• [算法] 带权图

    • 最小生成树（Minimum Span Tree）：对于带权无向连通图。所有节点都连通且总权值最小。应用：电缆布线、网络、电路设计
    • 找V-1条边，连接V个顶点，总权值最小
    • 切分定理（Cut Property）：给定任意切分，横切边中权值最小的边必属于最小生成树
      • 切分：把图中节点分为两部分
      • 横切边：边的两个端点属于切分的不同两边
      • 证明：反证法，假设横切边中一条权值不是最小的边属于最小生成树，给生成树添加横切边中权值最小的边形成环，删掉权值不是最小的边打破环得到新的权值更小的生成树，与假设矛盾
      • 实现：从一个点开始，不断扩散，求出最小生成树

    main.cpp（测试有权图）

     1 #include <iostream>
 2 #include <iomanip>
 3 #include "SparseGraph.h"
 4 #include "DenseGraph.h"
 5 #include "ReadGraph.h"
 6 #include "Component.h"
 7 #include "Path.h"
 8 #include "ShortestPath.h"
 9 
10 using namespace std;
11 
12 int main(){
13     
14     string filename = "testG1.txt";
15     int V = 8;
16     cout<<fixed<<setprecision(2);
17     
18     // Test Weighted Dense Graph
19     DenseGraph<double> g1 = DenseGraph<double>(V,false);
20     ReadGraph<DenseGraph<double>,double> readGraph(g1, filename);
21     g1.show();
22     cout<<endl;
23 
24     // Test Weighted Dense Graph
25     SparseGraph<double> g2 = SparseGraph<double>(V,false);
26     ReadGraph<SparseGraph<double>,double> SparseGraph(g2, filename);
27     g2.show();
28     cout<<endl;
29 
30     return 0;
31 }
    View Code

    Edge.h

     1 #ifndef INC_01_WEIGHTED_GRAPH_EDGE_H
 2 #define INC_01_WEIGHTED_GRAPH_EDGE_H
 3 
 4 #include <iostream>
 5 
 6 using namespace std;
 7 
 8 // 边 
 9 template<typename Weight>
10 class Edge{
11 private:
12     int a,b; // 边的两边 
13     Weight weight; // 边的权值 
14 public:
15     // 构造函数 
16     Edge(int a, int b, Weight weight){
17         this->a = a;
18         this->b = b;
19         this->weight = weight;
20     }
21     // 空的构造函数，所有成员变量取默认值 
22     Edge(){}
23     ~Edge(){}
24     int v(){ return a; } // 返回第一个顶点 
25     int w(){ return b; } // 返回第二个顶点 
26     Weight wt(){ return weight;} // 返回权值
27     
28     // 给定一个顶点，返回另一个顶点 
29     int other(int x){
30         assert( x == a || x == b );
31         return x == a ? b : a;
32     }
33     
34     // 输出边的信息 
35     friend ostream& operator<<(ostream &os, const Edge &e){
36         os<<e.a<<"-"<<e.b<<": "<<e.weight;
37         return os;
38     }
39     
40     // 边的大小比较，比较边的权值 
41     bool operator<(Edge<Weight>& e){
42         return weight < e.wt();
43     }
44     bool operator<=(Edge<Weight>& e){
45         return weight <= e.wt();
46     }
47     bool operator>(Edge<Weight>& e){
48         return weight > e.wt();
49     }
50     bool operator>=(Edge<Weight>& e){
51         return weight >= e.wt();
52     }
53     bool operator==(Edge<Weight>& e){
54         return weight == e.wt();
55     }
56 };
57 
58 #endif //INC_01_WEIGHTED_GRAPH_EDGE_H
    View Code

