Randomized local search, evolutionary algorithms, and the minimum spanning tree problem

被引:147
作者
Neumann, Frank [1 ]
Wegener, Ingo
机构
[1] Max Planck Inst Informat, Dept Algorithms & Complex 1, D-66123 Saarbrucken, Germany
[2] FB Informat, D-44221 Dortmund, Germany
关键词
minimum spanning trees; analysis of expected optimization timed; parallel random search (I plus lambda) EA;
D O I
10.1016/j.tcs.2006.11.002
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Randomized search heuristics, among them randomized local search and evolutionary algorithms, are applied to problems whose structure is not well understood, as well as to problems in combinatorial optimization. The analysis of these randomized search heuristics has been started for some well-known problems, and this approach is followed here for the minimum spanning tree problem. After motivating this line of research, it is shown that randomized search heuristics find minimum spanning trees in expected polynomial time without employing the global technique of greedy algorithms. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:32 / 40
页数:9
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