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arXiv · 1509.05870

Exploiting Reduction Rules and Data Structures: Local Search for Minimum Vertex Cover in Massive Graphs

Yi Fan·Chengqian Li·Zongjie Ma·LjiLjana Brankovic·Vladimir Estivill-Castro·Abdul Sattar
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Abstract

The Minimum Vertex Cover (MinVC) problem is a well-known NP-hard problem. Recently there has been great interest in solving this problem on real-world massive graphs. For such graphs, local search is a promising approach to finding optimal or near-optimal solutions. In this paper we propose a local search algorithm that exploits reduction rules and data structures to solve the MinVC problem in such graphs. Experimental results on a wide range of real-word massive graphs show that our algorithm finds better covers than state-of-the-art local search algorithms for MinVC. Also we present interesting results about the complexities of some well-known heuristics.

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Yi Fan, Chengqian Li, Zongjie Ma, LjiLjana Brankovic, Vladimir Estivill-Castro, Abdul Sattar. 2015-09-19. Exploiting Reduction Rules and Data Structures: Local Search for Minimum Vertex Cover in Massive Graphs. https://arxiv.org/abs/1509.05870

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