Exploiting Reduction Rules and Data Structures: Local Search for Minimum Vertex Cover in Massive Graphs
Data Structures and Algorithms
2015-09-22 v1 Artificial Intelligence
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.
Cite
@article{arxiv.1509.05870,
title = {Exploiting Reduction Rules and Data Structures: Local Search for Minimum Vertex Cover in Massive Graphs},
author = {Yi Fan and Chengqian Li and Zongjie Ma and LjiLjana Brankovic and Vladimir Estivill-Castro and Abdul Sattar},
journal= {arXiv preprint arXiv:1509.05870},
year = {2015}
}
Comments
7 pages, 3 figures, 2 tables, 6 algorithms, submitted to AAAI-16