public class Node{ int value; Node next; public static void main(String args[]){ Node h =new Node(); Node p=h; for (int k=1;k<=4;k++) { p.value = 10 - k; Node q = new Node(); p.next = q; p = q; } p=h; while (p!=null){ System.out.println(p.value); p=p.next; } } }

这段Java代码创建了一个链表，链表中每个节点都包含一个整数值和一个指向下一个节点的引用。链表中共有4个节点。

在代码中，首先创建了一个头节点h，然后创建一个指针p指向头节点。接着用for循环创建了4个新节点，并将它们依次连接到链表中。循环结束后，将指针p重新指向头节点h。

最后，通过while循环，遍历整个链表，输出每个节点的值。

输出结果为：

9
8
7
6

相关问题

import java.io.BufferedReader; import java.io.File; import java.io.FileReader; import java.io.IOException; public class TSPSolver { public static void main(String[] args) throws IOException { String filePath = "mu1979.tsp";//该文件放在Java的包中 TSPSolver solver=new TSPSolver(); solver.readTSP(filePath); } public void readTSP(String fileName) throws IOException { File file = new File(fileName); BufferedReader br = new BufferedReader(new FileReader(file)); String line; int numNodes = 0; double[][] nodes = null; while ((line = br.readLine()) != null) { if (line.startsWith("DIMENSION")) { // 获取节点数量 String[] parts = line.split(":"); numNodes = Integer.parseInt(parts[1].trim()); nodes = new double[numNodes][2]; } else if (line.startsWith("NODE_COORD_SECTION")) { // 读取节点坐标 for (int i = 0; i < numNodes; i++) { line = br.readLine(); String[] parts = line.split("\s+"); nodes[i][0] = Double.parseDouble(parts[1]); nodes[i][1] = Double.parseDouble(parts[2]); } } } br.close(); // 计算节点之间的距离 double[][] distance = new double[numNodes][numNodes]; for (int i = 0; i < numNodes; i++) { for (int j = 0; j < numNodes; j++) { double dx = nodes[i][0] - nodes[j][0]; double dy = nodes[i][1] - nodes[j][1]; distance[i][j] = Math.sqrt(dxdx + dydy); } } // 贪心算法求解TSP问题 int start = 0; boolean[] visited = new boolean[numNodes]; visited[start] = true; int[] path = new int[numNodes]; path[0] = start; for (int i = 1; i < numNodes; i++) { int next = -1; double minDist = Double.MAX_VALUE; for (int j = 0; j < numNodes; j++) { if (!visited[j] && distance[start][j] < minDist) { next = j; minDist = distance[start][j]; } } visited[next] = true; path[i] = next; start = next; } // 输出结果 System.out.print("Path: "); for (int i = 0; i < numNodes; i++) { System.out.print(path[i] + "->"); if((i+1)%20==0) System.out.println(); } } }这段代码是用贪心法求解商旅问题，请将其改成用动态规划方法解决商旅问题

商旅问题是一个NP完全问题，使用动态规划算法求解比较困难。一种可行的方法是使用分支限界算法或遗传算法等启发式方法。以下是一个使用遗传算法求解商旅问题的Java代码，供您参考：

import java.io.BufferedReader;
import java.io.File;
import java.io.FileReader;
import java.io.IOException;
import java.util.Arrays;
import java.util.Random;

public class TSPSolver_DP {
    static class City {
        double x;
        double y;

        public City(double x, double y) {
            this.x = x;
            this.y = y;
        }

        public double distanceTo(City other) {
            double dx = x - other.x;
            double dy = y - other.y;
            return Math.sqrt(dx * dx + dy * dy);
        }
    }

    static class Individual implements Comparable<Individual> {
        int[] path;
        double fitness;

        public Individual(int[] path, double fitness) {
            this.path = path;
            this.fitness = fitness;
        }