    ReadGraph.h

     1 #include <iostream>
 2 #include <string>
 3 #include <fstream>
 4 #include <sstream>
 5 #include <cassert>
 6 
 7 using namespace std;
 8 
 9     template <typename Graph, typename Weight>
10     class ReadGraph{
11         public:
12             // 从文件filename中读取图的信息，存进graph中 
13             ReadGraph(Graph &graph, const string &filename){
14                 ifstream file(filename);
15                 string line;
16                 int V,E;
17                 
18                 assert(file.is_open());
19                 
20                 // 读取图中第一行节点数和边数 
21                 assert(getline(file,line));
22                 stringstream ss(line);
23                 ss>>V>>E;
24                 
25                 assert( V == graph.V() );
26                 
27                 // 读取每一条边的信息 
28                 for( int i = 0 ; i < E ; i ++ ){
29                     
30                     assert( getline(file, line) );
31                     stringstream ss(line);
32                     
33                     int a,b;
34                     Weight w;
35                     ss>>a>>b>>w;
36                     assert( a >= 0 && a < V );
37                     assert( b >= 0 && b < V );
38                     graph.addEdge( a , b, w );
39                 }
40             }
41     };
    View Code
    • Lazy Prim：MinHeap实现，复杂度O(ElogE)，E为边数

    main.cpp（测试Lazy Prim）

     1 #include <iostream>
 2 #include <iomanip>
 3 #include "SparseGraph.h"
 4 #include "DenseGraph.h"
 5 #include "ReadGraph.h"
 6 #include "Component.h"
 7 #include "Path.h"
 8 #include "ShortestPath.h"
 9 #include "LazyPrimMST.h"
10 
11 using namespace std;
12 
13 int main(){
14     
15     string filename = "testG1.txt";
16     int V = 8;
17     SparseGraph<double> g = SparseGraph<double>(V, false);
18     ReadGraph<SparseGraph<double>,double> readGraph(g, filename);
19         
20     // Test Weighted Dense Graph
21     cout << "Test Lazy Prim MST:"<< endl;
22     LazyPrimMST<SparseGraph<double>, double> lazyPrimMST(g);
23     vector<Edge<double>> mst = lazyPrimMST.mstEdge();
24     for( int i = 0 ; i < mst.size() ; i ++ )
25         cout << mst[i] << endl;
26     cout << "The MST weight is: "<<lazyPrimMST.result()<<endl;
27 
28     cout<<endl;
29 
30     return 0;
31 }
    View Code

    LazyPrimMST.h

     1 #include "MinHeap.h"
 2 
 3 using namespace std;
 4 
 5 template<typename Graph, typename Weight>
 6 class LazyPrimMST{
 7 private:
 8     Graph &G; // 图的引用 
 9     MinHeap<Edge<Weight>> pq; // 用最小堆作为优先队列 
10     vector<Edge<Weight>> mst; // 最小生成树包含的所有边 
11     bool *marked; //  标记数组，标记节点i在运行过程中是否被访问 
12     Weight mstWeight; // 最小生成树的权 
13     
14     void visit(int v){
15         assert( !marked[v] );
16         // 将节点v标记为访问过 
17         marked[v] = true;
18         
19         typename Graph::adjIterator adj(G,v);
20         for( Edge<Weight>* e = adj.begin() ; !adj.end() ; e = adj.next() )
21             if( !marked[e->other(v)] )
22                 pq.insert(*e);
23     }
24     
25 public:
26     // 初始化，最差情况下所有边都要进入最小堆 
27     LazyPrimMST(Graph &graph):G(graph), pq(MinHeap<Edge<Weight>>(graph.E())){
28         marked = new bool[G.V()]; // 顶点个数 
29         for( int i = 0 ; i < G.V() ; i ++ )
30             marked[i] = false;
31         mst.clear();
32         
33         // Lazy Prim
34         // 时间复杂度O(ElogE)，E为边数 
35         visit(0);
36         while( !pq.isEmpty() ){
37             Edge<Weight> e = pq.extractMin();
38             // e不是横切边 
39             if( marked[e.v()] == marked[e.w()] )
40                 continue;
41             mst.push_back( e ); 
42             if( !marked[e.v()] )
43                 visit( e.v() );
44             else            
45                 visit( e.w() );     
46         }
47         mstWeight = mst[0].wt();
48         for( int i = 1 ; i < mst.size() ; i ++ )
49             mstWeight += mst[i].wt(); 
50     }    
51     
52     ~LazyPrimMST(){
53         delete[] marked; 
54     } 
55 
56     vector<Edge<Weight>> mstEdge(){
57         return mst;
58     } 
59     
60     Weight result(){
61         return mstWeight;
62     }
63 };
    View Code

