
026import io.jenetics.util.Seq;
027
028/**
029 * <p>
030 * An alternative to the "weak" {@code LinearRankSelector} is to assign
031 * survival probabilities to the sorted individuals using an exponential
032 * function.
033 * </p>
034 * <p><img
035 *        src="doc-files/exponential-rank-selector.svg"
036 *        alt="P(i)=\left(c-1\right)\frac{c^{i-1}}{c^{N}-1}"
037 *     >,
038 * </p>
039 * where <i>c</i> must within the range {@code [0..1)}.
040 *
041 * <p>
042 * A small value of <i>c</i> increases the probability of the best phenotypes to
043 * be selected. If <i>c</i> is set to zero, the selection probability of the best
044 * phenotype is set to one. The selection probability of all other phenotypes is
045 * zero. A value near one equalizes the selection probabilities.
046 * </p>
047 * <p>
048 * This selector sorts the population in descending order while calculating the
049 * selection probabilities.
050 * </p>
051 *
052 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
053 * @since 1.0
054 * @version 5.0
055 */
056public final class ExponentialRankSelector<
057        G extends Gene<?, G>,
058        C extends Comparable<? super C>
059>
060        extends ProbabilitySelector<G, C>
061{
062
063        private final double _c;
064
065        /**
066         * Create a new exponential rank selector.
067         *
068         * @param c the <i>c</i> value
069         * @throws IllegalArgumentException if {@code c} is not within the range
070         *         {@code [0..1)}.
071         */
072        public ExponentialRankSelector(final double c) {
073                super(true);
074
075                if (compare(c, 0) < 0 || compare(c, 1) >= 0) {
076                        throw new IllegalArgumentException(format(
077                                "Value %f is out of range [0..1): ", c
078                        ));
079                }
080                _c = c;
081        }
082
083        /**
084         * Create a new selector with the default value of 0.975.
085         */
086        public ExponentialRankSelector() {
087                this(0.975);
088        }
089
090        /**
091         * This method sorts the population in descending order while calculating the
092         * selection probabilities.
093         */
094        @Override
095        protected double[] probabilities(
096                final Seq<Phenotype<G, C>> population,
097                final int count
098        ) {
099                assert population != null : "Population must not be null. ";
100                assert !population.isEmpty() : "Population is empty.";
101                assert count > 0 : "Population to select must be greater than zero. ";
102
103                final double N = population.size();
104                final double[] probabilities = new double[population.size()];
105
106                final double b = (_c - 1.0)/(pow(_c, N) - 1.0);
107                for (int i = 0; i < probabilities.length; ++i) {
108                        probabilities[i] = pow(_c, i)*b;
109                }
110
111                return probabilities;
112        }
113
114        @Override
115        public String toString() {
116                return format("%s[c=%f]", getClass().getSimpleName(), _c);
117        }
118
119}