Kruskal 最小生成树算法

对于一个给定的连通的无向图 G = (V, E),希望找到一个无回路的子集 T,T 是 E 的子集,它连接了所有的顶点,且其权值之和为最小。

因为 T 无回路且连接所有的顶点,所以它必然是一棵树,称为生成树(Spanning Tree),因为它生成了图 G。显然,由于树 T 连接了所有的顶点,所以树 T 有 V - 1 条边。一张图 G 可以有很多棵生成树,而把确定权值最小的树 T 的问题称为最小生成树问题(Minimum Spanning Tree)。术语 "最小生成树" 实际上是 "最小权值生成树" 的缩写。

Kruskal 算法提供一种在 O(ElogV) 运行时间确定最小生成树的方案。Kruskal 算法基于贪心算法(Greedy Algorithm)的思想进行设计,其选择的贪心策略就是,每次都选择权重最小的但未形成环路的边加入到生成树中。其算法结构如下:

  1. 将所有的边按照权重非递减排序;
  2. 选择最小权重的边,判断是否其在当前的生成树中形成了一个环路。如果环路没有形成,则将该边加入树中,否则放弃。
  3. 重复步骤 2,直到有 V - 1 条边在生成树中。

上述步骤 2 中使用了 Union-Find 算法来判断是否存在环路。

例如,下面是一个无向连通图 G。

图 G 中包含 9 个顶点和 14 条边,所以期待的最小生成树应包含 (9 - 1) = 8 条边。

首先对所有的边按照权重的非递减顺序排序:

Weight Src Dest
1 7 6
2 8 2
2 6 5
4 0 1
4 2 5
6 8 6
7 2 3
7 7 8
8 0 7
8 1 2
9 3 4
10 5 4
11 1 7
14 3 5

