java代码实现遗传算法

好的，以下是一个简单的Java代码实现遗传算法的示例：

import java.util.Random;

public class GeneticAlgorithm {
    private int populationSize;
    private double mutationRate;
    private double crossoverRate;
    private int elitismCount;

    public GeneticAlgorithm(int populationSize, double mutationRate, double crossoverRate, int elitismCount) {
        this.populationSize = populationSize;
        this.mutationRate = mutationRate;
        this.crossoverRate = crossoverRate;
        this.elitismCount = elitismCount;
    }

    public Population evolvePopulation(Population population) {
        Population newPopulation = new Population(population.size());

        // Keep the best individuals from the current population
        for (int i = 0; i < elitismCount; i++) {
            newPopulation.saveIndividual(i, population.getFittest(i));
        }

        // Crossover
        for (int i = elitismCount; i < population.size(); i++) {
            Individual parent1 = selectParent(population);
            Individual parent2 = selectParent(population);
            Individual child = crossover(parent1, parent2);
            newPopulation.saveIndividual(i, child);
        }

        // Mutation
        for (int i = elitismCount; i < newPopulation.size(); i++) {
            mutate(newPopulation.getIndividual(i));
        }

        return newPopulation;
    }

    private Individual selectParent(Population population) {
        Random random = new Random();
        int tournamentSize = 5;
        Population tournament = new Population(tournamentSize);
        for (int i = 0; i < tournamentSize; i++) {
            int randomIndex = random.nextInt(population.size());
            tournament.saveIndividual(i, population.getIndividual(randomIndex));
        }
        return tournament.getFittest(0);
    }

    private Individual crossover(Individual parent1, Individual parent2) {
        Individual child = new Individual(parent1.getChromosomeLength());
        Random random = new Random();
        for (int i = 0; i < parent1.getChromosomeLength(); i++) {
            if (random.nextDouble() <= crossoverRate) {
                child.setGene(i, parent1.getGene(i));
            } else {
                child.setGene(i, parent2.getGene(i));
            }
        }
        return child;
    }

    private void mutate(Individual individual) {
        Random random = new Random();
        for (int i = 0; i < individual.getChromosomeLength(); i++) {
            if (random.nextDouble() <= mutationRate) {
                int gene = random.nextInt(2);
                individual.setGene(i, gene);
            }
        }
    }
}

这个示例中，我们定义了一个遗传算法类 `GeneticAlgorithm`，它包含了一些参数，如种群大小、变异率、交叉率和精英数量。我们还定义了一些方法，如 `evolvePopulation`、`selectParent`、`crossover` 和 `mutate`，用于执行遗传算法的不同步骤。