Abstract
This paper introduces a multi-objective optimization idea to solve the community detection. First, the problem of community detection is transformed into complex multi-objective optimization problem. Second, an evolutionary multi-objective membrane algorithm is proposed for discovering community structure. Finally, the proposed algorithm is conducted on the synthetic networks, and the experimental results demonstrate that our algorithm is effective and promising, and it can detect communities more accurately compared with PSO and GSA.
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Acknowledgments
This project was supported by Shenyang Science and Technology Program (Grant No. 17-175-3-00).
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Liu, C., Fan, L., Li, L., Liu, Z., Dai, X., Gao, W. (2017). Community Detection in Networks by Using Multiobjective Membrane Algorithm. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10637. Springer, Cham. https://doi.org/10.1007/978-3-319-70093-9_44
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DOI: https://doi.org/10.1007/978-3-319-70093-9_44
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