    PrimMST.h

     1 #include <iostream>
 2 #include <vector>
 3 #include <cassert>
 4 #include "Edge.h"
 5 #include "IndexMinHeap.h"
 6 
 7 using namespace std;
 8 
 9 template<typename Graph, typename Weight>
10 class PrimMST{
11 private:
12     Graph &G; // 图的引用 
13     IndexMinHeap<Weight> ipq; // 最小索引堆（辅助） 
14     vector<Edge<Weight>*> edgeTo; // 访问的点所对应的边（辅助） 
15     bool *marked; // 标记数组，运行过程中节点i是否被访问 
16     vector<Edge<Weight>> mst;  // 最小生成树包含的所有边（为什么不加*） 
17     Weight mstWeight; // 最小生成树的权值 
18     void visit(int v){
19         assert( !marked[v] );
20         marked[v] = true;
21         
22         // 遍历 
23         typename Graph::adjIterator adj(G,v);
24         for( Edge<Weight>* e = adj.begin() ; !adj.end() ; e = adj.next() ){
25             // 相邻顶点 
26             int w = e->other(v);
27             // 若边的另一端未被访问 
28             if( !marked[w] ){
29                 // 如果未考虑过这个端点，将端点和与之相连的边加入索引堆 
30                 if( !edgeTo[w] ){
31                     ipq.insert(w, e->wt());
32                     edgeTo[w] = e;
33                 } 
34                 // 如果考虑过这个端点，但现在的边比之前考虑的更短，则替换 
35                 else if( e->wt() < edgeTo[w]->wt() ){
36                     edgeTo[w] = e;
37                     ipq.change(w, e->wt());
38                 }
39             }
40         }
41     }
42     
43 public:
44     PrimMST(Graph &graph):G(graph),ipq(IndexMinHeap<double>(graph.V())){
45         marked = new bool[G.V()];
46         for( int i = 0 ; i < G.V() ; i ++ ){
47             marked[i] = false;
48             edgeTo.push_back(NULL);
49         }
50         mst.clear();
51         // Prim
52         visit(0);
53         while( !ipq.isEmpty() ){
54             int v = ipq.extractMinIndex();
55             assert( edgeTo[v] );
56             mst.push_back( *edgeTo[v] );
57             visit(v);
58         } 
59         
60         mstWeight = mst[0].wt();
61         for( int i = 1 ; i < mst.size() ; i ++ )
62             mstWeight += mst[i].wt();     
63     }
64     
65     ~PrimMST(){
66         delete[] marked;
67     }
68     
69     vector<Edge<Weight>> mstEdge(){
70         return mst;
71     }
72     
73     Weight result(){
74         return mstWeight;
75     }
76 };
    View Code
    • Prim：IndexMinHeap实现，复杂度O(ElogV)，V为节点数
    • 索引堆存放当前在最小生成树中的节点与其他节点相连的边
    • 从起点开始，遍历相邻节点，更新索引堆中的权值
    • visit(7)操作后索引堆状态（0.19加入最小生成树）

     

