# 贪心算法——最小生成树

## 二、Prim算法

1 -> 3 : 1

3 -> 6 : 4

6 -> 4: 2

3 -> 2 : 5

2 -> 5 : 3

/* 主题：贪心算法——最小生成树（Prim）
* 作者：chinazhangjie
* 邮箱：chinajiezhang@gmail.com
* 开发语言： C++
* 开发环境： Virsual Studio 2005
* 时间: 2010.11.30
*/

#include
<iostream>
#include
<vector>
#include
<limits>
using namespace std ;

struct TreeNode
{
public:
TreeNode (
int nVertexIndexA = 0, int nVertexIndexB = 0, int nWeight = 0)
: m_nVertexIndexA (nVertexIndexA),
m_nVertexIndexB (nVertexIndexB),
m_nWeight (nWeight)
{ }
public:
int m_nVertexIndexA ;
int m_nVertexIndexB ;
int m_nWeight ;
} ;

class MST_Prim
{
public:
MST_Prim (
const vector<vector<int> >& vnGraph)
{
m_nvGraph
= vnGraph ;
m_nNodeCount
= (int)m_nvGraph.size () ;
}
void DoPrim ()
{
// 是否被访问标志
vector<bool> bFlag (m_nNodeCount, false) ;
bFlag[
0] = true ;

int nMaxIndexA ;
int nMaxIndexB ;
int j = 0 ;
while (j < m_nNodeCount - 1) {
int nMaxWeight = numeric_limits<int>::max () ;
// 找到当前最短路径
int i = 0 ;
while (i < m_nNodeCount) {
if (!bFlag[i]) {
++ i ;
continue ;
}
for (int j = 0; j < m_nNodeCount; ++ j) {
if (!bFlag[j] && nMaxWeight > m_nvGraph[i][j]) {
nMaxWeight
= m_nvGraph[i][j] ;
nMaxIndexA
= i ;
nMaxIndexB
= j ;
}
}
++ i ;
}
bFlag[nMaxIndexB]
= true ;
m_tnMSTree.push_back (TreeNode(nMaxIndexA, nMaxIndexB, nMaxWeight)) ;
++ j ;
}
// 输出结果
for (vector<TreeNode>::const_iterator ite = m_tnMSTree.begin() ;
ite
!= m_tnMSTree.end() ;
++ ite ) {
cout
<< (*ite).m_nVertexIndexA << "->"
<< (*ite).m_nVertexIndexB << " : "
<< (*ite).m_nWeight << endl ;
}
}
private:
vector
<vector<int> > m_nvGraph ; // 无向连通图
vector<TreeNode> m_tnMSTree ; // 最小生成树
int m_nNodeCount ;
} ;

int main()
{
const int cnNodeCount = 6 ;
vector
<vector<int> > graph (cnNodeCount) ;
for (size_t i = 0; i < graph.size() ; ++ i) {
graph[i].resize (cnNodeCount, numeric_limits
<int>::max()) ;
}
graph[
0][1]= 6 ;
graph[
0][2] = 1 ;
graph[
0][3] = 5 ;
graph[
1][2] = 5 ;
graph[
1][4] = 3 ;
graph[
2][3] = 5 ;
graph[
2][4] = 6 ;
graph[
2][5] = 4 ;
graph[
3][5] = 2 ;
graph[
4][5] = 6 ;

graph[
1][0]= 6 ;
graph[
2][0] = 1 ;
graph[
3][0] = 5 ;
graph[
2][1] = 5 ;
graph[
4][1] = 3 ;
graph[
3][2] = 5 ;
graph[
4][2] = 6 ;
graph[
5][2] = 4 ;
graph[
5][3] = 2 ;
graph[
5][4] = 6 ;

MST_Prim mstp (graph) ;
mstp.DoPrim () ;
return 0 ;
}

## 三、Kruskal算法

1）首先将G的n个顶点看成n个孤立的连通分支。将所有的边按权从小大排序。

（2）从第一条边开始，依边权递增的顺序检查每一条边。并按照下述方法连接两个不同的连通分支：当查看到第k条边(v,w)时，如果端点v和w分别是当前两个不同的连通分支T1和T2的端点是，就用边(v,w)将T1和T2连接成一个连通分支，然后继续查看第k+1条边；如果端点v和w在当前的同一个连通分支中，就直接再查看k+1条边。这个过程一个进行到只剩下一个连通分支时为止。

Kruskal算法的选边过程

1 -> 3 : 1

4 -> 6 : 2

2 -> 5 : 3

3 -> 4 : 4

2 -> 3 : 5

/* 主题：贪心算法之最小生成树(Kruskal算法)
* 作者：chinazhangjie
* 邮箱：chinajiezhang@gmail.com
* 开发语言：C++
* 开发环境：Visual Studio 2005
* 时间：2010.12.01
*/

