NuMWVC: A novel local search for minimum weighted vertex cover problem

Abstract

The problem of finding a minimum weighted vertex cover (MWVC) in a graph is a well-known combinatorial optimisation problem with important applications. This article introduces a novel local search algorithm called NuMWVC for MWVC based on three ideas. First, four reduction rules are introduced during the initial construction phase. Second, a strategy called configuration checking with aspiration, which aims for reducing cycling in local search, is proposed for MWVC for the first time. Moreover, a self-adaptive vertex removing strategy is proposed to save time spent on searching solutions for which the quality is likely far from optimality. Experimental results show that NuMWVC outperforms state-of-the-art local search algorithms for MWVC on the standard benchmarks, massive graphs and real-world problem (map labeling problem) instances.