ILSGVCP: An improved local search algorithm for generalized vertex cover problem

Abstract

The generalized vertex cover problem (GVCP) is a well-known combinatorial problem of the classic minimum vertex cover problem with rich applications. And local search algorithm is an effective heuristic algorithm to solve GVCP. Therefore, In this paper, we develop an improved local search algorithm for the problem, namely ILSGVCP. Specifically, new choosing small weight rules called CSWR is presented for initialization to acquire a high-quality candidate solution. Furthermore, we propose a dynamic perturbation mechanism called DP with a novel formula which makes local search perturbed dynamically. Moreover, we combine CSWR and DP to propose our algorithm ILSGVCP. Finally, we carry out experiments to evaluate ILSGVCP on random instances with up to 1000 vertices and 400,000 edges and DIMACS instances. A detailed experimental evaluation reveals that ILSGVCP outperforms other state-of-the-art algorithms for the GVCP.

Keywords:

• Local Search
• generalized vertex cover problem
• initial solution
• perturbation mechanism
• combinatorial optimization

Acknowledgements

The authors of this article wish to extend their sincere gratitude to all the reviewers for their effort work.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (62076108, 61972360, 61872159).