Volume 50, Number 2, April-June 2016
Special issue: Research on Optimization and Graph Theory dedicated to COSI 2013
|Page(s)||269 - 283|
|Published online||21 March 2016|
Combined neighborhood tabu search for community detection in complex networks
1 LERIA, University of Angers, 2 Bd Lavoisier, 49045 Angers cedex 01, France.
2 Institut Universitaire de France, Paris, France.
Corresponding author: firstname.lastname@example.org
Accepted: 28 September 2015
Community is one prominent feature of complex networks. Community detection is one important research topic in the area of complex networks analysis. In this paper, we introduce a new heuristic algorithm for community detection using the popular modularity measure. The proposed algorithm, called CNTS for combined neighborhood tabu search (CNTS), relies on a joint use of vertex move and merge operators to improve the quality of visited solutions. A dedicated tabu mechanism provides the algorithm with additional capacities to effectively explore the search space. Experiments using a collection of 21 well-known benchmark instances show that the proposed algorithm competes favorably with state-of-the-art algorithms.
Mathematics Subject Classification: 90-08 / 90C27
Key words: Community detection / heuristics / tabu search / graph partitioning / clustering / combinatorial optimization
© EDP Sciences, ROADEF, SMAI 2016
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