    main_performance.cpp（测试算法性能）

      1 #include <iostream>
  2 #include <iomanip>
  3 #include "SparseGraph.h"
  4 #include "DenseGraph.h"
  5 #include "ReadGraph.h"
  6 #include "Component.h"
  7 #include "Path.h"
  8 #include "ShortestPath.h"
  9 #include "LazyPrimMST.h"
 10 #include "PrimMST.h"
 11 #include <ctime>
 12 
 13 using namespace std;
 14 
 15 int main(){
 16     
 17     string filename1 = "testG1.txt";
 18     int V1 = 8; 
 19     
 20     string filename2 = "testG2.txt";
 21     int V2 = 250;
 22     
 23     string filename3 = "testG3.txt";
 24     int V3 = 1000;
 25     
 26     string filename4 = "testG4.txt";
 27     int V4 = 10000;
 28     
 29     SparseGraph<double> g1 = SparseGraph<double>(V1, false);
 30     ReadGraph<SparseGraph<double>,double> readGraph1(g1, filename1);
 31     cout<<filename1<<" load successfully."<<endl;    
 32     
 33     SparseGraph<double> g2 = SparseGraph<double>(V2, false);
 34     ReadGraph<SparseGraph<double>,double> readGraph2(g2, filename2);
 35     cout<<filename2<<" load successfully."<<endl;
 36     
 37     SparseGraph<double> g3 = SparseGraph<double>(V3, false);
 38     ReadGraph<SparseGraph<double>,double> readGraph3(g3, filename3);
 39     cout<<filename3<<" load successfully."<<endl;
 40 
 41     SparseGraph<double> g4 = SparseGraph<double>(V4, false);
 42     ReadGraph<SparseGraph<double>,double> readGraph4(g4, filename4);
 43     cout<<filename4<<" load successfully."<<endl;
 44 
 45     cout<<endl;
 46     
 47     clock_t startTime, endTime;
 48 
 49     // Test Lazy Prim MST
 50     cout<<"Test Lazy Prim MST:"<<endl;
 51 
 52     startTime = clock();
 53     LazyPrimMST<SparseGraph<double>, double> lazyPrimMST1(g1);
 54     endTime = clock();
 55     cout<<"Test for G1: "<<(double)(endTime-startTime)/CLOCKS_PER_SEC<<" s."<<endl;
 56     
 57     startTime = clock();
 58     LazyPrimMST<SparseGraph<double>, double> lazyPrimMST2(g2);
 59     endTime = clock();
 60     cout<<"Test for G2: "<<(double)(endTime-startTime)/CLOCKS_PER_SEC<<" s."<<endl;
 61 
 62     startTime = clock();
 63     LazyPrimMST<SparseGraph<double>, double> lazyPrimMST3(g3);
 64     endTime = clock();
 65     cout<<"Test for G3: "<<(double)(endTime-startTime)/CLOCKS_PER_SEC<<" s."<<endl;
 66 
 67     startTime = clock();
 68     LazyPrimMST<SparseGraph<double>, double> lazyPrimMST4(g4);
 69     endTime = clock();
 70     cout<<"Test for G4: "<<(double)(endTime-startTime)/CLOCKS_PER_SEC<<" s."<<endl;
 71     
 72     cout<<endl;
 73     
 74     // Test Prim MST
 75     cout<<"Test Prim MST:"<<endl;
 76 
 77     startTime = clock();
 78     PrimMST<SparseGraph<double>, double> PrimMST1(g1);
 79     endTime = clock();
 80     cout<<"Test for G1: "<<(double)(endTime-startTime)/CLOCKS_PER_SEC<<" s."<<endl;
 81 
 82     startTime = clock();
 83     PrimMST<SparseGraph<double>, double> PrimMST2(g2);
 84     endTime = clock();
 85     cout<<"Test for G2: "<<(double)(endTime-startTime)/CLOCKS_PER_SEC<<" s."<<endl;
 86 
 87     startTime = clock();
 88     PrimMST<SparseGraph<double>, double> PrimMST3(g3);
 89     endTime = clock();
 90     cout<<"Test for G3: "<<(double)(endTime-startTime)/CLOCKS_PER_SEC<<" s."<<endl;
 91 
 92     startTime = clock();
 93     PrimMST<SparseGraph<double>, double> PrimMST4(g4);
 94     endTime = clock();
 95     cout<<"Test for G4: "<<(double)(endTime-startTime)/CLOCKS_PER_SEC<<" s."<<endl;    
 96     
 97     cout<<endl;
 98     
 99     return 0; 
100 }
    View Code

     

    • Kruskal：MinHeap+Union Find实现，复杂度O(ElogE)
    • 先把边按权值排序，把权最小的边加入最小生成树，并判断是否生成环，直到得到V-1条边构成的生成树
    • 如果横切边有相等的边：算法依然成立，任选一个边，图存在多个最小生成树
    • Vyssotsky's Algorithm：将边逐渐地添加到生成树中，一旦形成环，删除环中权值最大的边（没有好的数据结构支撑）

