普里姆算法的应用场景为修路问题,就是用最小的路径连接所有节点
转换一下就是最小生成树(MST)的问题:给定一个带权的无向连接图,如何选取一颗生成树,使树上的所有的边上权的总和为最小,就是最小生成树
普里姆算法求最小生成树:在包含n个顶点的连接图中,找出只有(n-1)条边并包含所有n个顶点的连通子图,即极小连通子图
过程:
设G={V,E}是连通网,T={U,D}是最小生成树,V,U是顶点的集合,E,D是边的集合
从顶点u开始构造最小生成树,则从V中取出u放到U中,并标记顶点v的visited[u]=1
若集合U中顶点u和V中顶点之间存在边,则寻找最小边,并不构成回路,将此节点加入U中并将边加到D中
重复第2步骤,知道U,V相等(就是所有顶点被访问过),此时D中则有n-1条边
import java.util.Arrays; public class PrimAlgorithm { public static void main(String[] args) { char[] data = new char[]{'A', 'B', 'C', 'D', 'E', 'F', 'G'}; int verxs = data.length; int[][] weight = new int[][]{ {10000, 5, 7, 10000, 10000, 10000, 2}, {5, 10000, 10000, 9, 10000, 10000, 3}, {7, 10000, 10000, 10000, 8, 10000, 10000}, {10000, 9, 10000, 10000, 10000, 4, 10000}, {10000, 10000, 8, 10000, 10000, 5, 4}, {10000, 10000, 10000, 4, 5, 10000, 6}, {2, 3, 10000, 10000, 4, 6, 10000}, }; MGraph graph = new MGraph(verxs); MinTree minTree = new MinTree(); minTree.createGraph(graph, verxs, data, weight); minTree.showGraph(graph); minTree.prim(graph,0); } } class MinTree { /** * @param graph 图对象 * @param verxs 图对应的顶点个数 * @param date 图的各个顶点的值 * @param weight 图的邻接矩阵 */ public void createGraph(MGraph graph, int verxs, char[] date, int[][] weight) { int i, j; for (i = 0; i < verxs; i++) { graph.data[i] = date[i]; for (j = 0; j < verxs; j++) { graph.weight[i][j] = weight[i][j]; } } } public void showGraph(MGraph graph) { for (int[] link : graph.weight) { System.out.println(Arrays.toString(link)); } } /** * prim算法生成最小树 * * @param graph 图 * @param v 从第几个节点生成 */ public void prim(MGraph graph, int v) { //标记节点是否访问过 int[] visited = new int[graph.verxs]; visited[v] = 1; //记录两个节点的下标 int h1 = -1; int h2 = -1; int minWeight = 10000; //循环节点数-1次 for (int k = 1; k < graph.verxs; k++) { for (int i = 0; i < graph.verxs; i++) {//i被访问的节点 for (int j = 0; j < graph.verxs; j++) {//j没有被访问的节点 if (visited[i] == 1 && visited[j] == 0 && graph.weight[i][j] < minWeight) { //替换 minWeight minWeight = graph.weight[i][j]; h1 = i; h2 = j; } } } System.out.println("边<" + graph.data[h1] + "," + graph.data[h2] + "> 权值=" + minWeight); visited[h2] = 1; minWeight = 10000; } } } class MGraph { int verxs;//节点数 char[] data;//节点数据 int[][] weight;//边 (邻接矩阵) public MGraph(int verxs) { this.verxs = verxs; data = new char[verxs]; weight = new int[verxs][verxs]; } }