http://blog.csdn.net/dark_scope/article/details/8880547
发现这个博客里面写的匈牙利算法比较简单易懂
/*==================================================*
| 二分图匹配(匈牙利算法DFS 实现)
| INIT: g[][]邻接矩阵;
| CALL: res = MaxMatch();
| 优点:实现简洁容易理解,适用于稠密图,DFS找增广路快。
| 找一条增广路的复杂度为O(E),最多找V条增广路,故时间复杂度为O(VE)
*==================================================*/
const int MAXN = 1000;
int uN, vN; // u, v数目,要初始化!!!
bool g[MAXN][MAXN]; // g[i][j] 表示xi与yj相连
int xM[MAXN], yM[MAXN]; // 输出量
bool chk[MAXN]; // 辅助量检查某轮y[v]是否被check
bool SearchPath(int u)
{
int v;
for(v = 0; v < vN; v++)
if(g[u][v] && !chk[v])
{
chk[v] = true;
if(yM[v] == -1 || SearchPath(yM[v]))
{
yM[v] = u; xM[u] = v;
return true ;
}
}
return false ;
}
int MaxMatch()
{
int u, ret = 0 ;
memset(xM, -1, sizeof (xM));
memset(yM, -1, sizeof (yM));
for(u = 0; u < uN; u++)
if(xM[u] == -1)
{
memset(chk, false, sizeof (chk));
if(SearchPath(u)) ret++;
}
return ret;
/*==================================================*
| 二分图匹配(匈牙利算法BFS 实现)
| INIT: g[][]邻接矩阵;
| CALL: res = MaxMatch();Nx, Ny初始化!!!
| 优点:适用于稀疏二分图,边较少,增广路较短。
| 匈牙利算法的理论复杂度是O(VE)
*==================================================*/
const int MAXN = 1000;
int g[MAXN][MAXN], Mx[MAXN], My[MAXN], Nx, Ny;
int chk[MAXN], Q[MAXN], prev[MAXN];
int MaxMatch(void)
{
int res = 0;
int qs, qe;
memset(Mx, -1, sizeof(Mx));
memset(My, -1, sizeof(My));
memset(chk, -1, sizeof(chk));
for (int i = 0; i < Nx; i++)
{
if (Mx[i] == -1){
qs = qe = 0;
Q[qe++] = i;
prev[i] = -1;
bool flag = 0;
while (qs < qe && !flag)
{
int u = Q[qs];
for (int v = 0; v < Ny && !flag; v++)
if (g[u][v] && chk[v] != i)
{
chk[v] = i; Q[qe++] = My[v];
if (My[v] >= 0) prev[My[v]] = u;
else
{
flag = 1;
int d = u, e = v;
while (d != -1)
{
int t = Mx[d];
Mx[d] = e; My[e] = d;
d = prev[d]; e = t;
}
}
}
qs++;
}
if (Mx[i] != -1) res++;
}
}
return res;
}
anytime you feel the pain.hey,refrain.don't carry the world upon your shoulders