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Collective dynamics of particle swarm optimization: A network science perspective

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  • Deng, Lingyun
  • Liu, Sanyang

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.

Suggested Citation

  • Deng, Lingyun & Liu, Sanyang, 2025. "Collective dynamics of particle swarm optimization: A network science perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 675(C).
    • Handle: RePEc:eee:phsmap:v:675:y:2025:i:c:s0378437125004303
    DOI: 10.1016/j.physa.2025.130778
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    References listed on IDEAS

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