Upcoming SlideShare
×
Like this presentation? Why not share!

Like this? Share it with your network

Share

# Greedy minimum spanning tree- prim's algorithm

• 242 views

More in: Engineering , Technology
• Comment goes here.
Are you sure you want to
Be the first to comment
Be the first to like this

Total Views
242
On Slideshare
242
From Embeds
0
Number of Embeds
0

Shares
5
0
Likes
0

No embeds

### Report content

No notes for slide

### Transcript

• 1. Greedy Minimum Spanning Tree: Prim's Algorithm 研究⽣生：鍾聖彥 教授： 許慶昇 ⽼老師
• 2. Key ingredients of greedy algorithms • Optimal substructure: An optimal solution to the problem contains within it optimal solutions to subproblems. • Greedy-choice property: We can assemble a globally optimal solution by making locally optimal (greedy) choices.
• 3. 什麼問題可以使⽤用greedy algorithm來解? 1.如果做出⼀一個choice之後,  可以找到剩下要解的單⼀一個 subproblem     2.Greedy-choice property(必須證明最佳解裡⾯面⼀一定有 greedy choice) 3.有optimal substructure (必須證明⼤大問題的最佳解裡 ⾯面有⼩小問題的最佳解)
• 4. Graphs
• 5. EXAMPLE：Weighted graph Ａ Ｃ Ｄ Ｆ Ｅ Ｂ Ｇ Ｈ
• 6. Spanning Tree(⽣生成樹)
• 7. Minimum Spanning Tree Ａ Ｃ Ｄ Ｆ Ｅ Ｂ Ｇ Ｈ ⺫⽬目的：移除weighted graph中的部份邊線，使得⼦子圖仍然 保持連通性，且邊線weight總和為最⼩小 權重最⼩小的⽣生成樹就是最⼩小⽣生成樹
• 8. Application
• 9. Optimal substructure • ⼀一、兩棵 MST ，要合併成⼀一棵 MST 時，以兩棵 MST 之間權重最⼩小 的邊進⾏行連結，當然會是最好的。 • ⼆二、三棵 MST ，要合併成⼀一棵 MST 時，先連結其中兩棵連結權重 最⼩小的 MST ，然後才連結第三棵，總是⽐比較好。 • 三、⼀一個單獨的點，可以視作⼀一棵 MST 。 • 由以上三點，可以歸納出⼀一個 greedy 演算法：以權重最⼩小的邊連結 各棵 MST ，⼀一定⽐比較好。
• 10. Optimal substructure MST T
• 11. Optimal substructure MST T Remove any edge (u,v) ∈ T
• 12. Optimal substructure MST T Remove any edge (u,v) ∈ T. Then it is partitioned into two subtrees T1 and T2 T1 T2
• 13. Optimal substructure MST T Theorem. The subtree T1 is MST of G1 = (V1,E1),the subgragh of G induced by the vertex of T1 Similarly for T2 T1 T2 G1
• 14. Proof of Optimal substructure MST T T1 T2 G1 w(T) = w(u, v) + w(T1) + w(T2) If T1′ were a lower-weight spanning treat than T1 for G1, then T′ = {(u, v)} ∪ T1′ ∪ T2 would be a lower-weight spanning tree than T of G
• 15. –Greedy Agorithm Greedy-choice property" A locally optimal choice is globally optimal
• 16. Theorem Let T be the MST of G = (V,E), and let A ⊆ V. Suppose that (u,v)∈ E is the least-weight edge connecting A to V-A, then (u,v)∈ T The proof is by contradiction(⽭矛盾) Cut-and-Paste is a way used in prooﬁng graph theory concepts, Idea: Assume you have solution for Problem A, you want to say some edge/node, should be available in solution. You will assume you have solution without speciﬁed edge/node, you try to reconstruct a solution by cutting an edge/node and pasting speciﬁed edge/node and say new solution beneﬁt is at least as same as previous solution.
• 17. Proof of theorem Consider the unique simple path from u to v in T
• 18. Proof of theorem Swap(u, v) with the ﬁrst edge on this path that connects a vertex in A to a vertex in V–A
• 19. Proof of theorem A lighter-weight spanning tree than T results. Proving that greedy choice is good enough.
• 20. Prim’s Algorithm
• 21. Prim’s Algorithm Use Priority Queue
• 22. Prim’s Algorithm • 增加節點的觀念做為出發點。 • ⾸首先以某⼀一節點當作出發點，在與其相連且 尚未被選取的節點裡，選擇權重最⼩小的邊， 將新的節點加⼊入。 • 如此重覆加⼊入新節點，直到增加了n - 1條邊 為⽌止。(假設有 n 個節點)