Djikstra算法

public static void main(String[] args){
		
		Scanner sc = new Scanner(System.in);
		
		int pointsNum = sc.nextInt();
		
		int edgesNum = sc.nextInt();
		
		int[][] map = new int[pointsNum + 1][pointsNum + 1];	
		
		boolean[] isTree = new boolean[pointsNum+1];
		
		int[] minDis = new int[pointsNum + 1];
		
		Arrays.fill(minDis, Integer.MAX_VALUE);
		
		minDis[1] = 0;
		
		for(int i = 0 ; i < edgesNum; i++) {
			
			int p1 = sc.nextInt();
			int p2 = sc.nextInt();
			int v = sc.nextInt();
			map[p1][p2] = v;

		}
		

		
		for(int i = 1; i <= pointsNum; i ++) {
			
			int cur = 1;
			int min = Integer.MAX_VALUE;
			
			//第一步，选距离源点最近且未访问过的节点
			for(int j = 1; j <= pointsNum; j++) {
				
				if(!isTree[j] && minDis[j] < min) {
					min = minDis[j];
					cur = j;
				}
			}
			
			//第二步，标记该节点为已经访问
			isTree[cur] = true;
			
			
			//第三步，更新minDis， 非访问节点到源点的距离
			
			for(int j = 1; j <= pointsNum; j++) {
				
				if(!isTree[j] && map[cur][j] != 0 &&  minDis[cur] + map[cur][j] < minDis[j]) {
					minDis[j] = minDis[cur] + map[cur][j];
					//minDis[cur] + map[cur][j] 当前节点到源点的距离 + 当前节点到该非访问节点的距离
				}
				
			}
			
			
			
		}
		
		
		if(minDis[pointsNum] == Integer.MAX_VALUE) {
			System.out.println(-1);
		}else {

			System.out.println(minDis[pointsNum]);
			
		}
		
		
	}

import java.util.*;

class Edge {
    int to;  // 邻接顶点
    int val; // 边的权重

    Edge(int to, int val) {
        this.to = to;
        this.val = val;
    }
}

class MyComparison implements Comparator<Pair<Integer, Integer>> {
    @Override
    public int compare(Pair<Integer, Integer> lhs, Pair<Integer, Integer> rhs) {
        return Integer.compare(lhs.second, rhs.second);
    }
}

class Pair<U, V> {
    public final U first;
    public final V second;

    public Pair(U first, V second) {
        this.first = first;
        this.second = second;
    }
}

public class Main {
    public static void main(String[] args) {
        Scanner scanner = new Scanner(System.in);
        int n = scanner.nextInt();
        int m = scanner.nextInt();

        List<List<Edge>> grid = new ArrayList<>(n + 1);
        for (int i = 0; i <= n; i++) {
            grid.add(new ArrayList<>());
        }

        for (int i = 0; i < m; i++) {
            int p1 = scanner.nextInt();
            int p2 = scanner.nextInt();
            int val = scanner.nextInt();
            grid.get(p1).add(new Edge(p2, val));
        }

        int start = 1;  // 起点
        int end = n;    // 终点

        // 存储从源点到每个节点的最短距离
        int[] minDist = new int[n + 1];
        Arrays.fill(minDist, Integer.MAX_VALUE);

        // 记录顶点是否被访问过
        boolean[] visited = new boolean[n + 1];

        // 优先队列中存放 Pair<节点，源点到该节点的权值>
        PriorityQueue<Pair<Integer, Integer>> pq = new PriorityQueue<>(new MyComparison());

        // 初始化队列，源点到源点的距离为0，所以初始为0
        pq.add(new Pair<>(start, 0));

        minDist[start] = 0;  // 起始点到自身的距离为0

        while (!pq.isEmpty()) {
            // 1. 第一步，选源点到哪个节点近且该节点未被访问过（通过优先级队列来实现）
            // <节点， 源点到该节点的距离>
            Pair<Integer, Integer> cur = pq.poll();

            if (visited[cur.first]) continue;

            // 2. 第二步，该最近节点被标记访问过
            visited[cur.first] = true;

            // 3. 第三步，更新非访问节点到源点的距离（即更新minDist数组）
            for (Edge edge : grid.get(cur.first)) { // 遍历 cur指向的节点，cur指向的节点为 edge
                // cur指向的节点edge.to，这条边的权值为 edge.val
                if (!visited[edge.to] && minDist[cur.first] + edge.val < minDist[edge.to]) { // 更新minDist
                    minDist[edge.to] = minDist[cur.first] + edge.val;
                    pq.add(new Pair<>(edge.to, minDist[edge.to]));
                }
            }
        }

        if (minDist[end] == Integer.MAX_VALUE) {
            System.out.println(-1); // 不能到达终点
        } else {
            System.out.println(minDist[end]); // 到达终点最短路径
        }
    }
}