求Pareto蚁群算法的源码 Java的

Question

求Pareto最优化和蚁群算法相结合的算法的源码，即Pareto蚁群算法 Java的

Answer 1

以下Java示例模拟了一个简单的问题，其中每个城市之间的距离由 graph 矩阵表示。在 main 方法中，创建了一个 ParetoAntColony 对象并运行了 optimize 方法来执行算法。最后，输出找到的所有解。

import java.util.ArrayList;
import java.util.List;
import java.util.Random;

public class ParetoAntColony {

    private static final int ANT_COUNT = 10;
    private static final int MAX_ITERATIONS = 100;
    private static final double ALPHA = 1.0; // 控制信息素重要程度
    private static final double BETA = 2.0; // 控制启发函数重要程度
    private static final double RHO = 0.5; // 信息素挥发速度
    private static final double Q = 500; // 信息素增加强度系数
    private static final double INITIAL_PHEROMONE = 1.0; // 初始信息素浓度
    private static final int DIMENSION = 2; // 问题维度

    private int[][] graph;
    private double[][] pheromones;
    private double[][] heuristicValues;
    private List<int[]> solutions;

    public ParetoAntColony(int[][] graph) {
        this.graph = graph;
        this.pheromones = new double[graph.length][graph.length];
        this.heuristicValues = new double[graph.length][graph.length];
        this.solutions = new ArrayList<>();
        initializePheromones();
        initializeHeuristicValues();
    }

    private void initializePheromones() {
        for (int i = 0; i < pheromones.length; i++) {
            for (int j = 0; j < pheromones[i].length; j++) {
                pheromones[i][j] = INITIAL_PHEROMONE;
            }
        }
    }

    private void initializeHeuristicValues() {
        for (int i = 0; i < graph.length; i++) {
            for (int j = 0; j < graph[i].length; j++) {
                heuristicValues[i][j] = 1.0 / (graph[i][j] + 0.0001);
            }
        }
    }

    public void optimize() {
        for (int iteration = 0; iteration < MAX_ITERATIONS; iteration++) {
            for (int ant = 0; ant < ANT_COUNT; ant++) {
                int[] solution = constructSolution();
                solutions.add(solution);
                updatePheromones(solution);
            }
            evaporatePheromones();
        }
    }

    private int[] constructSolution() {
        int[] solution = new int[DIMENSION];
        boolean[] visited = new boolean[graph.length];
        Random random = new Random();
        int current = random.nextInt(graph.length);
        solution[0] = current;
        visited[current] = true;
        for (int i = 1; i < DIMENSION; i++) {
            int next = selectNext(current, visited);
            solution[i] = next;
            visited[next] = true;
            current = next;
        }
        return solution;
    }

    private int selectNext(int current, boolean[] visited) {
        double[] probabilities = new double[graph.length];
        double total = 0;
        for (int i = 0; i < graph.length; i++) {
            if (!visited[i]) {
                probabilities[i] = Math.pow(pheromones[current][i], ALPHA) * Math.pow(heuristicValues[current][i], BETA);
                total += probabilities[i];
            }
        }
        double rand = Math.random() * total;
        double sum = 0;
        for (int i = 0; i < probabilities.length; i++) {
            if (!visited[i]) {
                sum += probabilities[i];
                if (rand <= sum) {
                    return i;
                }
            }
        }
        return -1; // Should not reach here
    }

    private void updatePheromones(int[] solution) {
        for (int i = 0; i < solution.length - 1; i++) {
            pheromones[solution[i]][solution[i + 1]] += Q;
        }
        pheromones[solution[solution.length - 1]][solution[0]] += Q; // Close the loop
    }

    private void evaporatePheromones() {
        for (int i = 0; i < pheromones.length; i++) {
            for (int j = 0; j < pheromones[i].length; j++) {
                pheromones[i][j] *= (1 - RHO);
            }
        }
    }

    public List<int[]> getSolutions() {
        return solutions;
    }

    public static void main(String[] args) {
        // Example usage
        int[][] graph = {
            {0, 2, 3},
            {2, 0, 4},
            {3, 4, 0}
        };
        ParetoAntColony pac = new ParetoAntColony(graph);
        pac.optimize();
        List<int[]> solutions = pac.getSolutions();
        for (int[] solution : solutions) {
            for (int city : solution) {
                System.out.print(city + " ");
            }
            System.out.println();
        }
    }
}