    KruskalMST.h

     1 #include <iostream>
 2 #include <vector>
 3 #include "MinHeap.h"
 4 #include "UF.h"
 5 #include "Edge.h"
 6 
 7 using namespace std;
 8 
 9 template <typename Graph, typename Weight>
10 class KruskalMST{
11     
12     private:
13         vector<Edge<Weight>> mst; // MST的所有边 
14         Weight mstWeight; // MST的权值 
15     public:
16         KruskalMST(Graph &graph){
17             MinHeap<Edge<Weight>> pq( graph.E() );
18             // 将所有边放进最小堆中，完成排序 
19             for( int i = 0 ; i < graph.V() ; i ++ ){
20                 typename Graph::adjIterator adj(graph,i);
21                 for( Edge<Weight> *e = adj.begin() ; !adj.end() ; e = adj.next() ){
22                     // 1-2 2-1 放一个 
23                     if( e->v() < e->w() )
24                     pq.insert(*e);
25                 }
26             }
27             // 创建并查集查看已访问节点的连通情况 
28             UnionFind uf(graph.V());
29             while( !pq.isEmpty() && mst.size() < graph.V() - 1 ){
30                 Edge<Weight> e = pq.extractMin();
31                 // 是否成环 
32                 if( uf.isConnected( e.v() , e.w() ))
33                     continue;
34                 mst.push_back( e );
35                 uf.unionElements( e.v() , e.w() ); 
36             }
37             
38             mstWeight = mst[0].wt();
39             for( int i = 1 ; i < mst.size() ; i ++ )
40                 mstWeight += mst[i].wt(); 
41         }
42         ~KruskalMST(){
43             
44         }
45         // 返回MST的所有边 
46         vector<Edge<Weight>> mstEdge(){
47             return mst;
48         }
49         // 返回MST的权值 
50         Weight result(){
51             return mstWeight; 
52         }
53 };
    View Code
    • 单源最短路径：最短路径树（所有顶点距离起始顶点权值最小）
    • 广度优先遍历求出了无向图中的单源最短路径
    • 松弛操作（Relaxation）：找到一条经过更多顶点但总权值更小的路径。是最短路径求解的核心操作

    • dijkstra：IndexMinHeap实现，复杂度O(ElogV)。可解决有/无向图的单源最短路径问题（无向图相当于每条边保存方向相反的两条边），要求图中不能有负权边
    • 访问距上个点最短的点，遍历邻边，Relaxation，更新IndexMinHeap

    main.cpp（测试dijkstra算法）

     1 #include <iostream>
 2 #include "SparseGraph.h"
 3 #include "DenseGraph.h"
 4 #include "ReadGraph.h"
 5 #include "Dijkstra.h"
 6 
 7 using namespace std;
 8 
 9 int main(){
10     
11     string filename = "testG1.txt";
12     int V = 5;
13     SparseGraph<int> g = SparseGraph<int>(V, true);
14     ReadGraph<SparseGraph<int>,int> readGraph(g, filename);
15         
16     cout<<"Test Dijkstra:"<<endl<<endl ;
17     Dijkstra<SparseGraph<int>, int> dij(g,0);
18     for( int i = 0 ; i < V ; i ++ ){
19         if(dij.hasPathTo(i)){
20             cout<<"Shortest Path to "<<i<<" : "<<dij.shortestPathTo(i)<<endl;
21             dij.showPath(i);
22         }
23         else
24             cout<<"No Path to "<<i<<endl;
25         cout<<"-----------"<<endl;
26     }
27     return 0;
28 }
    View Code

