图的搜索算法

在游戏中，常常遇到路径规划问题，用到图的相关算法，我们以简单图来学习。

图通常有两种表示方式，矩阵和邻接表。矩阵表示简单，运算快，但当矩阵是稀疏矩阵的时候就存在空间浪费的问题，并且效率也会下降，而邻接表节约空间，并且由于边是连续访问，时间效率也比较高。在本文中，我们将以邻接表来表示图。

#include<queue>#include<stack>using namespace std;struct SE{int vIndex;int tag;SE* next;};struct SMap{SE* pE;int nnode;};void visit(SE *se){printf("%d\n", se->vIndex);}SMap* create_map(int matrix[][6], int n){SMap* pMap = new SMap();pMap->nnode = n;pMap->pE = new SE[n];memset(pMap->pE, 0, n*sizeof(SE));for (int i = 0; i<n; i++){pMap->pE[i].vIndex = i;pMap->pE[i].tag = 0;SE* p = &pMap->pE[i];for (int j = 0; j<n; j++){if (matrix[i][j] != 0){p->next = new SE();p->next->vIndex = j;p->next->tag = 0;p->next->next = NULL;p = p->next;}}}return pMap;}int BFS(SMap* pMap, int n){queue<SE*> q;for (int i = 0; i < n; i++){if (pMap->pE[i].tag == 0){q.push(&pMap->pE[i]);while (!q.empty()){SE *se = q.front();q.pop();if (pMap->pE[se->vIndex].tag == 1){continue;}visit(se);pMap->pE[se->vIndex].tag = 1;SE * p = se;while (p->next){p = p->next;if (pMap->pE[p->vIndex].tag == 0){q.push(p);}}}}}return 0;}int DFS(SMap* pMap, int n){stack<SE*> s;for (int i = 0; i < n; i++){if (pMap->pE[i].tag == 0){s.push(&pMap->pE[i]);while (!s.empty()){SE *se = s.top();s.pop();if (pMap->pE[se->vIndex].tag == 1){continue;}visit(se);pMap->pE[se->vIndex].tag = 1;SE * p = &pMap->pE[se->vIndex];stack<SE*> tmp;while (p->next){p = p->next;if (pMap->pE[p->vIndex].tag == 0){tmp.push(p);}}while (!tmp.empty()){s.push(tmp.top());tmp.pop();}}}}return 0;}int main(){int map[6][6] = {{ 0, 1, 0, 1, 0, 0 },{ 1, 0, 1, 1, 1, 0 },{ 0, 1, 0, 1, 0, 0 },{ 1, 1, 1, 0, 1, 0 },{ 0, 1, 0, 1, 0, 1 },{ 0, 0, 0, 0, 1, 0 }};SMap* smap = create_map(map, 6);//BFS(smap, 6);DFS(smap, 6);return 0;}