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Erschienen in:
2009 | OriginalPaper | Buchkapitel
A New Genetic Algorithm for Community Detection
verfasst von : Chuan Shi, Yi Wang, Bin Wu, Cha Zhong
Erschienen in: Complex Sciences
Verlag: Springer Berlin Heidelberg
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With the rapidly grown evidence that various systems in nature and society can be modeled as complex networks, community detection in networks becomes a hot research topic in many research fields. This paper proposes a new genetic algorithm for community detection. The algorithm uses the fundamental measure criterion modularity Q as the fitness function. A special locus-based adjacency encoding scheme is applied to represent the community partition. The encoding scheme is suitable for the community detection based on the reason that it determines the community number automatically and reduces the search space distinctly. In addition, the corresponding crossover and mutation operators are designed. The experiments in three aspects show that the algorithm is effective, efficient and steady.