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Dijkstra(迪杰斯特拉 权值都是正的)
是典型的单源最短路径算法,用于计算一个节点到其他所有节点的最短路径。主要特点是以起始点为中心向外层层扩展,直到扩展到终点为止
算法的输入是:
有权(有向)图
起点(源)
所有边的权非负
算法的输出是:
起点(源)到其他各点的最短路径
Floyd(弗洛伊德 可以带负权值)
是解决任意两点间的最短路径的一种算法,可以正确处理有向图或负权的最短路径问题,同时也被用于计算有向图的传递闭包。Floyd-Warshall算法的时间复杂度为O(N3),空间复杂度为O(N2)
Bellman-Ford(伯尔曼 单源最短路径可以带负权值,比Dijkstra要广)
首先假设源点到所有点的距离为无穷大,然后从任一顶点u出发,遍历其它所有顶点vi,计算从源点到其它顶点vi的距离与从vi到u的距离的和,如果比原来距离小,则更新,遍历完所有的顶点为止,即可求得源点到所有顶点的最短距离。
4.无向无权图的最短路径算法
public class Dijkstra { static int max = Integer.MAX_VALUE; static int dist[] = new int[6]; static int prev[] = new int[6]; static int a[][] = { {0,max,10,max,30,100}, {max,0,5,max,max,max}, {max,max,0,50,max,max}, {max,max,max,0,max,10}, {max,max,max,20,0,60}, {max,max,max,max,max,0} }; void dijkstra(int v,int a[][], int dist[], int prev[]){ int n = dist.length - 1; boolean s[] = new boolean[n+1]; for (int i = 1; i<= n;i++){ dist[i] = a[v][i]; s[i] = false; if (dist[i] < Integer.MAX_VALUE) prev[i] = v; else prev[i] = -1; } dist[v] = 0; s[v] = true; for (int i=1;i<=n;i++){ int temp = Integer.MAX_VALUE; int u = v; for (int j =1; j<= n;j++){ if (!s[j] && dist[j] <temp){ u = j; temp = dist[j]; } } s[u] = true; for (int j = 0;j <= n; j++){ if(!s[j] && a[u][j] < Integer.MAX_VALUE){ int newDist = dist[u] + a[u][j]; if (newDist < dist[j]){ dist[j] = newDist; prev[j] = u; } } } } } void outPath(int m, int p[],int []d){ for (int i = 0; i< dist.length; i++){ if (d[i] < Integer.MAX_VALUE && i != m){ System.out.print("v"+i+"<--"); int next = p[i]; while (next != m){ System.out.print("v"+next+"<--"); next = p[next]; } System.out.println("v"+m+":"+d[i]); } else if( i != m) System.out.println("v"+i+"<--"+"v"+m+":no path"); } } public static void main(String[] args) { Dijkstra d = new Dijkstra(); d.dijkstra(0,a,dist,prev); d.outPath(0,prev,dist); } } =================== import java.util.ArrayList; public class Floyd { /* * 给出一个含有n个顶点的带权有向图,要求其每一对顶点之间的最短路径。 * 这里采用佛洛依德(Floyd)最短路径算法: */ private static int max=Integer.MAX_VALUE; private static int [][]dist=new int[6][6]; //存储最短路径 private static int [][]path=new int[6][6]; //存储最短路径的长度 private static ArrayList list=new ArrayList<Integer>(); private static int [][]Arcs={ {max,max,10,max,30,100}, {max,max,5,max,max,max}, {max,max,max,50,max,max}, {max,max,max,max,20,10}, {max,max,max,max,max,60}, {max,max,max,max,max,max} }; public void findCheapestPath(int begin,int end,int Arcs[][]){ floyd(Arcs); list.clear(); list.add(begin); findPath(begin,end); list.add(end); } public void findPath(int i,int j){ int k=path[i][j]; if(k==-1) return ; findPath(i,k); list.add(k); findPath(k,j); } public void floyd(int [][] Arcs){ int n=Arcs.length; for(int i=0;i<n;i++) for(int j=0;j<n;j++){ path[i][j]=-1; //初始化当前的路径长度表 dist[i][j]=Arcs[i][j]; //初始化当前的路径表 } for(int k=0;k<n;k++) for(int i=0;i<n;i++) for(int j=0;j<n;j++){ if(dist[i][k]!=max&&dist[k][j]!=max&&dist[i][k]+dist[k][j]<dist[i][j]){ dist[i][j]=dist[i][k]+dist[k][j]; path[i][j]=k; } } } public static void main(String[] args) { // TODO Auto-generated method stub Floyd f=new Floyd(); for(int i=0;i<Arcs.length;i++) for(int j=0;j<Arcs.length;j++){ f.findCheapestPath(i, j, Arcs); ArrayList<Integer>L=f.list; System.out.print(i+"-->"+j+":"); if(f.dist[i][j]==max){ System.out.println("之间没有最短路径"); System.out.println(); } else{ System.out.println("的最短路径是:"); System.out.print(L.toString()+" "); System.out.println("路径长度:"+f.dist[i][j]); System.out.println(); } } } } ============= import java.io.*; import java.util.*; public class bellmanford { final public static int MAX = 1000000000; // Short driver program to test the Bellman Ford's method. public static void main(String[] args) { // Read in graph. int[][] adj = new int[5][5]; Scanner fin = new Scanner(System.in); int numEdges = 0; for (int i = 0; i<25; i++) { adj[i/5][i%5] = fin.nextInt(); if (adj[i/5][i%5] != 0) numEdges++; } // Form edge list. edge[] eList = new edge[numEdges]; int eCnt = 0; for (int i = 0; i<25; i++) if (adj[i/5][i%5] != 0) eList[eCnt++] = new edge(i/5, i%5, adj[i/5][i%5]); // Run algorithm and print out shortest distances. int[] answers = bellmanford(eList, 5, 0); for (int i=0; i<5; i++) System.out.print(answers[i]+" "); System.out.println(); } // Returns the shortest paths from vertex source to the rest of the // vertices in the graph via Bellman Ford's algorithm. public static int[] bellmanford(edge[] eList, int numVertices, int source) { // This array will store our estimates of shortest distances. int[] estimates = new int[numVertices]; // Set these to a very large number, larger than any path in our // graph could possibly be. for (int i=0; i<estimates.length; i++) estimates[i] = MAX; // We are already at our source vertex. estimates[source] = 0; // Runs v-1 times since the max number of edges on any shortest path is v-1, if // there are no negative weight cycles. for (int i=0; i<numVertices-1; i++) { // Update all estimates based on this particular edge only. for (edge e: eList) { if (estimates[e.v1]+e.w < estimates[e.v2]) estimates[e.v2] = estimates[e.v1] + e.w; } } return estimates; } } class edge { public int v1; public int v2; public int w; public edge(int a, int b, int c) { v1 = a; v2 = b; w = c; } public void negate() { w = -w; } }
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