然后从排序后的列表中选择权重最小的边。

1. 选择边 {7, 6},无环路形成,包含在生成树中。

2. 选择边 {8, 2},无环路形成,包含在生成树中。

3. 选择边 {6, 5},无环路形成,包含在生成树中。

4. 选择边 {0, 1},无环路形成,包含在生成树中。

5. 选择边 {2, 5},无环路形成,包含在生成树中。

6. 选择边 {8, 6},有环路形成,放弃。

7. 选择边 {2, 3},无环路形成,包含在生成树中。

8. 选择边 {7, 8},有环路形成,放弃。

9. 选择边 {0, 7},无环路形成,包含在生成树中。

10. 选择边 {1, 2},有环路形成,放弃。

11. 选择边 {3, 4},无环路形成,包含在生成树中。

12. 由于当前生成树中已经包含 V - 1 条边,算法结束。

C# 实现的 Kruskal 算法如下。

  1 using System;
  2 using System.Collections.Generic;
  3 using System.Linq;
  4 
  5 namespace GraphAlgorithmTesting
  6 {
  7   class Program
  8   {
  9     static void Main(string[] args)
 10     {
 11       Graph g = new Graph(9);
 12       g.AddEdge(0, 1, 4);
 13       g.AddEdge(0, 7, 8);
 14       g.AddEdge(1, 2, 8);
 15       g.AddEdge(1, 7, 11);
 16       g.AddEdge(2, 3, 7);
 17       g.AddEdge(2, 5, 4);
 18       g.AddEdge(8, 2, 2);
 19       g.AddEdge(3, 4, 9);
 20       g.AddEdge(3, 5, 14);
 21       g.AddEdge(5, 4, 10);
 22       g.AddEdge(6, 5, 2);
 23       g.AddEdge(8, 6, 6);
 24       g.AddEdge(7, 6, 1);
 25       g.AddEdge(7, 8, 7);
 26 
 27       Console.WriteLine();
 28       Console.WriteLine("Graph Vertex Count : {0}", g.VertexCount);
 29       Console.WriteLine("Graph Edge Count : {0}", g.EdgeCount);
 30       Console.WriteLine();
 31 
 32       Console.WriteLine("Is there cycle in graph: {0}", g.HasCycle());
 33       Console.WriteLine();
 34 
 35       Edge[] mst = g.Kruskal();
 36       Console.WriteLine("MST Edges:");
 37       foreach (var edge in mst)
 38       {
 39         Console.WriteLine("\t{0}", edge);
 40       }
 41 
 42       Console.ReadKey();
 43     }
 44 
 45     class Edge
 46     {
 47       public Edge(int begin, int end, int weight)
 48       {
 49         this.Begin = begin;
 50         this.End = end;
 51         this.Weight = weight;
 52       }
 53 
 54       public int Begin { get; private set; }
 55       public int End { get; private set; }
 56       public int Weight { get; private set; }
 57 
 58       public override string ToString()
 59       {
 60         return string.Format(
 61           "Begin[{0}], End[{1}], Weight[{2}]",
 62           Begin, End, Weight);
 63       }
 64     }
 65 
 66     class Subset
 67     {
 68       public int Parent { get; set; }
 69       public int Rank { get; set; }
 70     }
 71 
 72     class Graph
 73     {
 74       private Dictionary<int, List<Edge>> _adjacentEdges
 75         = new Dictionary<int, List<Edge>>();
 76 
 77       public Graph(int vertexCount)
 78       {
 79         this.VertexCount = vertexCount;
 80       }
 81 
 82       public int VertexCount { get; private set; }
 83 
 84       public IEnumerable<int> Vertices { get { return _adjacentEdges.Keys; } }
 85 
 86       public IEnumerable<Edge> Edges
 87       {
 88         get { return _adjacentEdges.Values.SelectMany(e => e); }
 89       }
 90 
 91       public int EdgeCount { get { return this.Edges.Count(); } }
 92 
 93       public void AddEdge(int begin, int end, int weight)
 94       {
 95         if (!_adjacentEdges.ContainsKey(begin))
 96         {
 97           var edges = new List<Edge>();
 98           _adjacentEdges.Add(begin, edges);
 99         }
100 
101         _adjacentEdges[begin].Add(new Edge(begin, end, weight));
102       }
103 
104       private int Find(Subset[] subsets, int i)
105       {
106         // find root and make root as parent of i (path compression)
107         if (subsets[i].Parent != i)
108           subsets[i].Parent = Find(subsets, subsets[i].Parent);
109 
110         return subsets[i].Parent;
111       }
112 
113       private void Union(Subset[] subsets, int x, int y)
114       {
115         int xroot = Find(subsets, x);
116         int yroot = Find(subsets, y);
117 
118         // Attach smaller rank tree under root of high rank tree
119         // (Union by Rank)
120         if (subsets[xroot].Rank < subsets[yroot].Rank)
121           subsets[xroot].Parent = yroot;
122         else if (subsets[xroot].Rank > subsets[yroot].Rank)
123           subsets[yroot].Parent = xroot;
124 
125         // If ranks are same, then make one as root and increment
126         // its rank by one
127         else
128         {
129           subsets[yroot].Parent = xroot;
130           subsets[xroot].Rank++;
131         }
132       }
133 
134       public bool HasCycle()
135       {
136         Subset[] subsets = new Subset[VertexCount];
137         for (int i = 0; i < subsets.Length; i++)
138         {
139           subsets[i] = new Subset();
140           subsets[i].Parent = i;
141           subsets[i].Rank = 0;
142         }
143 
144         // Iterate through all edges of graph, find subset of both
145         // vertices of every edge, if both subsets are same, 
146         // then there is cycle in graph.
147         foreach (var edge in this.Edges)
148         {
149           int x = Find(subsets, edge.Begin);
150           int y = Find(subsets, edge.End);
151 
152           if (x == y)
153           {
154             return true;
155           }
156 
157           Union(subsets, x, y);
158         }
159 
160         return false;
161       }
162 
163       public Edge[] Kruskal()
164       {
165         // This will store the resultant MST
166         Edge[] mst = new Edge[VertexCount - 1];
167 
168         // Step 1: Sort all the edges in non-decreasing order of their weight
169         // If we are not allowed to change the given graph, we can create a copy of
170         // array of edges
171         var sortedEdges = this.Edges.OrderBy(t => t.Weight);
172         var enumerator = sortedEdges.GetEnumerator();
173 
174         // Allocate memory for creating V ssubsets
175         // Create V subsets with single elements
176         Subset[] subsets = new Subset[VertexCount];
177         for (int i = 0; i < subsets.Length; i++)
178         {
179           subsets[i] = new Subset();
180           subsets[i].Parent = i;
181           subsets[i].Rank = 0;
182         }
183 
184         // Number of edges to be taken is equal to V-1
185         int e = 0;
186         while (e < VertexCount - 1)
187         {
188           // Step 2: Pick the smallest edge. And increment the index
189           // for next iteration
190           Edge nextEdge;
191           if (enumerator.MoveNext())
192           {
193             nextEdge = enumerator.Current;
194 
195             int x = Find(subsets, nextEdge.Begin);
196             int y = Find(subsets, nextEdge.End);
197 
198             // If including this edge does't cause cycle, include it
199             // in result and increment the index of result for next edge
200             if (x != y)
201             {
202               mst[e++] = nextEdge;
203               Union(subsets, x, y);
204             }
205             else
206             {
207               // Else discard the nextEdge
208             }
209           }
210         }
211 
212         return mst;
213       }
214     }
215   }
216 }

输出结果如下:

参考资料

本篇文章《Kruskal 最小生成树算法》由 Dennis Gao 发表自博客园,未经作者本人同意禁止任何形式的转载,任何自动或人为的爬虫转载行为均为耍流氓。

posted @ 2015-01-31 09:22  sangmado  阅读(10209)  评论(2编辑  收藏  举报