A multi-objective community detection algorithm based on ant lion optimization

Taoyun Dai; Guoqiang Chen; Hongji Zhou

doi:10.1117/12.2692059

23 August 2023 A multi-objective community detection algorithm based on ant lion optimization

Taoyun Dai, Guoqiang Chen, Hongji Zhou

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 127841P (2023) https://doi.org/10.1117/12.2692059
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

Complex networks have received widespread attention and research now. A prominent feature of networks is their community structure, and community structure detection has emerged. Ant lion Optimization algorithm (ALO) has the advantages of fast convergence speed, fewer parameters, and constantly falling into local optimal solutions. ALO has been widely used in various engineering problems. In this paper, a multi-objective community detection algorithm based on ant lion optimization (MOALOCD) is proposed. This algorithm can optimize both KKM and RC objectives simultaneously. Experiments on real networks have shown that this algorithm can achieve good results.

Citation Download Citation

Taoyun Dai, Guoqiang Chen, and Hongji Zhou "A multi-objective community detection algorithm based on ant lion optimization", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 127841P (23 August 2023); https://doi.org/10.1117/12.2692059

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