The problem of community structure discovery in complex networks has become one of the hot spots in recent years. This paper proposes a multiobjective genetic algorithm MOGCM to uncover community structure. This method overcomes the limitations of the community detection problems, choosing MinMaxCut and the community fitness as the objective functions. In the experiments, 2 well-known real-life networks are used to validate the performance and the results show that the method successfully detects the communities and it is competitive with state-of-the-art approaches.
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