Hopcroft–最大匹配|集2的Karp算法(实现)

我们强烈建议将以下帖子作为先决条件。 Hopcroft–最大匹配|集1的Karp算法(简介)

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在我们开始实施之前,有几件重要的事情需要注意。

  1. 我们需要 找到一条扩展路径 (在匹配边和不匹配边之间交替的路径,以自由顶点作为起点和终点)。
  2. 一旦我们找到了交替的路径,我们需要 将找到的路径添加到现有匹配 .此处添加路径意味着,将此路径上的前一条匹配边设置为不匹配,将前一条不匹配边设置为匹配。

其思想是使用BFS(广度优先搜索)来寻找增广路径。由于BFS逐层遍历,因此它用于将图划分为匹配边和不匹配边的层。添加一个虚拟顶点NIL,该顶点连接到左侧的所有顶点和右侧的所有顶点。下面的数组用于查找扩充路径。到零的距离初始化为INF(无限)。如果我们从虚拟顶点开始,然后使用不同顶点的交替路径返回到它,那么就有一条增广路径。

  1. pairU[]:大小为m+1的数组,其中m是二部图左侧的顶点数。pairU[u]如果u匹配,则在右侧存储一对u,否则为零。
  2. pairV[]:大小为n+1的数组,其中n是二部图右侧的顶点数。如果v匹配,则pairV[v]在左侧存储一对v,否则为零。
  3. dist[]:大小为m+1的数组,其中m是二部图左侧的顶点数。如果不匹配,dist[u]初始化为0,否则初始化为INF(无限)。NIL的dist[]也被初始化为INF

一旦找到增广路径,就会使用DFS(深度优先搜索)将增广路径添加到当前匹配中。DFS只是遵循BFS设置的距离数组。如果在BFS中v与u相邻,则填充pairU[u]和pairV[v]中的值。

下面是上述Hopkroft-Karp算法的实现。

C++14

// C++ implementation of Hopcroft Karp algorithm for
// maximum matching
#include<bits/stdc++.h>
using namespace std;
#define NIL 0
#define INF INT_MAX
// A class to represent Bipartite graph for Hopcroft
// Karp implementation
class BipGraph
{
// m and n are number of vertices on left
// and right sides of Bipartite Graph
int m, n;
// adj[u] stores adjacents of left side
// vertex 'u'. The value of u ranges from 1 to m.
// 0 is used for dummy vertex
list< int > *adj;
// These are basically pointers to arrays needed
// for hopcroftKarp()
int *pairU, *pairV, *dist;
public :
BipGraph( int m, int n); // Constructor
void addEdge( int u, int v); // To add edge
// Returns true if there is an augmenting path
bool bfs();
// Adds augmenting path if there is one beginning
// with u
bool dfs( int u);
// Returns size of maximum matching
int hopcroftKarp();
};
// Returns size of maximum matching
int BipGraph::hopcroftKarp()
{
// pairU[u] stores pair of u in matching where u
// is a vertex on left side of Bipartite Graph.
// If u doesn't have any pair, then pairU[u] is NIL
pairU = new int [m+1];
// pairV[v] stores pair of v in matching. If v
// doesn't have any pair, then pairU[v] is NIL
pairV = new int [n+1];
// dist[u] stores distance of left side vertices
// dist[u] is one more than dist[u'] if u is next
// to u'in augmenting path
dist = new int [m+1];
// Initialize NIL as pair of all vertices
for ( int u=0; u<=m; u++)
pairU[u] = NIL;
for ( int v=0; v<=n; v++)
pairV[v] = NIL;
// Initialize result
int result = 0;
// Keep updating the result while there is an
// augmenting path.
while (bfs())
{
// Find a free vertex
for ( int u=1; u<=m; u++)
// If current vertex is free and there is
// an augmenting path from current vertex
if (pairU[u]==NIL && dfs(u))
result++;
}
return result;
}
// Returns true if there is an augmenting path, else returns
// false
bool BipGraph::bfs()
{
queue< int > Q; //an integer queue
// First layer of vertices (set distance as 0)
for ( int u=1; u<=m; u++)
{
// If this is a free vertex, add it to queue
if (pairU[u]==NIL)
{
// u is not matched
dist[u] = 0;
Q.push(u);
}
// Else set distance as infinite so that this vertex
// is considered next time
else dist[u] = INF;
}
// Initialize distance to NIL as infinite
dist[NIL] = INF;
// Q is going to contain vertices of left side only.
while (!Q.empty())
{
// Dequeue a vertex
int u = Q.front();
Q.pop();
// If this node is not NIL and can provide a shorter path to NIL
if (dist[u] < dist[NIL])
{
// Get all adjacent vertices of the dequeued vertex u
list< int >::iterator i;
for (i=adj[u].begin(); i!=adj[u].end(); ++i)
{
int v = *i;
// If pair of v is not considered so far
// (v, pairV[V]) is not yet explored edge.
if (dist[pairV[v]] == INF)
{
// Consider the pair and add it to queue
dist[pairV[v]] = dist[u] + 1;
Q.push(pairV[v]);
}
}
}
}
// If we could come back to NIL using alternating path of distinct
// vertices then there is an augmenting path
return (dist[NIL] != INF);
}
// Returns true if there is an augmenting path beginning with free vertex u
bool BipGraph::dfs( int u)
{
if (u != NIL)
{
list< int >::iterator i;
for (i=adj[u].begin(); i!=adj[u].end(); ++i)
{
// Adjacent to u
int v = *i;
// Follow the distances set by BFS
if (dist[pairV[v]] == dist[u]+1)
{
// If dfs for pair of v also returns
// true
if (dfs(pairV[v]) == true )
{
pairV[v] = u;
pairU[u] = v;
return true ;
}
}
}
// If there is no augmenting path beginning with u.
dist[u] = INF;
return false ;
}
return true ;
}
// Constructor
BipGraph::BipGraph( int m, int n)
{
this ->m = m;
this ->n = n;
adj = new list< int >[m+1];
}
// To add edge from u to v and v to u
void BipGraph::addEdge( int u, int v)
{
adj[u].push_back(v); // Add u to v’s list.
}
// Driver Program
int main()
{
BipGraph g(4, 4);
g.addEdge(1, 2);
g.addEdge(1, 3);
g.addEdge(2, 1);
g.addEdge(3, 2);
g.addEdge(4, 2);
g.addEdge(4, 4);
cout << "Size of maximum matching is " << g.hopcroftKarp();
return 0;
}