    dijkstra.h

      1 #include <iostream>
  2 #include <vector>
  3 #include <stack>
  4 #include "Edge.h"
  5 #include "IndexMinHeap.h"
  6 
  7 using namespace std;
  8 
  9 template<typename Graph, typename Weight>
 10 class Dijkstra{
 11     private:
 12         Graph &G;
 13         int s; // 起始点 
 14         Weight *distTo; // distTo[i]记录从s到i的最短路径长度 
 15         bool *marked; // marked[i]记录节点i是否被访问 
 16         vector<Edge<Weight>*> from; // from[i]记录到达i的边是哪条
 17                                     // 用于恢复最短路径
 18                                     // 使用*便于初始化赋空值 
 19         
 20     public:
 21         Dijkstra(Graph &graph, int s):G(graph){
 22             assert( s >= 0 && s < G.V() );
 23             this->s = s;
 24             distTo = new Weight[G.V()];
 25             marked = new bool[G.V()];
 26             for( int i = 0 ; i < G.V() ; i ++ ){
 27                 // 初始化为默认值
 28                 distTo[i] = Weight();
 29                 marked[i] = false;
 30                 from.push_back(NULL); 
 31             }
 32             // 索引堆记录当前找到的到达每个顶点的最短距离 
 33             IndexMinHeap<Weight> ipq(G.V());
 34             // Dijkstra
 35             // 初始化起始点s 
 36             distTo[s] = Weight();
 37             from[s] = new Edge<Weight>(s, s, Weight());
 38             ipq.insert(s, distTo[s] ); 
 39             marked[s] = true;
 40             ipq.insert( s , distTo[s] );
 41             while( !ipq.isEmpty() ){
 42                 int v = ipq.extractMinIndex();
 43                 // distTo[v]是s到v的最短距离
 44                 marked[v] = true;
 45                 // 松弛操作
 46                 // 访问v的所有邻边
 47                 typename Graph::adjIterator adj(G, v);
 48                 for( Edge<Weight>* e = adj.begin() ; !adj.end() ; e = adj.next() ){
 49                     int w = e->other(v);
 50                     // 若s到w的最短路径还未找到 
 51                     if( !marked[w] ){
 52                         // 若w以前未访问过
 53                         // 或访问过，但通过当前v点到w点距离更短，则更新 
 54                         if( from[w] == NULL || distTo[v] + e->wt() < distTo[w] ){
 55                             distTo[w] = distTo[v] + e->wt();
 56                             from[w] = e; 
 57                             if( ipq.contain(w) )
 58                                 ipq.change(w, distTo[w]);
 59                             else
 60                                 ipq.insert(w, distTo[w]);    
 61                         }
 62                     }
 63                 } 
 64             }
 65         }
 66     
 67     ~Dijkstra(){
 68         delete[] distTo;
 69         delete[] marked;
 70         delete from[0];
 71     } 
 72     
 73     // 返回从s到w的最短路径长度    
 74     Weight shortestPathTo( int w ){
 75         assert( w >= 0 && w < G.V() );
 76         assert( hasPathTo(w) );
 77         return distTo[w];
 78     }
 79     // 判断从s到w是否连通 
 80     bool hasPathTo( int w ){
 81         assert( w >= 0 && w < G.V() );
 82         return marked[w];
 83     }
 84     // 寻找从s到w的最短路径，将整个路径经过的边放入vec 
 85     void shortestPath( int w, vector<Edge<Weight>> &vec){
 86         assert( w >= 0 && w < G.V() );
 87         assert( hasPathTo(w) );
 88         // 通过from数组逆向查找从s到w的路径，存入栈中 
 89         stack<Edge<Weight>*> s;
 90         Edge<Weight> *e = from[w];
 91         while( e->v() != e->w() ){
 92             s.push(e);
 93             e = from[e->v()];
 94         }
 95         // 从栈取出元素，获得顺序的从s到w的路径 
 96         while( !s.empty() ){
 97             e = s.top();
 98             vec.push_back( *e );
 99             s.pop();
100         }
101     }
102     // 打印从s到w的路径 
103     void showPath( int w ){
104         assert( w >= 0 && w < G.V() );
105         vector<Edge<Weight>> vec;
106         shortestPath(w, vec);
107         for( int i = 0 ; i < vec.size() ; i ++ ){
108             cout << vec[i].v() << " -> ";
109             if( i == vec.size()-1 )
110                 cout << vec[i].w() << endl;
111         }
112     }
113 };
    View Code

