Description
We will use the following (standard) definitions from graph theory. Let V be a nonempty and finite set, its elements being called vertices (or nodes). Let E be a subset of the Cartesian product V×V, its elements being called edges. Then G=(V,E) is called a directed graph.
Let n be a positive integer, and let p=(e1,...,en) be a sequence of length n of edges ei∈E such that ei=(vi,vi+1) for a sequence of vertices (v1,...,vn+1). Then p is called a path from vertex v1 to vertex vn+1 in G and we say that vn+1 is reachable from v1, writing (v1→vn+1).
Here are some new definitions. A node v in a graph G=(V,E) is called a sink, if for every node w in G that is reachable from v, v is also reachable from w. The bottom of a graph is the subset of all nodes that are sinks, i.e., bottom(G)={v∈V|∀w∈V:(v→w)⇒(w→v)}. You have to calculate the bottom of certain graphs.
Let n be a positive integer, and let p=(e1,...,en) be a sequence of length n of edges ei∈E such that ei=(vi,vi+1) for a sequence of vertices (v1,...,vn+1). Then p is called a path from vertex v1 to vertex vn+1 in G and we say that vn+1 is reachable from v1, writing (v1→vn+1).
Here are some new definitions. A node v in a graph G=(V,E) is called a sink, if for every node w in G that is reachable from v, v is also reachable from w. The bottom of a graph is the subset of all nodes that are sinks, i.e., bottom(G)={v∈V|∀w∈V:(v→w)⇒(w→v)}. You have to calculate the bottom of certain graphs.
Input
The input contains several test cases, each of which corresponds to a directed graph G. Each test case starts with an integer number v, denoting the number of vertices of G=(V,E), where the vertices will be identified by the integer numbers in the set V={1,...,v}. You may assume that 1<=v<=5000. That is followed by a non-negative integer e and, thereafter, e pairs of vertex identifiers v1,w1,...,ve,we with the meaning that (vi,wi)∈E. There are no edges other than specified by these pairs. The last test case is followed by a zero.
Output
For each test case output the bottom of the specified graph on a single line. To this end, print the numbers of all nodes that are sinks in sorted order separated by a single space character. If the bottom is empty, print an empty line. 

Sample Input
3 3 1 3 2 3 3 1 2 1 1 2 0
Sample Output
1 3 2
#include<iostream>
#include<cstdio>
#include<cstring>
#include<algorithm>
using namespace std;
const int maxn=100000;
struct edge
{
int t,w;//u->t=w;
int next;
};
int V,E;//点数(从1开始),边数
int p[maxn],pf[maxn];//邻接表原图,逆图
edge G[maxn],Gf[maxn];//邻接表原图,逆图
int l,lf;
void init()
{
memset(p,-1,sizeof(p));
memset(pf,-1,sizeof(pf));
l=lf=0;
}
void addedge(int u,int t,int w,int l)
{
G[l].w=w;
G[l].t=t;
G[l].next=p[u];
p[u]=l;
}
void addedgef(int u,int t,int w,int l)
{
Gf[l].w=w;
Gf[l].t=t;
Gf[l].next=pf[u];
pf[u]=l;
}
///Kosaraju算法,返回为强连通分量个数
bool flag[maxn]; //访问标志数组
int belg[maxn]; //存储强连通分量,其中belg[i]表示顶点i属于第belg[i]个强连通分量
int numb[maxn]; //结束时间(出栈顺序)标记,其中numb[i]表示离开时间为i的顶点
//用于第一次深搜,求得numb[1..n]的值
void VisitOne(int cur, int &sig)
{
flag[cur] = true;
for (int i=p[cur];i!=-1;i=G[i].next)
{
if (!flag[G[i].t])
{
VisitOne(G[i].t,sig);
}
}
numb[++sig] = cur;
}
//用于第二次深搜,求得belg[1..n]的值
void VisitTwo(int cur, int sig)
{
flag[cur] = true;
belg[cur] = sig;
for (int i=pf[cur];i!=-1;i=Gf[i].next)
{
if (!flag[Gf[i].t])
{
VisitTwo(Gf[i].t,sig);
}
}
}
//Kosaraju算法,返回为强连通分量个数
int Kosaraju_StronglyConnectedComponent()
{
int i, sig;
//第一次深搜
memset(flag,0,sizeof(flag));
for ( sig=0,i=1; i<=V; ++i )
{
if ( false==flag[i] )
{
VisitOne(i,sig);
}
}
//第二次深搜
memset(flag,0,sizeof(flag));
for ( sig=0,i=V; i>0; --i )
{
if ( false==flag[numb[i]] )
{
VisitTwo(numb[i],++sig);
}
}
return sig;
}
//缩点
int n;//缩点后的点个数1~n
int g[maxn];
edge eg[maxn];//邻接表
int re;
int cont[maxn];
int out[maxn];
void dinit(int sig)
{
memset(g,-1,sizeof(g));
n=sig;
re=0;
memset(out,0,sizeof(out));
memset(cont,0,sizeof(cont));//1~n 第sig块强联通分量中的点数
}
void addedge0(int u,int t,int w,int l)
{
eg[l].w=w;
eg[l].t=t;
eg[l].next=g[u];
g[u]=l;
}
int main()
{
while(scanf("%d",&V)==1&&V)
{
scanf("%d",&E);
init();
for(int i=0;i<E;i++)
{
int u,t,w=1;scanf("%d%d",&u,&t);
addedge(u,t,w,l++);
addedgef(t,u,w,lf++);
}
int ans=Kosaraju_StronglyConnectedComponent();
//printf("%d/n",ans);
///缩点
dinit(ans);
for(int i=1;i<=V;i++)//构图
{
for(int j=p[i];j!=-1;j=G[j].next)
{
int st=belg[i],ed=belg[G[j].t];
if(st!=ed)
{
addedge0(st,ed,1,re++);
}
}
}
//计算每块强联通分量中的点个数
for(int i=1;i<=V;i++)
{
cont[belg[i]]++;
}
//计算DAG图中各点的出度
for(int i=1;i<=n;i++)
{
for(int j=g[i];j!=-1;j=eg[j].next)
{
out[i]++;
}
}
/*
先求图中的强连通分支,缩点,如果一个连通分支的出度为0,则这个连通分支中的所
有点都满足条件,输出即可(如果一个连通分支中有一个点可以到达该连通分支以外的
点,则该连通分支中的所有点都不满足条件)
*/
int f=0;
for(int i=1;i<=V;i++)
{
if(out[belg[i]]==0)
{
if(f==0)
{
printf("%d",i);f=1;
}
else printf(" %d",i);
}
}printf("/n");
}
return 0;
}
本文介绍了一种基于图论的算法,利用Kosaraju算法寻找图中的强连通分量,并通过缩点操作进一步分析图的结构特征。

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