多应用+插件架构,代码干净,二开方便,首家独创一键云编译技术,文档视频完善,免费商用码云13.8K 广告
      对一个**有向无环图**(Directed Acyclic Graph简称DAG)G进行拓扑排序,是将G中所有顶点排成一个线性序列,使得图中任意一对顶点u和v,若边(u,v)∈E(G),则u在线性序列中出现在v之前。通常,这样的线性序列称为满足拓扑次序(Topological Order)的序列,简称拓扑序列。简单的说,由某个集合上的一个偏序得到该集合上的一个全序,这个操作称之为**拓扑排序**。(摘抄自:[拓扑排序-百度百科](http://baike.baidu.com/link?url=LQa-nm5WHvlG9AFeR27hZOvYN3HCyfgyLZiVFzh6TfULibSs3QGawKSwR5_dzy58dN7fx6H56zGyfoGA57Z2fq))。       首先对于一个优先图需要先判断是否存在环,然后再进行拓扑排序操作。如何判断有向图是否存在环呢,参考:[有向图是否有环](http://blog.csdn.net/u012796139/article/details/49863539)。 ![](https://box.kancloud.cn/2016-08-17_57b429234fa00.jpg) **源代码**示例: ~~~ #include <iostream> #include <vector> #include <stack> #include <algorithm> using namespace std; class Digraph { public: Digraph(size_t nvertax) : arr(nvertax), vertaxs(nvertax), edges(0) {} void addEdge(size_t a, size_t b); void removeEdge(size_t a, size_t b); void addVertax(size_t v); void removeVertax(size_t v); Digraph reverse() const; vector<size_t> adj(size_t v) const; void showAdj(size_t v) const; void showDigraph() const; size_t edge() const { return edges; } size_t vertax() const { return vertaxs; } size_t arrSize() const { return arr.size(); } private: vector<vector<size_t>> arr; // 邻接表 size_t vertaxs; // 顶点个数 size_t edges; // 边的个数 }; /// 使用深度优先遍历在有向图中寻找有向环 class DirectedCycle { public: DirectedCycle(const Digraph &graph) : marked(graph.arrSize()), edgeto(graph.arrSize()), on_stack(graph.arrSize()) { for (size_t i = 0; i < graph.arrSize(); i++) marked[i] = on_stack[i] = false; for (size_t i = 0; i < graph.arrSize(); i++) { if (!marked[i]) dfs(graph, i); } } bool hasCycle() const { return !sta.empty(); } stack<size_t> cycle() const { return sta; } private: void dfs(const Digraph &graph, size_t v) { on_stack[v] = true; marked[v] = true; vector<size_t> vec = graph.adj(v); for (size_t i = 0; i < vec.size(); i++) { if (this->hasCycle()) return; else if (!marked[vec[i]]) { edgeto[vec[i]] = v; dfs(graph, vec[i]); } else if (on_stack[vec[i]]) { for (size_t x = v; x != vec[i]; x = edgeto[x]) sta.push(x); sta.push(vec[i]); sta.push(v); } } on_stack[v] = false; } vector<bool> marked; vector<size_t> edgeto; vector<bool> on_stack; stack<size_t> sta; }; /// 有向图中基于深度优先遍历的顶点排序,保证图中没有有向环 class DepthFirstOrder { public: DepthFirstOrder(const Digraph &graph) : marked(graph.arrSize()) { for (size_t i = 0; i < marked.size(); i++) marked[i] = false; for (size_t i = 0; i < graph.arrSize(); i++) { if (!marked[i]) dfs(graph, i); } } vector<size_t> getPre() const { return pre; } vector<size_t> getPost() const { return post; } stack<size_t> getReversePost() const { return reverse_post; } private: void dfs(const Digraph &graph, size_t v) { marked[v] = true; pre.push_back(v); vector<size_t> vec = graph.adj(v); for (size_t i = 0; i < vec.size(); i++) { if (!marked[vec[i]]) dfs(graph, vec[i]); } post.push_back(v); reverse_post.push(v); } vector<bool> marked; vector<size_t> pre; // 