An ant colony optimization algorithm for the minimum weight vertex cover problem

Shyong Jian Shyu, Peng Yeng Yin, Miao-Tsong Lin

Research output: Contribution to journalArticle

72 Scopus citations

Abstract

Given an undirected graph and a weighting function defined on the vertex set, the minimum weight vertex cover problem is to find a vertex subset whose total weight is minimum subject to the premise that the selected vertices cover all edges in the graph. In this paper, we introduce a meta-heuristic based upon the Ant Colony Optimization (ACO) approach, to find approximate solutions to the minimum weight vertex cover problem. In the literature, the ACO approach has been successfully applied to several well-known combinatorial optimization problems whose solutions might be in the form of paths on the associated graphs. A solution to the minimum weight vertex cover problem however needs not to constitute a path. The ACO algorithm proposed in this paper incorporates several new features so as to select vertices out of the vertex set whereas the total weight can be minimized as much as possible. Computational experiments are designed and conducted to study the performance of our proposed approach. Numerical results evince that the ACO algorithm demonstrates significant effectiveness and robustness in solving the minimum weight vertex cover problem.

Original languageEnglish
Pages (from-to)283-304
Number of pages22
JournalAnnals of Operations Research
Volume131
Issue number1-4
DOIs
StatePublished - 1 Oct 2004

Keywords

  • ant colony optimization
  • meta-heuristic algorithm
  • minimum weight vertex cover

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