旅行商问题java 代码

旅行商问题（TSP）是一个著名的NP难问题，是求解所有城市之间的最短路径的问题。其实现方式有很多种，这里简单介绍一下基于遗传算法（GA）的实现方式。

下面是一个简单的Java代码示例，使用遗传算法求解旅行商问题：

import java.util.Arrays;
import java.util.Random;

public class TSPGA {
    private int[][] distance; // 城市之间的距离
    private int cityNum; // 城市数量
    private int populationSize; // 种群规模
    private int maxGenerations; // 最大进化代数
    private double crossoverProbability; // 交叉概率
    private double mutationProbability; // 变异概率
    private int elitismCount; // 精英个数
    private int[] bestTour; // 最优路径
    private int bestTourLength; // 最优路径长度

    public TSPGA(int[][] distance, int populationSize, int maxGenerations,
                double crossoverProbability, double mutationProbability,
                int elitismCount) {
        this.distance = distance;
        this.cityNum = distance.length;
        this.populationSize = populationSize;
        this.maxGenerations = maxGenerations;
        this.crossoverProbability = crossoverProbability;
        this.mutationProbability = mutationProbability;
        this.elitismCount = elitismCount;
    }

    public void solve() {
        Population population = new Population(populationSize, cityNum);
        population.initialize();

        for (int i = 0; i < maxGenerations; i++) {
            population = evolvePopulation(population);
        }

        bestTour = population.getFittest().getTour();
        bestTourLength = population.getFittest().getTourLength();
    }

    private Population evolvePopulation(Population population) {
        Population newPopulation = new Population(populationSize, cityNum);

        for (int i = 0; i < elitismCount; i++) {
            newPopulation.setIndividual(i, population.getFittest());
        }

        for (int i = elitismCount; i < populationSize; i++) {
            Individual parent1 = selection(population);
            Individual parent2 = selection(population);
            Individual child = crossover(parent1, parent2);
            mutate(child);
            newPopulation.setIndividual(i, child);
        }

        return newPopulation;
    }

    private Individual selection(Population population) {
        Random rand = new Random();
        Population tournament = new Population(elitismCount, cityNum);
        for (int i = 0; i < elitismCount; i++) {
            tournament.setIndividual(i, population.getIndividual(rand.nextInt(populationSize)));
        }
        return tournament.getFittest();
    }

    private Individual crossover(Individual parent1, Individual parent2) {
        Individual child = new Individual(cityNum);

        int startPos = (int) (Math.random() * parent1.getTourLength());
        int endPos = (int) (Math.random() * parent1.getTourLength());

        for (int i = 0; i < child.getTourLength(); i++) {
            if (startPos < endPos && i > startPos && i < endPos) {
                child.setCity(i, parent1.getCity(i));
            } else if (startPos > endPos) {
                if (!(i < startPos && i > endPos)) {
                    child.setCity(i, parent1.getCity(i));
                }
            }
        }

        for (int i = 0; i < parent2.getTourLength(); i++) {
            if (!child.containsCity(parent2.getCity(i))) {
                for (int j = 0; j < child.getTourLength(); j++) {
                    if (child.getCity(j) == -1) {
                        child.setCity(j, parent2.getCity(i));
                        break;
                    }
                }
            }
        }
        return child;
    }

    private void mutate(Individual individual) {
        Random rand = new Random();
        for (int i = 0; i < individual.getTourLength(); i++) {
            if (Math.random() < mutationProbability) {
                int j = rand.nextInt(individual.getTourLength());
                int temp = individual.getCity(i);
                individual.setCity(i, individual.getCity(j));
                individual.setCity(j, temp);
            }
        }
    }

    public int[] getBestTour() {
        return bestTour;
    }

    public int getBestTourLength() {
        return bestTourLength;
    }

    public static void main(String[] args) {
        int[][] distance = {{0, 2, 9, 10}, {1, 0, 6, 4}, {15, 7, 0, 8}, {6, 3, 12, 0}};
        TSPGA tspGA = new TSPGA(distance, 100, 1000, 0.9, 0.1, 2);
        tspGA.solve();
        System.out.println("Best tour length: " + tspGA.getBestTourLength());
        System.out.println("Best tour: " + Arrays.toString(tspGA.getBestTour()));
    }
}

class Population {
    private Individual[] individuals;

    public Population(int populationSize, int tourSize) {
        individuals = new Individual[populationSize];
        for (int i = 0; i < populationSize; i++) {
            individuals[i] = new Individual(tourSize);
        }
    }

    public void initialize() {
        for (int i = 0; i < individuals.length; i++) {
            individuals[i].generateIndividual();
        }
    }

    public Individual getFittest() {
        Individual fittest = individuals;
        for (int i = 1; i < individuals.length; i++) {
            if (fittest.getFitness() <= individuals[i].getFitness()) {
                fittest = individuals[i];
            }
        }
        return fittest;
    }

    public void setIndividual(int index, Individual individual) {
        individuals[index] = individual;
    }

    public Individual getIndividual(int index) {
        return individuals[index];
    }
}

class Individual {
    private int[] tour;
    private int tourLength;

    public Individual(int tourSize) {
        tour = new int[tourSize];
        tourLength = tourSize;
    }

    public void generateIndividual() {
        for (int i = 0; i < tourLength; i++) {
            tour[i] = i;
        }
        shuffle();
    }

    private void shuffle() {
        Random rand = new Random();
        for (int i = tourLength - 1; i > 0; i--) {
            int j = rand.nextInt(i + 1);
            int temp = tour[i];
            tour[i] = tour[j];
            tour[j] = temp;
        }
    }

    public int getFitness() {
        int fitness = 0;
        for (int i = 0; i < tourLength - 1; i++) {
            fitness += distance[tour[i]][tour[i + 1]];
        }
        fitness += distance[tour[tourLength - 1]][tour];
        return fitness;
    }

    public boolean containsCity(int city) {
        for (int i = 0; i < tourLength; i++) {
            if (tour[i] == city) {
                return true;
            }
        }
        return false;
    }

    public void setCity(int index, int city) {
        tour[index] = city;
    }

    public int getCity(int index) {
        return tour[index];
    }

    public int getTourLength() {
        return tourLength;
    }

    public int[] getTour() {
        return tour;
    }
}

请问你还有什么其他问题吗？