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Minimum Spanning Trees Kun-Mao Chao ( 趙坤茂 ) Department of Computer Science and Information Engineering National Taiwan University, Taiwan

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1 Minimum Spanning Trees Kun-Mao Chao ( 趙坤茂 ) Department of Computer Science and Information Engineering National Taiwan University, Taiwan E-mail: kmchao@csie.ntu.edu.tw WWW: http://www.csie.ntu.edu.tw/~kmchao

2 2 Minimum Spanning Trees A minimum spanning tree (MST) of a weighted graph G is a spanning tree of G whose edges sum to minimum weight. In other words, a minimum spanning tree is a tree formed from a subset of the edges in a given undirected graph, with two properties: – it spans the graph, i.e., it includes every vertex in the graph, and – it is a minimum, i.e., the total weight of all the edges is as low as possible.

3 3 Minimum Spanning Trees The minimum spanning tree problem is always included in algorithm textbooks since it arises in many applications, it is an important example where greedy algorithms always deliver an optimal solution, and clever data structures are necessary to make it work efficiently.

4 4 Its minimum spanning trees?

5 5 Some of its minimum spanning trees

6 6 Bor\r{u}vka's Algorithm (1926)

7 7 Kruskal's Algorithm (1956)

8 8 Prim’s Algorithm (1957)

9 Approximation algorithms

10 10 NP-hard: the barrier Since Levin & Cook (1971) & Karp (1972), many important problems have been shown to be NP-hard. The life-cycle of a problem –Defined –NP-hard –Heuristic or for special data

11 11 Too hard to survive? Life finds the ways –Approximation –Online –Distributed –New models Quantum computing Bio-computing

12 12 Approximation algorithms Heuristic vs. approximation algorithms –Ensuring the worst-case quality The error ratio –Relative and Absolute –A k-approximation: minimization: sol/opt<=k; maximization: opt/sol<=k –The ratio is always >1

13 13 Polynomial time approximation scheme For any fixed k>0, it finds a (1+k)-approximation in polynomial time. –Usually (1/k) appears in the time complexity, e.q. O(n/k), O(n 1/k ). –If (1/k) not in the exponent, FPTAS

14 14 An example – Minimum tour (MT) Starting at a node, find a tour of min distance traveling all nodes and back to the starting node. 10 15 8 3 2 5 2 6 10

15 15 A doubling tree algorithm Find a minimum spanning tree Output the Euler tour in the doubling tree of MST 10 15 8 3 2 5 2 6 10 15 8 3 2 5 2 6 10

16 16 The error ratio MST<=MT –MST is the minimum cost of any spanning tree. –A tour must contain a spanning tree since it is connected. It is a 2-approximation Triangle inequality => 2-approximation for TSP (visiting each city only once) Why?

17 17 All exact science is dominated by the idea of approximation. -- Bertrand Russell (1872 - 1970)


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