EWLS: A New Local Search for Minimum Vertex Cover

Authors

  • Shaowei Cai Peking University
  • Kaile Su Peking University
  • Qingliang Chen Jinan University

DOI:

https://doi.org/10.1609/aaai.v24i1.7539

Keywords:

Minimum Vertex Cover, Local Search, Edge Weighting

Abstract

A number of algorithms have been proposed for the Minimum Vertex Cover problem. However, they are far from satisfactory, especially on hard instances. In this paper, we introduce Edge Weighting Local Search (EWLS), a new local search algorithm for the Minimum Vertex Cover problem. EWLS is based on the idea of extending a partial vertex cover into a vertex cover. A key point of EWLS is to find a vertex set that provides a tight upper bound on the size of the minimum vertex cover. To this purpose, EWLS employs an iterated local search procedure, using an edge weighting scheme which updates edge weights when stuck in local optima. Moreover, some sophisticated search strategies have been taken to improve the quality of local optima. Experimental results on the broadly used DIMACS benchmark show that EWLS is competitive with the current best heuristic algorithms, and outperforms them on hard instances. Furthermore, on a suite of difficult benchmarks, EWLS delivers the best results and sets a new record on the largest instance.

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Published

2010-07-03

How to Cite

Cai, S., Su, K., & Chen, Q. (2010). EWLS: A New Local Search for Minimum Vertex Cover. Proceedings of the AAAI Conference on Artificial Intelligence, 24(1), 45-50. https://doi.org/10.1609/aaai.v24i1.7539

Issue

Section

Constraints, Satisfiability, and Search