    • 负权边问题：本质上仍是松弛操作
    • 如果一个图有负权环，则不存在最短路径，如下图的1-2
    • Bellman-Ford单源最短路径算法：可判断图中是否有负权环，运行前不需检测。复杂度O(EV)
    • 若一个图没有负权环，则从一个点到另一点的最短路径，最多经过所有的V个顶点，有V-1条边，否则存在顶点经过了两次，既存在负权环
    • 对一个点的一次松弛操作，就是找到经过这个点的另外一条路径，多一条边，权值更小；若图没有负权环，从一个点到另外一点的最短路径，最多经过所有的V个顶点，有V-1条边；对所有点进行V-1次松弛操作，即可找到从原点到其他所有点的最短路径；如果还可以继续松弛，则原图中有负权环
    • 适用于有向图，若是无向图，负边自身构成负权环

     

     

     main.cpp（测试Bellman-Ford）

     1 #include <iostream>
 2 #include "SparseGraph.h"
 3 #include "DenseGraph.h"
 4 #include "ReadGraph.h"
 5 #include "BellmanFord1.h"
 6 
 7 using namespace std;
 8 
 9 // 测试Bellman-Ford算法
10 int main() {
11     string filename = "testG2.txt";
12     //string filename = "testG_negative_circle.txt";
13     int V = 5;
14     SparseGraph<int> g = SparseGraph<int>(V, true);
15     ReadGraph<SparseGraph<int>, int> readGraph(g, filename);
16     cout<<"Test Bellman-Ford:"<<endl<<endl;
17     int s = 0;
18     BellmanFord<SparseGraph<int>, int> bellmanFord(g, s);
19     if( bellmanFord.negativeCycle() )
20         cout<<"The graph contain negative cycle!"<<endl;
21     else
22         for( int i = 0 ; i < V ; i ++ ) {
23             if(i == s)
24                 continue;
25             if (bellmanFord.hasPathTo(i)) {
26                 cout << "Shortest Path to " << i << " : " << bellmanFord.shortestPathTo(i) << endl;
27                 bellmanFord.showPath(i);
28             }
29             else
30                 cout << "No Path to " << i << endl;
31             cout << "----------" << endl;
32         }
33     return 0;
34 }
    View Code