#include
<iostream>
#include
<vector>
#include
<queue>
#include
<limits>
using namespace std ;

struct TreeNode
{
public:
TreeNode (
int nVertexIndexA = 0, int nVertexIndexB = 0, int nWeight = 0)
: m_nVertexIndexA (nVertexIndexA),
m_nVertexIndexB (nVertexIndexB),
m_nWeight (nWeight)
{ }
friend
bool operator < (const TreeNode& lth, const TreeNode& rth)
{
return lth.m_nWeight > rth.m_nWeight ;
}

public:
int m_nVertexIndexA ;
int m_nVertexIndexB ;
int m_nWeight ;
} ;

// 并查集
class UnionSet
{
public:
UnionSet (
int nSetEleCount)
: m_nSetEleCount (nSetEleCount)
{
__init() ;
}
// 合并i，j。如果i，j同在集合中，返回false。否则返回true
bool Union (int i, int j)
{
int ifather = __find (i) ;
int jfather = __find (j) ;
if (ifather == jfather )
{
return false ;
// copy (m_nvFather.begin(), m_nvFather.end(), ostream_iterator<int> (cout, " "));
// cout << endl ;
}
else
{
m_nvFather[jfather]
= ifather ;
// copy (m_nvFather.begin(), m_nvFather.end(), ostream_iterator<int> (cout, " "));
// cout << endl ;
return true ;
}

}

private:
// 初始化并查集
int __init()
{
m_nvFather.resize (m_nSetEleCount) ;
for (vector<int>::size_type i = 0 ;
i
< m_nSetEleCount;
++ i )
{
m_nvFather[i]
= static_cast<int>(i) ;
// cout << m_nvFather[i] << " " ;
}
// cout << endl ;
return 0 ;
}
// 查找index元素的父亲节点 并且压缩路径长度
int __find (int nIndex)
{
if (nIndex == m_nvFather[nIndex])
{
return nIndex;
}
return m_nvFather[nIndex] = __find (m_nvFather[nIndex]);
}

private:
vector
<int> m_nvFather ; // 父亲数组
vector<int>::size_type m_nSetEleCount ; // 集合中结点个数
} ;

class MST_Kruskal
{
typedef priority_queue
<TreeNode> MinHeap ;
public:
MST_Kruskal (
const vector<vector<int> >& graph)
{
m_nNodeCount
= static_cast<int>(graph.size ()) ;
__getMinHeap (graph) ;
}
void DoKruskal ()
{
UnionSet us (m_nNodeCount) ;
int k = 0 ;
while (m_minheap.size() != 0 && k < m_nNodeCount - 1)
{
TreeNode tn
= m_minheap.top () ;
m_minheap.pop () ;
// 判断合理性
if (us.Union (tn.m_nVertexIndexA, tn.m_nVertexIndexB))
{
m_tnMSTree.push_back (tn) ;
++ k ;
}
}
// 输出结果
for (size_t i = 0; i < m_tnMSTree.size() ; ++ i)
{
cout
<< m_tnMSTree[i].m_nVertexIndexA << "->"
<< m_tnMSTree[i].m_nVertexIndexB << " : "
<< m_tnMSTree[i].m_nWeight
<< endl ;
}
}

private:
void __getMinHeap (const vector<vector<int> >& graph)
{
for (int i = 0; i < m_nNodeCount; ++ i)
{
for (int j = 0; j < m_nNodeCount; ++ j)
{
if (graph[i][j] != numeric_limits<int>::max())
{
m_minheap.push (TreeNode(i, j, graph[i][j])) ;
}
}
}
}
private:
vector
<TreeNode> m_tnMSTree ;
int m_nNodeCount ;
MinHeap m_minheap ;
} ;

int main ()
{
const int cnNodeCount = 6 ;
vector
<vector<int> > graph (cnNodeCount) ;
for (size_t i = 0; i < graph.size() ; ++ i)
{
graph[i].resize (cnNodeCount, numeric_limits
<int>::max()) ;
}
graph[
0][1]= 6 ;
graph[
0][2] = 1 ;
graph[
0][3] = 3 ;
graph[
1][2] = 5 ;
graph[
1][4] = 3 ;
graph[
2][3] = 5 ;
graph[
2][4] = 6 ;
graph[
2][5] = 4 ;
graph[
3][5] = 2 ;
graph[
4][5] = 6 ;

graph[
1][0]= 6 ;
graph[
2][0] = 1 ;
graph[
3][0] = 3 ;
graph[
2][1] = 5 ;
graph[
4][1] = 3 ;
graph[
3][2] = 5 ;
graph[
4][2] = 6 ;
graph[
5][2] = 4 ;
graph[
5][3] = 2 ;
graph[
5][4] = 6 ;

MST_Kruskal mst (graph);
mst.DoKruskal () ;
}

posted @ 2010-12-02 12:37  独酌逸醉  阅读(19482)  评论(5编辑  收藏