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.ext;
021
022import static java.lang.String.format;
023
024import io.jenetics.Gene;
025import io.jenetics.Mutator;
026import io.jenetics.TruncationSelector;
027import io.jenetics.engine.Engine.Builder;
028import io.jenetics.engine.Engine.Setup;
029import io.jenetics.internal.util.Requires;
030
031/**
032 * Setup for a (μ, λ)-Evolution Strategy. Applying this setup is done in the
033 * following way.
034 * {@snippet lang="java":
035 * final var engine = Engine.builder(problem)
036 *     .setup(new MLEvolutionStrategy<>(μ, λ, p))
037 *     .build();
038 * }
039 *
040 * And is equivalent to the following builder setup.
041 * {@snippet lang="java":
042 * final var engine = Engine.builder(problem)
043 *     .populationSize(λ)
044 *     .survivorsSize(0)
045 *     .offspringSelector(new TruncationSelector<>(μ))
046 *     .alterers(new Mutator<>(p))
047 *     .build();
048 * }
049 *
050 * @param <G> the gene type
051 * @param <C> the fitness result type
052 *
053 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
054 * @version 6.0
055 * @since 6.0
056 */
057public final class MLEvolutionStrategy<
058        G extends Gene<?, G>,
059        C extends Comparable<? super C>
060>
061        implements Setup<G, C>
062{
063
064        private final int _mu;
065        private final int _lambda;
066        private final double _mutationProbability;
067
068        /**
069         * Create a new (μ, λ)-Evolution Strategy with the given parameters.
070         *
071         * @param mu the number of the fittest individuals to be selected
072         * @param lambda the population count
073         * @param mutationProbability the mutation probability
074         * @throws IllegalArgumentException if {@code mu < 2} or {@code lambda < mu}
075         *         or {@code mutationProbability not in [0, 1]}
076         */
077        public MLEvolutionStrategy(
078                final int mu,
079                final int lambda,
080                final double mutationProbability
081        ) {
082                if (mu < 2) {
083                        throw new IllegalArgumentException(format(
084                                "mu (μ) must be greater or equal 2: %d.", mu
085                        ));
086                }
087                if (lambda < mu) {
088                        throw new IllegalArgumentException(format(
089                                "lambda (λ) must be greater or equal then μ [μ=%d, λ=%d].",
090                                mu, lambda
091                        ));
092                }
093
094                _mu = mu;
095                _lambda = lambda;
096                _mutationProbability = Requires.probability(mutationProbability);
097        }
098
099        /**
100         * Create a new (μ, λ)-Evolution Strategy with the given parameters. The
101         * mutation probability is set to {@link Mutator#DEFAULT_ALTER_PROBABILITY}.
102         *
103         * @param mu the number of the fittest individuals to be selected
104         * @param lambda the population count
105         * @throws IllegalArgumentException if {@code mu < 2} or {@code lambda < mu}
106         *         or {@code mutationProbability not in [0, 1]}
107         */
108        public MLEvolutionStrategy(final int mu, final int lambda) {
109                this(mu, lambda, Mutator.DEFAULT_ALTER_PROBABILITY);
110        }
111
112        @Override
113        public void apply(final Builder<G, C> builder) {
114                builder.populationSize(_lambda)
115                        .survivorsSize(0)
116                        .offspringSelector(new TruncationSelector<>(_mu))
117                        .alterers(new Mutator<>(_mutationProbability));
118        }
119
120}