JAVA

// Java implementation of Hopcroft Karp
// algorithm for maximum matching
import java.util.ArrayList;
import java.util.Arrays;
import java.util.LinkedList;
import java.util.List;
import java.util.Queue;
class GFG{
static final int NIL = 0 ;
static final int INF = Integer.MAX_VALUE;
// A class to represent Bipartite graph
// for Hopcroft Karp implementation
static class BipGraph
{
// m and n are number of vertices on left
// and right sides of Bipartite Graph
int m, n;
// adj[u] stores adjacents of left side
// vertex 'u'. The value of u ranges
// from 1 to m. 0 is used for dummy vertex
List<Integer>[] adj;
// These are basically pointers to arrays
// needed for hopcroftKarp()
int [] pairU, pairV, dist;
// Returns size of maximum matching
int hopcroftKarp()
{
// pairU[u] stores pair of u in matching where u
// is a vertex on left side of Bipartite Graph.
// If u doesn't have any pair, then pairU[u] is NIL
pairU = new int [m + 1 ];
// pairV[v] stores pair of v in matching. If v
// doesn't have any pair, then pairU[v] is NIL
pairV = new int [n + 1 ];
// dist[u] stores distance of left side vertices
// dist[u] is one more than dist[u'] if u is next
// to u'in augmenting path
dist = new int [m + 1 ];
// Initialize NIL as pair of all vertices
Arrays.fill(pairU, NIL);
Arrays.fill(pairV, NIL);
// Initialize result
int result = 0 ;
// Keep updating the result while
// there is an augmenting path.
while (bfs())
{
// Find a free vertex
for ( int u = 1 ; u <= m; u++)
// If current vertex is free and there is
// an augmenting path from current vertex
if (pairU[u] == NIL && dfs(u))
result++;
}
return result;
}
// Returns true if there is an augmenting
// path, else returns false
boolean bfs()
{
// An integer queue
Queue<Integer> Q = new LinkedList<>();
// First layer of vertices (set distance as 0)
for ( int u = 1 ; u <= m; u++)
{
// If this is a free vertex,
// add it to queue
if (pairU[u] == NIL)
{
// u is not matched
dist[u] = 0 ;
Q.add(u);
}
// Else set distance as infinite
// so that this vertex is
// considered next time
else
dist[u] = INF;
}
// Initialize distance to
// NIL as infinite
dist[NIL] = INF;
// Q is going to contain vertices
// of left side only.
while (!Q.isEmpty())
{
// Dequeue a vertex
int u = Q.poll();
// If this node is not NIL and
// can provide a shorter path to NIL
if (dist[u] < dist[NIL])
{
// Get all adjacent vertices of
// the dequeued vertex u
for ( int i : adj[u])
{
int v = i;
// If pair of v is not considered
// so far (v, pairV[V]) is not yet
// explored edge.
if (dist[pairV[v]] == INF)
{
// Consider the pair and add
// it to queue
dist[pairV[v]] = dist[u] + 1 ;
Q.add(pairV[v]);
}
}
}
}
// If we could come back to NIL using
// alternating path of distinct vertices
// then there is an augmenting path
return (dist[NIL] != INF);
}
// Returns true if there is an augmenting
// path beginning with free vertex u
boolean dfs( int u)
{
if (u != NIL)
{
for ( int i : adj[u])
{
// Adjacent to u
int v = i;
// Follow the distances set by BFS
if (dist[pairV[v]] == dist[u] + 1 )
{
// If dfs for pair of v also returns
// true
if (dfs(pairV[v]) == true )
{
pairV[v] = u;
pairU[u] = v;
return true ;
}
}
}
// If there is no augmenting path
// beginning with u.
dist[u] = INF;
return false ;
}
return true ;
}
// Constructor
@SuppressWarnings ( "unchecked" )
public BipGraph( int m, int n)
{
this .m = m;
this .n = n;
adj = new ArrayList[m + 1 ];
Arrays.fill(adj, new ArrayList<>());
}
// To add edge from u to v and v to u
void addEdge( int u, int v)
{
// Add u to v’s list.
adj[u].add(v);
}
}
// Driver code
public static void main(String[] args)
{
BipGraph g = new BipGraph( 4 , 4 );
g.addEdge( 1 , 2 );
g.addEdge( 1 , 3 );
g.addEdge( 2 , 1 );
g.addEdge( 3 , 2 );
g.addEdge( 4 , 2 );
g.addEdge( 4 , 4 );
System.out.println( "Size of maximum matching is " +
g.hopcroftKarp());
}
}
// This code is contributed by sanjeev2552


输出:

Size of maximum matching is 4

上述实现主要采用的是在的Wiki页面上提供的算法 霍普克罗夫特-卡普算法 . 本文由 古普塔 。如果您发现任何不正确的地方,或者您想分享有关上述主题的更多信息,请发表评论

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