  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.
