Combined neighborhood tabu search for community detection in complex networks | Zendy

Olivier Gach | Zendy; JinKao Hao | Zendy

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Combined neighborhood tabu search for community detection in complex networks

Author(s) -

Olivier Gach,

JinKao Hao

Publication year - 2015

Publication title -

rairo - operations research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.383

H-Index - 24

eISSN - 1290-3868

pISSN - 0399-0559

DOI - 10.1051/ro/2015046

Subject(s) - tabu search , merge (version control) , computer science , benchmark (surveying) , complex network , heuristic , vertex (graph theory) , harmony search , algorithm , artificial intelligence , data mining , theoretical computer science , graph , information retrieval , geodesy , world wide web , geography

International audience

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.

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