期刊
INFORMATION PROCESSING LETTERS
卷 95, 期 5, 页码 503-511出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ipl.2005.05.010
关键词
graph algorithms; combinatorial optimization; variable depth search; neighborhood; maximum clique problem
We propose a variable depth search based algorithm, called k-opt local search (KLS), for the maximum clique problem. KLS efficiently explores the k-opt neighborhood defined as the set of neighbors that can be obtained by a sequence of several add and drop moves that are adaptively changed in the feasible search space. Computational results on DIMACS benchmark graphs indicate that KLS is capable of finding considerably satisfactory cliques with reasonable running times in comparison with those of state-of-the-art metaheuristics. (c) 2005 Elsevier B.V. All rights reserved.
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