A swarm intelligence approach to the quadratic minimum spanning tree problem

被引:84
|
作者
Sundar, Shyam [1 ]
Singh, Alok [1 ]
机构
[1] Univ Hyderabad, Dept Comp & Informat Sci, Hyderabad 500046, Andhra Pradesh, India
关键词
Artificial bee colony algorithm; Constrained optimization; Heuristic; Quadratic minimum spanning tree problem; Swarm intelligence; COLONY ABC ALGORITHM; OPTIMIZATION;
D O I
10.1016/j.ins.2010.05.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The quadratic minimum spanning tree problem (Q-MST) is an extension of the minimum spanning tree problem (MST). In Q-MST, in addition to edge costs, costs are also associated with ordered pairs of distinct edges and one has to find a spanning tree that minimizes the sumtotal of the costs of individual edges present in the spanning tree and the costs of the ordered pairs containing only edges present in the spanning tree. Though MST can be solved in polynomial time, Q-MST is NP-Hard. In this paper we present an artificial bee colony (ABC) algorithm to solve Q-MST. The ABC algorithm is a new swarm intelligence approach inspired by intelligent foraging behavior of honey bees. Computational results show the effectiveness of our approach. (C) 2010 Elsevier Inc. All rights reserved.
引用
收藏
页码:3182 / 3191
页数:10
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