深度优先与广度优先算法

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图的遍历有深度优先和广度优先算法。

深度优先遍历可描述为一个递归算法。当到达顶点v时,具体操作是:

①访问(v);

②for(与v相邻的每个顶点w)

遍历(w);

//深度优先算法template<int max_size>void Diagraph<max_size>::depth_first(void(*visit)(Vertex &)) const {bool visited[max_size]; //引入数组防止无限循环Vertex v;for (all v in G) visited[v] = false;for (all v in G) {if (!visited[v]) {traverse(v, visited, visit);}}}template<int max_size>void Diagraph<max_size>::traverse(Vertex &v, bool visited[],void (*visit)(Vertex &)) const {Vertex w;visited[v] = true;(*visit)(v);for (all w adjacent to v) {if (!visited[w]) {traverse(w, visited, visit);}}}

广度优先算法借助队列,当访问v后, 将v相邻的仍未访问过的顶点加到队列后面,然后访问队列头:

//广度优先算法template<int max_size>void Diagraph<max_size>::breadth_first(void (*visit)(Vertex &)) const {Queue q;bool visited[max_size];Vertex v, w, x;for (all v in G) visited[v] = false;for (all v in G) {if (!visited[v]) {q.append(v);while (!q.empty()) {q.retrieve(w);if (!visited[w]) {visited[w] = true;(*visit) (w);for (all x adjacent to w) {q.append(x);}}q.serve();}}}}


可以使用深度优先遍历和广度优先遍历确定拓扑次序。

深度优先遍历: 时间复杂度O(n+e)(n为图的定点数,e为图的边数)。

//深度优先算法template<int graph_size>void Diagraph<graph_size>:: depth_sort(List<Vertex>&topological_order) {bool visited[graph_size];Vertex v;for (v = 0; v < count; v++) visited[v] = false;topological_order.clear();for (v = 0; v < count; v++) {if (!visited[v]) {recursive_depth_sort(v, visited, topological_order);}}}template<int max_size>void Diagraph<max_size>::recursive_depth_sort(Vertex v, bool *visited, List<Vertex>& topological_order) {visited[v] = true;int degree = neighbors[v].size();for (int i = 0; i < degree; i++) {Vertex w;neighbors[v].retrieve(i, w);if (!visited[w]) {recursive_depth_sort(w, visited, topological_order);}}topological_order.insert(0, v);}



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