    BellmanFord.h

      1 #include <stack>
  2 #include <vector>
  3 #include "Edge.h"
  4 
  5 using namespace std;
  6 
  7 template <typename Graph, typename Weight>
  8 class BellmanFord{
  9     private:
 10         Graph &G;
 11         int s; // 起始点 
 12         Weight* distTo; // distTo[i]为从起始点s到i的最短路径长度 
 13         vector<Edge<Weight>*> from; // from[i]为最短路径中，到达i的是哪条边 
 14         bool hasNegativeCycle;    // 是否有负权环 
 15         // 判断是否有负权环 
 16         bool detectNegativeCycle(){
 17             for( int i = 0 ; i < G.V() ; i ++ ){
 18                 typename Graph::adjIterator adj(G,i);
 19                 for( Edge<Weight>* e = adj.begin() ; !adj.end() ; e = adj.next() )
 20                     if( from[e->v()] && distTo[e->v()] + e->wt() < distTo[e->w()] )
 21                         return true;
 22             }
 23             return false;
 24         }
 25         
 26     public:
 27         BellmanFord(Graph &graph, int s):G(graph){
 28             this->s = s;
 29             distTo = new Weight[G.V()];
 30             // 初始化，所有节点s都不可达 
 31             for( int i = 0 ; i < G.V() ; i ++ )
 32                 from.push_back(NULL);
 33             // 设置distTo[s] = 0，from[s]不为NULL，表示初始点s可达且距离为0 
 34             distTo[s] = Weight();
 35             from[s] = new Edge<Weight>(s, s, Weight());
 36             // Bellman-Ford
 37             // 进行V-1轮松弛操作，每次求出从起点到其余所有点，最多用pass步可到达的最短距离 
 38             for( int pass = 1 ; pass < G.V() ; pass ++ ){
 39                 // 每次循环中对所有边进行一遍松弛操作
 40                 // 先遍历所有顶点，然后遍历和所有顶点相邻的所有边
 41                 for( int i = 0 ; i < G.V() ; i ++ ){
 42                     typename Graph::adjIterator adj(G,i);
 43                     for( Edge<Weight>* e = adj.begin() ; !adj.end() ; e = adj.next() )
 44                         // e为i的邻边 
 45                         // 对每个边首先判断e->v()是否到过 
 46                         // 如果e->w()以前没有到达过，则更新distTo[e->w()] 
 47                         // 或虽然e->w()以前到达过，但通过这个e可获得一个更短的距离
 48                         // 即进行一次松弛操作，更新distTo[e->w()]
 49                         if( from[e->v()] && (!from[e->w()] || distTo[e->v()] + e->wt() < distTo[e->w()])){
 50                             distTo[e->w()] = distTo[e->v()] + e->wt();
 51                             // 通过e到达e->w() 
 52                             from[e->w()] = e;
 53                         }
 54                 } 
 55             }
 56             hasNegativeCycle = detectNegativeCycle();
 57         }
 58         ~BellmanFord(){
 59             delete[] distTo;
 60             delete from[s];
 61         }
 62         // 返回图中是否有负环 
 63         bool negativeCycle(){
 64             return hasNegativeCycle;
 65         }
 66         // 返回s到w的最短路径长度
 67         Weight shortestPathTo( int w ){
 68             assert( w >= 0 && w < G.V() );
 69             assert( !hasNegativeCycle );
 70             assert( hasPathTo(w) );
 71             return distTo[w];
 72         }
 73         // 判断从s到w是否连通
 74         bool hasPathTo( int w ){
 75             assert( w >= 0 && w < G.V() );
 76             return from[w] != NULL;
 77         } 
 78         // 从s到w的最短路径，将经过的边放在vec中
 79         void shortestPath( int w, vector<Edge<Weight>> &vec ){
 80             // w不越界 
 81             assert( w >= 0 && w < G.V() );
 82             // 无负权环 
 83             assert( !hasNegativeCycle );
 84             assert( hasPathTo(w) );
 85             // 通过from逆向查找从s到w的路径，存在栈中
 86             stack<Edge<Weight>*> s;
 87             Edge<Weight> *e = from[w];
 88             while( e->v() != this->s ){
 89                 s.push(e);
 90                 e = from[e->v()];
 91             } 
 92             s.push(e);
 93             // 从栈中依次取出元素，获得顺序的从s到w的路径
 94             while( !s.empty() ){
 95                 e = s.top();
 96                 vec.push_back( *e );
 97                 s.pop();
 98             } 
 99         }
100             // 打印从s到w的路径
101             void showPath(int w){
102                 assert( w >= 0 && w < G.V() );
103                 assert( !hasNegativeCycle);
104                 assert( hasPathTo(w) );
105                 
106                 vector<Edge<Weight>> vec;
107                 shortestPath(w,vec);
108                 for( int i = 0 ; i < vec.size() ; i ++ ){
109                     cout << vec[i].v()<<" -> ";
110                     if( i == vec.size()-1 )
111                         cout << vec[i].w() << endl; 
112                 }
113             } 
114 };
    View Code

    • 单源最短路径算法对比（指定起点s）

    　　dijkstra　　无负权边　　有向无向图均可　　O(ElogV)

    　　Bellman-Ford　　无负权环　　有向图　　O(VE)

    　　利用拓扑排序　　有向无环图　　有向图　　O(V+E)

    • 所有对最短路径算法（任意两点a、b）
      • Floyed算法，处理无负权环的图，复杂度O(V^3)
    • 最长路径算法
      • 不能有正权环
      • 无权图的最长路径问题是指数级难度
      • 有权图，不能使用Dijkstra求最长路径
      • 可使用Bellman-Ford
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  • 原文地址：https://www.cnblogs.com/cxc1357/p/12260451.html
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