Community detection in networks by using multiobjective evolutionary algorithm with decomposition

Maoguo Gong, Lijia Ma, Qingfu Zhang and Licheng Jiao

Physica A: Statistical Mechanics and its Applications, 2012, vol. 391, issue 15, 4050-4060

Abstract: Community structure is an important property of complex networks. Most optimization-based community detection algorithms employ single optimization criteria. In this study, the community detection is solved as a multiobjective optimization problem by using the multiobjective evolutionary algorithm based on decomposition. The proposed algorithm maximizes the density of internal degrees, and minimizes the density of external degrees simultaneously. It can produce a set of solutions which can represent various divisions to the networks at different hierarchical levels. The number of communities is automatically determined by the non-dominated individuals resulting from our algorithm. Experiments on both synthetic and real-world network datasets verify that our algorithm is highly efficient at discovering quality community structure.

Keywords: Community detection; Complex network; Multiobjective optimization; Evolutionary algorithm; Decomposition (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:391:y:2012:i:15:p:4050-4060

DOI: 10.1016/j.physa.2012.03.021

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