@@ -0,0 +1,1919 @@
+/*%0A * Java Genetic Algorithm Library (@__identifier__@).%0A * Copyright (c) @__year__@ Franz Wilhelmst%C3%B6tter%0A *%0A * Licensed under the Apache License, Version 2.0 (the %22License%22);%0A * you may not use this file except in compliance with the License.%0A * You may obtain a copy of the License at%0A *%0A *      http://www.apache.org/licenses/LICENSE-2.0%0A *%0A * Unless required by applicable law or agreed to in writing, software%0A * distributed under the License is distributed on an %22AS IS%22 BASIS,%0A * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.%0A * See the License for the specific language governing permissions and%0A * limitations under the License.%0A *%0A * Author:%0A *    Franz Wilhelmst%C3%B6tter (franz.wilhelmstoetter@gmx.at)%0A */%0Apackage org.jenetics.example;%0A%0Aimport org.jenetics.DoubleGene;%0Aimport org.jenetics.Mutator;%0Aimport org.jenetics.TruncationSelector;%0Aimport org.jenetics.engine.Codec;%0Aimport org.jenetics.engine.Engine;%0Aimport org.jenetics.engine.EvolutionResult;%0Aimport org.jenetics.engine.codecs;%0Aimport org.jenetics.util.DoubleRange;%0A%0A/**%0A * The (%CE%BC + %CE%BB) evolution strategy is among the simplest ES algorithms.%0A *%0A * @author %3Ca href=%22mailto:franz.wilhelmstoetter@gmx.at%22%3EFranz Wilhelmst%C3%B6tter%3C/a%3E%0A * @version !__version__!%0A * @since !__version__!%0A */%0Apublic class MpLStrategy %7B%0A%0A%09static double fitness(final double x) %7B%0A%09%09return x;%0A%09%7D%0A%0A%09public static void main(final String%5B%5D args) %7B%0A%09%09final int %CE%BC = 5;%0A%09%09final int %CE%BB = 20;%0A%09%09final double p = 0.2;%0A%0A%09%09final Codec%3CDouble, DoubleGene%3E codec = codecs%0A%09%09%09.ofScalar(DoubleRange.of(0, 1));%0A%0A%09%09final Engine%3CDoubleGene, Double%3E engine = Engine%0A%09%09%09.builder(MpLStrategy::fitness, codec)%0A%09%09%09.populationSize(%CE%BB)%0A%09%09%09.survivorsSize(%CE%BC)%0A%09%09%09.selector(new TruncationSelector%3C%3E(%CE%BC))%0A%09%09%09.alterers(new Mutator%3C%3E(p))%0A%09%09%09.build();%0A%0A%09%09System.out.println(%0A%09%09%09codec.decode(%0A%09%09%09%09engine.stream()%0A%09%09%09%09%09.limit(100)%0A%09%09%09%09%09.collect(EvolutionResult.toBestGenotype())%0A%09%09%09)%0A%09%09);%0A%09%7D%0A%0A%7D%0A

Implement (μ + λ) ES example.