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An adaptive dynamic multi-swarm PSO algorithm based on topological structure for solving complex constrained optimization problems and its applications on UAV path planning
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AI
DOI：10.1016/j.asoc.2026.114813.png)
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Abstract
En 中文
• A clustering strategy based on unsupervised topology is proposed for analysis of relationship between particles. • Adaptive subpopulation size regulation mechanism based on factorization is designed to balance between exploration and exploitation. • A probability-driven cross-subpopulation information interaction model was established to realize information sharing. • An improved Deb rule is integrated into both personal and global optimization updates to enhance constraint handling and search efficiency. • The proposed T-ADMPSO is accessed on CEC2017 benchmark functions and complex UAV path planning problems.
Keywords:
topological structure
adaptive multi-swarm PSO
constrained optimization
UAV path planning
information sharing
Journal
IF:
6.6
Papers:
1.4W
Citations:
4.8W