所有顶点的前序排列 vector<size_t> post; // 所有顶点的后序排列 stack<size_t> reverse_post; // 所有顶点的逆后序排列 }; /// 拓扑排序,借助于DepthFirstOrder来实现,保证图中没有环 class Topological { public: Topological(const Digraph &graph) { DepthFirstOrder dfs(graph); stack<size_t> sta = dfs.getReversePost(); while (!sta.empty()) { order.push_back(sta.top()); sta.pop(); } } vector<size_t> getOrder() const { return order; } private: vector<size_t> order; // 顶点的拓扑顺序 }; int main(void) { Digraph graph(13); graph.addEdge(0, 1); graph.addEdge(0, 5); graph.addEdge(0, 6); graph.addEdge(2, 0); graph.addEdge(2, 3); graph.addEdge(3, 5); graph.addEdge(5, 4); graph.addEdge(6, 4); graph.addEdge(6, 9); graph.addEdge(7, 6); graph.addEdge(8, 7); graph.addEdge(9, 10); graph.addEdge(9, 11); graph.addEdge(9, 12); graph.addEdge(11, 12); cout << graph.vertax() << endl; cout << graph.edge() << endl; graph.showDigraph(); cout << endl; DirectedCycle cycle(graph); stack<size_t> sta; if (cycle.hasCycle()) { cout << "graph has cycle" << endl; sta = cycle.cycle(); while (!sta.empty()) { cout << sta.top() << " "; sta.pop(); } cout << endl; } else cout << "graph hasn't cycle" << endl; Topological topo(graph); vector<size_t> vec = topo.getOrder(); for (size_t i = 0; i < vec.size(); i++) cout << vec[i] << " "; cout << endl; system("pause"); return 0; } void Digraph::addEdge(size_t a, size_t b) { if (!(a < vertax() && b < vertax())) return; arr[a].push_back(b); edges++; } void Digraph::removeEdge(size_t a, size_t b) { if (!(a < vertax() && b < vertax())) return; vector<size_t>::iterator iter = find(arr[a].begin(), arr[a].end(), b); if (iter != arr[a].end()) { arr[a].erase(iter); edges--; } } void Digraph::addVertax(size_t v) { if (v != arrSize()) return; arr.push_back(vector<size_t>()); vertaxs++; } void Digraph::removeVertax(size_t v) { if (v >= arrSize()) return; vector<size_t>::iterator iter; for (size_t i = 0; i < arrSize(); i++) { if (i == v) { edges -= arr[i].size(); // 减去头部是v的边的个数 arr[i].clear(); vertaxs--; } else { iter = find(arr[i].begin(), arr[i].end(), v); if (iter != arr[i].end()) { arr[i].erase(iter); edges--; } } } } Digraph Digraph::reverse() const { Digraph graph(vertax()); vector<size_t> vec; for (size_t i = 0; i < arrSize(); i++) { vec = adj(i); for (size_t j = 0; j < vec.size(); j++) { graph.addEdge(vec[j], i); // 取得该图的反向图 } } return graph; } vector<size_t> Digraph::adj(size_t v) const { if (v < arrSize()) return arr[v]; else vector<size_t>(); } void Digraph::showAdj(size_t v) const { if (v >= arrSize()) return; vector<size_t> vec = adj(v); for (size_t i = 0; i < vec.size(); i++) cout << vec[i] << " "; cout << endl; } void Digraph::showDigraph() const { for (size_t i = 0; i < arr.size(); i++) { cout << i << ": "; showAdj(i); } } ~~~ **参考资料**:       1、[https://github.com/luoxn28/algorithm_data_structure](https://github.com/luoxn28/algorithm_data_structure) (里面有常用的数据结构源代码,图相关算法在graph文件夹中)       2、《算法 第4版》 图有关章节