旅行商路线规划最短哈密尔顿回路求法java代码

以下是使用遗传算法求解旅行商问题的Java代码示例：

import org.uma.jmetal.algorithm.multiobjective.nsgaii.NSGAIIBuilder;
import org.uma.jmetal.operator.MutationOperator;
import org.uma.jmetal.problem.Problem;
import org.uma.jmetal.problem.multiobjective.TSP;
import org.uma.jmetal.solution.DoubleSolution;
import org.uma.jmetal.util.AbstractAlgorithmRunner;
import org.uma.jmetal.util.JMetalException;
import org.uma.jmetal.util.ProblemUtils;
import org.uma.jmetal.util.comparator.RankingAndCrowdingDistanceComparator;

import java.util.List;

public class TSPNSGAIIRunner extends AbstractAlgorithmRunner {
    /**
     * @param args Command line arguments.
     * @throws SecurityException Invoking command:
     *                           java org.uma.jmetal.runner.multiobjective.NSGAIIRunner problemName [referenceFront]
     */
    public static void main(String[] args) throws JMetalException {
        Problem<DoubleSolution> problem;
        MutationOperator<DoubleSolution> mutation;
        NSGAIIBuilder<DoubleSolution> algorithm;

        String problemName = "org.uma.jmetal.problem.multiobjective.TSP";
        String referenceParetoFront = "";

        if (args.length == 1) {
            problemName = args[0];
        } else if (args.length == 2) {
            problemName = args[0];
            referenceParetoFront = args[1];
        }

        problem = ProblemUtils.loadProblem(problemName);

        int populationSize = 100;
        int maxEvaluations = 25000;
        mutation = new SwapMutation();

        algorithm = new NSGAIIBuilder<>(problem, mutation)
                .setPopulationSize(populationSize)
                .setMaxEvaluations(maxEvaluations)
                .setSelectionOperator(new BinaryTournamentSelection<>(new RankingAndCrowdingDistanceComparator<>()))
                .build();

        algorithm.run();

        List<DoubleSolution> population = algorithm.getResult();

        printFinalSolutionSet(population);
        if (!referenceParetoFront.equals("")) {
            printQualityIndicators(population, referenceParetoFront);
        }
    }
}

该代码使用了JMetal框架中的NSGA-II算法来解决TSP问题，其中SwapMutation是一个自定义的变异算子。需要注意的是，该代码仅提供了一个框架，需要根据具体的问题进行修改和调整。