Enhancing Explainability and Reliable Decision-Making in Particle Swarm Optimization through Communication Topologies

• URL: http://arxiv.org/abs/2504.12803v1
• Date: Thu, 17 Apr 2025 10:05:10 GMT
• Title: Enhancing Explainability and Reliable Decision-Making in Particle Swarm Optimization through Communication Topologies
• Authors: Nitin Gupta, Indu Bala, Bapi Dutta, Luis Martínez, Anupam Yadav,
• Abstract summary: This study focuses on how different communication topologies affect convergence and search behaviors.<n>Using an adapted IOHxplainer, we investigate how these topologies influence information flow, diversity, and convergence speed.
• Score: 14.88267665338613
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Swarm intelligence effectively optimizes complex systems across fields like engineering and healthcare, yet algorithm solutions often suffer from low reliability due to unclear configurations and hyperparameters. This study analyzes Particle Swarm Optimization (PSO), focusing on how different communication topologies Ring, Star, and Von Neumann affect convergence and search behaviors. Using an adapted IOHxplainer , an explainable benchmarking tool, we investigate how these topologies influence information flow, diversity, and convergence speed, clarifying the balance between exploration and exploitation. Through visualization and statistical analysis, the research enhances interpretability of PSO's decisions and provides practical guidelines for choosing suitable topologies for specific optimization tasks. Ultimately, this contributes to making swarm based optimization more transparent, robust, and trustworthy.

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