A Multi-Objective Pigeon-Inspired Optimization Algorithm for Community Detection in Complex Networks

Lin Yu, Xiaodan Guo, Dongdong Zhou and Jie Zhang ()
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Lin Yu: School of Automation, Nanjing University of Science and Technology, Xiaolingwei Street, Nanjing 210094, China
Xiaodan Guo: Northern Information Control Research Institute Group Co., Jiangjun Street, Nanjing 211153, China
Dongdong Zhou: Northern Information Control Research Institute Group Co., Jiangjun Street, Nanjing 211153, China
Jie Zhang: School of Automation, Nanjing University of Science and Technology, Xiaolingwei Street, Nanjing 210094, China

Mathematics, 2024, vol. 12, issue 10, 1-20

Abstract: Community structure is a very interesting attribute and feature in complex networks, which has attracted scholars’ attention and research on community detection. Many single-objective optimization algorithms have been migrated and modified to serve community detection problems. Due to the limitation of resolution, the final algorithm implementation effect is not ideal. In this paper, a multi-objective community detection method based on a pigeon-inspired optimization algorithm, MOPIO-Net, is proposed. Firstly, the PIO algorithm is discretized in terms of the solution space representation, position, and velocity-updating strategies to adapt to discrete community detection scenarios. Secondly, by minimizing the two objective functions of community score and community fitness at the same time, the community structure with a tight interior and sparse exterior is obtained. Finally, for the misclassification caused by boundary nodes, a mutation strategy is added to improve the accuracy of the final community recognition. Experiments on synthetic and real networks verify that the proposed algorithm is more accurate in community recognition compared to 11 benchmark algorithms, confirming the effectiveness of the proposed method.

Keywords: complex networks; community detection; heuristic algorithm; pigeon-inspired optimization; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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