Abstract
In this work, a hybrid optimization method is proposed for dealing with the community discovery problem in social networks relying on the bat algorithm. The proposed method hybrids discrete bat algorithm with Tabu search for enhancing the quality of solution in contrast to discrete bat algorithm. The Tabu search is a neighborhood search based method. The local search capability of bat algorithm is improved by introducing the Tabu search strategy. The recommended hybrid approach is tested on a few real-world networks and synthetic benchmark network. The obtained results are very promising and comparable as well. The results are compared with existing algorithms which demonstrate that the proposed method enhances the quality of the obtained solution.
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Rani, S., Mehrotra, M. (2020). A Hybrid Bat Algorithm for Community Detection in Social Networks. In: Abraham, A., Cherukuri, A., Melin, P., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2018 2018. Advances in Intelligent Systems and Computing, vol 941. Springer, Cham. https://doi.org/10.1007/978-3-030-16660-1_92
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DOI: https://doi.org/10.1007/978-3-030-16660-1_92
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