        @Override
        public int compareTo(Individual o) {
            return Double.compare(fitness, o.fitness);
        }
    }

    private int numCities;
    private City[] cities;
    private Random random = new Random();

    public static void main(String[] args) throws IOException {
        String filePath = "mu1979.tsp";
        TSPSolver_DP solver = new TSPSolver_DP();
        solver.readTSP(filePath);
        solver.solveTSP(100, 10000, 0.8, 0.1);
    }

    public void readTSP(String fileName) throws IOException {
        File file = new File(fileName);
        BufferedReader br = new BufferedReader(new FileReader(file));
        String line;
        while ((line = br.readLine()) != null) {
            if (line.startsWith("DIMENSION")) {
                numCities = Integer.parseInt(line.split(":")[1].trim());
                cities = new City[numCities];
            } else if (line.startsWith("NODE_COORD_SECTION")) {
                for (int i = 0; i < numCities; i++) {
                    line = br.readLine();
                    String[] parts = line.split("\\s+");
                    cities[i] = new City(Double.parseDouble(parts[1]), Double.parseDouble(parts[2]));
                }
            }
        }
        br.close();
    }

    public void solveTSP(int populationSize, int numGenerations, double crossoverRate, double mutationRate) {
        Individual[] population = initializePopulation(populationSize);
        for (int i = 0; i < numGenerations; i++) {
            Arrays.sort(population);
            System.out.printf("Generation %d: Best fitness = %f\n", i, population[0].fitness);
            population = evolvePopulation(population, crossoverRate, mutationRate);
        }
        System.out.printf("Best path: ");
        for (int i = 0; i < numCities; i++) {
            System.out.printf("%d->", population[0].path[i]);
            if ((i + 1) % 20 == 0) {
                System.out.println();
            }
        }
        System.out.printf("%d\n", population[0].path[0]);
    }

    private Individual[] initializePopulation(int populationSize) {
        Individual[] population = new Individual[populationSize];
        for (int i = 0; i < populationSize; i++) {
            int[] path = new int[numCities];
            for (int j = 0; j < numCities; j++) {
                path[j] = j;
            }
            shuffle(path);
            double fitness = evaluateFitness(path);
            population[i] = new Individual(path, fitness);
        }
        return population;
    }

    private void shuffle(int[] array) {
        for (int i = 0; i < array.length; i++) {
            int j = random.nextInt(array.length - i) + i;
            swap(array, i, j);
        }
    }

    private void swap(int[] array, int i, int j) {
        int temp = array[i];
        array[i] = array[j];
        array[j] = temp;
    }

    private double evaluateFitness(int[] path) {
        double distance = 0;
        for (int i = 0; i < numCities; i++) {
            distance += cities[path[i]].distanceTo(cities[path[(i + 1) % numCities]]);
        }
        return 1 / distance;
    }

    private Individual[] evolvePopulation(Individual[] population, double crossoverRate, double mutationRate) {
        Individual[] nextGeneration = new Individual[population.length];
        for (int i = 0; i < population.length; i++) {
            Individual parent1 = selectParent(population);
            Individual parent2 = selectParent(population);
            Individual offspring = crossover(parent1, parent2, crossoverRate);
            mutate(offspring, mutationRate);
            double fitness = evaluateFitness(offspring.path);
            nextGeneration[i] = new Individual(offspring.path, fitness);
        }
        return nextGeneration;
    }

    private Individual selectParent(Individual[] population) {
        int index = random.nextInt(population.length);
        return population[index];
    }

    private Individual crossover(Individual parent1, Individual parent2, double crossoverRate) {
        if (random.nextDouble() < crossoverRate) {
            int index1 = random.nextInt(numCities);
            int index2 = random.nextInt(numCities);
            if (index1 > index2) {
                int temp = index1;
                index1 = index2;
                index2 = temp;
            }
            int[] offspringPath = new int[numCities];
            Arrays.fill(offspringPath, -1);
            for (int i = index1; i <= index2; i++) {
                offspringPath[i] = parent1.path[i];
            }
            int j = 0;
            for (int i = 0; i < numCities; i++) {
                if (j == index1) {
                    j = index2 + 1;
                }
                if (contains(offspringPath, parent2.path[i])) {
                    continue;
                }
                while (offspringPath[j] != -1) {
                    j = (j + 1) % numCities;
                }
                offspringPath[j] = parent2.path[i];
                j = (j + 1) % numCities;
            }
            return new Individual(offspringPath, evaluateFitness(offspringPath));
        } else {
            return parent1;
        }
    }

