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This paper presents a method for revealing the community structure of complex networks in multi-objective genetic algorithm. The algorithm can detect with sparse connections between groups and within groups of closely connected nodes and define the objective function of the two detection methods were optimized. This method produces a series of hierarchical network part, which contains more of the deep part of the community the community by the solution contains less control. Number of community exchange by a better objective function value is determined automatically. Through simulation and real experimental verification, the algorithm can successfully detect the community structure.