001/* 002 * Java Genetic Algorithm Library (jenetics-9.0.0). 003 * Copyright (c) 2007-2026 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.engine; 021 022import io.jenetics.Gene; 023import io.jenetics.Phenotype; 024import io.jenetics.util.ISeq; 025import io.jenetics.util.Seq; 026 027/** 028 * This interface allows defining different strategies for evaluating the 029 * fitness functions of a given population. <em>Normally</em> there is no 030 * need for <em>overriding</em> the default evaluation strategy, but it might 031 * be necessary if you have performance problems and a <em>batched</em> 032 * fitness evaluation would solve the problem. 033 * <p> 034 * The implementer is free to do the evaluation <em>in place</em>, or create 035 * new {@link Phenotype} instance and return the newly created one. A simple 036 * serial evaluator can easily implement: 037 * {@snippet lang="java": 038 * final Function<? super Genotype<G>, ? extends C> fitness = null; // @replace substring='null' replacement="..." 039 * final Evaluator<G, C> evaluator = population -> population 040 * .map(pt -> pt.eval(fitness)) 041 * .asISeq(); 042 * 043 * final Engine<G, C> engine = new Engine.Builder<>(evaluator, genotypeFactory) 044 * .build(); 045 * } 046 * 047 * @apiNote 048 * The size of the returned, evaluated, phenotype sequence must be exactly 049 * the size of the input phenotype sequence, and all phenotypes must have a 050 * fitness value assigned ({@code assert population.forAll(Phenotype::isEvaluated);}). 051 * It is allowed to return the input sequence, after evaluation, as well as a newly 052 * created one. 053 * 054 * @see Evaluators 055 * @see Engine 056 * 057 * @param <G> the gene type 058 * @param <C> the fitness result type 059 * 060 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a> 061 * @version 5.0 062 * @since 4.2 063 */ 064@FunctionalInterface 065public interface Evaluator< 066 G extends Gene<?, G>, 067 C extends Comparable<? super C> 068> { 069 070 /** 071 * Evaluates the fitness values of the given {@code population}. The 072 * given {@code population} might contain already evaluated individuals. 073 * It is the responsibility of the implementer to filter out already 074 * evaluated individuals, if desired. 075 * 076 * @param population the population to evaluate 077 * @return the evaluated population. Implementers are free to return the 078 * input population or a newly created one. 079 */ 080 ISeq<Phenotype<G, C>> eval(final Seq<Phenotype<G, C>> population); 081 082}