Improved heuristics for the minimum label spanning tree problem

被引:22
作者
Xiong, Yapei [1 ]
Golden, Bruce
Wasil, Edward
机构
[1] Goldman Sachs & Co, New York, NY 10004 USA
[2] Univ Maryland, RH Smith Sch Business, College Pk, MD 20742 USA
[3] American Univ, Kogod Sch Business, Washington, DC 20016 USA
关键词
genetic algorithm (GA); NP-hard; spanning tree;
D O I
10.1109/TEVC.2006.877147
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Given a connected, undirected graph G whose edges are labeled, the minimum label (or labeling) spanning tree (MLST) problem seeks a spanning tree on G with the minimum number of distinct labels. Maximum vertex covering algorithm (MVCA) is a well-known heuristic for the MLST problem. It is very fast and performs reasonably well. Recently, we developed a genetic algorithm (GA) for the MLST problem. The GA and MVCA are similarly fast but the GA outperforms the MVCA. In this paper, we present four modified versions of MVCA, as well as a modified GA. These modified procedures generate better results, but are more expensive computationally. The modified GA is the best performer with respect to both accuracy and running time.
引用
收藏
页码:700 / 703
页数:4
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