    private boolean contains(int[] array, int value) {
        for (int i = 0; i < array.length; i++) {
            if (array[i] == value) {
                return true;
            }
        }
        return false;
    }

    private void mutate(Individual individual, double mutationRate) {
        for (int i = 0; i < numCities; i++) {
            if (random.nextDouble() < mutationRate) {
                int j = random.nextInt(numCities);
                swap(individual.path, i, j);
            }
        }
    }
}

该程序假设文件“mu1979.tsp”包含以下格式的数据：

DIMENSION: 1979
NODE_COORD_SECTION
1 0.00000 0.00000
2 0.00000 1.00000
...

程序读取数据并使用遗传算法求解商旅问题，输出结果包括最优路径和最优路径长度。

jsonnode转成jsonmap

要将 `JsonNode` 转换为 `JsonMap`，你可以使用 Jackson 库提供的 API。下面是一个示例代码：

import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;

import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import java.util.Map.Entry;

public class JsonUtils {
    public static JsonMap convertToJsonMap(JsonNode jsonNode) {
        JsonMap jsonMap = new JsonMap();
        
        if (jsonNode.isObject()) {
            Iterator<Entry<String, JsonNode>> fields = jsonNode.fields();
            while (fields.hasNext()) {
                Entry<String, JsonNode> field = fields.next();
                jsonMap.put(field.getKey(), convertToJsonMap(field.getValue()));
            }
        } else if (jsonNode.isArray()) {
            int index = 0;
            for (JsonNode element : jsonNode) {
                jsonMap.put(String.valueOf(index++), convertToJsonMap(element));
            }
        } else if (jsonNode.isValueNode()) {
            jsonMap.put("value", jsonNode.asText());
        }
        
        return jsonMap;
    }
    
    public static void main(String[] args) throws Exception {
        String jsonString = "{\"name\": \"John\", \"age\": 30, \"city\": \"New York\"}";
        ObjectMapper objectMapper = new ObjectMapper();
        JsonNode jsonNode = objectMapper.readTree(jsonString);
        
        JsonMap jsonMap = convertToJsonMap(jsonNode);
        System.out.println(jsonMap);
    }
}

class JsonMap extends HashMap<String, Object> {
    @Override
    public String toString() {
        StringBuilder sb = new StringBuilder();
        sb.append("{");
        
        for (Entry<String, Object> entry : entrySet()) {
            sb.append("\"").append(entry.getKey()).append("\"");            sb.append(": ");
            
            Object value = entry.getValue();
            if (value instanceof JsonMap) {
                sb.append(value.toString());
            } else {
                sb.append("\"").append(value).append("\"");
            }
            
            sb.append(", ");
        }
        
        if (!isEmpty()) {
            sb.setLength(sb.length() - 2);
        }
        
        sb.append("}");
        return sb.toString();
    }
}

以上代码将 `JsonNode` 对象转换为自定义的 `JsonMap` 对象，`JsonMap` 继承自 `HashMap<String, Object>`。你可以根据需要自定义 `JsonMap` 类的方法和字段。

在示例中，我们先将 `JsonNode` 对象转换为 `JsonMap` 对象，然后通过重写 `toString()` 方法将 `JsonMap` 转换为 JSON 字符串进行输出。

注意：为了运行示例代码，你需要将 Jackson 库添加到项目依赖中。你可以在 Maven 或 Gradle 中添加以下依赖：

Maven:

<dependencies>
    <dependency>
        <groupId>com.fasterxml.jackson.core</groupId>
        <artifactId>jackson-databind</artifactId>
        <version>2.12.5</version>
    </dependency>
</dependencies>

Gradle:

dependencies {
    implementation 'com.fasterxml.jackson.core:jackson-databind:2.12.5'
}

希望能对你有所帮助！如有其他问题，请随时提问。