smile.gap.Chromosome Maven / Gradle / Ivy

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 * Copyright (c) 2010-2020 Haifeng Li. All rights reserved.
 *
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package smile.gap;

/**
 * Artificial chromosomes in genetic algorithm/programming encoding candidate
 * solutions to an optimization problem. Note that chromosomes have to
 * implement Comparable interface to support comparison of their fitness.
 *
 * @author Haifeng Li
 */
public interface Chromosome extends Comparable {

    /**
     * Returns the fitness of chromosome.
     */
    double fitness();

    /**
     * Returns a new random instance.
     */
    Chromosome newInstance();

    /**
     * Returns a pair of offsprings by crossovering this one with another one
     * according to the crossover rate, which determines how often will be
     * crossover performed. If there is no crossover, offspring is exact copy of
     * parents. Various crossover strategies can be employed.
     */
    Chromosome[] crossover(Chromosome another);

    /**
     * For genetic algorithms, this method mutates the chromosome randomly.
     * The offspring may have no changes since the mutation rate is usually
     * very low. For Lamarckian algorithms, this method actually does the local
     * search such as such as hill-climbing.
     */
    void mutate();
}