Community Detection in Complex Networks based on Multiobjective Honey Bee Mating Optimization

Detecting community structure is crucial for uncovering the links between structures and functions in complex networks. Most of contemporary community detection algorithms employ single optimization criteria (e.g., modularity), which may have fundamental disadvantages. This paper considers the community detection process as a Multi-Objective optimization Problem (MOP). To solve the community detection problem this study used improved honey bee mating optimization (HBMO) algorithm. In the proposed algorithm, an external repository is considered to save non-dominated (Pareto) solutions found during the search process. The efficiency of the proposed algorithm is studied by testing on several data sets. Numerical results show that the proposed evolutionary optimization algorithm is robust and suitable for community detection problem. Keywordscomplex network; community; multi-objective; honey bee mating optimization