Collective dynamics of particle swarm optimization: A network science perspective

Lingyun Deng and Sanyang Liu

Physica A: Statistical Mechanics and its Applications, 2025, vol. 675, issue C

Abstract: Particle swarm optimization (PSO) is a cornerstone of evolutionary computation, yet its population dynamics and topological properties remain poorly understood beyond traditional stability analysis. This study presents the first network science-based investigation of PSO’s intrinsic topology, demonstrating that its network structure inherently exhibits small-world architecture and heavy-tailed degree distributions. Through systematic analysis of 13 benchmark functions – including 7 unimodal and 6 multimodal problems – we construct population communication networks where nodes represent particles and edges denote the interaction between individuals. This interdisciplinary lens provides a promising theoretical framework for analyzing evolutionary computation methods.

Keywords: Evolutionary computation; Particle swarm optimization; Population communication network; Small-world phenomenon; Heavy-tailed distribution (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:675:y:2025:i:c:s0378437125004303

DOI: 10.1016/j.physa.2025.130778

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