21.boost Ford最短路径算法(效率低)

到某个节点最近距离                  最短路径当前节点的父节点

完整代码

#include <iostream>
#include <string>
#include <utility>
#include <vector>
#include <deque>
#include <boost/graph/adjacency_list.hpp>
//A*寻路算法
#include <boostgraphastar_search.hpp>
//dijsktra
#include <boostgraphdijkstra_shortest_paths.hpp>
//bellman-Ford算法
#include <boostgraphellman_ford_shortest_paths.hpp>
using namespace std;
using namespace boost;


void main()
{
    //定义节点和边的相关对象和属性
    enum { u, v, x, y, z, N };
    char name[] = { 'u', 'v', 'x', 'y', 'z' };
    typedef std::pair < int, int >E;
    E edge_array[] = { E(u, y), E(u, x), E(u, v), E(v, u),
        E(x, y), E(x, v), E(y, v), E(y, z), E(z, u), E(z, x) };
    int weights[] = { -4, 8, 5, -2, 9, -3, 7, 2, 6, 7 };
    int num_arcs = sizeof(edge_array) / sizeof(E);

    //定义所用的图种类和相关类型
    typedef adjacency_list < vecS, vecS, directedS,
        no_property, property < edge_weight_t, int > > Graph;
    //生成图对象
    Graph g(edge_array, edge_array + num_arcs, weights, N);
    graph_traits < Graph >::edge_iterator ei, ei_end;

    //distance用于放置依近到远的路径距离
    std::vector<int> distance(N, (std::numeric_limits < short >::max)());
    //parent用于放置最短路径生成树的各个顶点的父节点
    std::vector<std::size_t> parent(N);
    for (int i = 0; i < N; ++i)
        parent[i] = i;


    //将源点z对应距离设为0
    distance[z] = 0;
    //应用Bellman-Ford算法
    bool r = bellman_ford_shortest_paths
    (g, int(N), weight_map(get(edge_weight, g)).distance_map(&distance[0]).
        predecessor_map(&parent[0]));

    if (r)
    {
        std::cout << "源点z到各点的最短路径
";
        std::cout << "目的点	" << "最短路径	" << "最短路径树的父节点:
";
        for (int i = 0; i < N; ++i)
            std::cout << name[i] << ": 	" << distance[i]
            << "		" << name[parent[i]] << std::endl;
    }
    else
        std::cout << "negative cycle" << std::endl;
    
    system("pause");
}