Hybrid particle swarm optimization algorithm based on arena competitive learning strategy

Debin Lu; Jiawen Wang; Xinsheng Wang; Zheng Ren; Jiaqi Liu; Hao Liu

doi:10.1117/12.3004105

11 October 2023 Hybrid particle swarm optimization algorithm based on arena competitive learning strategy

Debin Lu, Jiawen Wang, Xinsheng Wang, Zheng Ren, Jiaqi Liu, Hao Liu

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128000K (2023) https://doi.org/10.1117/12.3004105
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

The research on optimization algorithms has kept pace with the times, and one of the hot spots that has attracted much attention is the improvement of Particle Swarm Optimization algorithm (PSO) in the field of swarm intelligence. In this paper, a hybrid PSO algorithm using Adaptive Learning strategy (ALPSO) is introduced, and a hybrid PSO based on Arena Competitive Learning strategy (ACLPSO) is proposed from the perspective of search space and candidate particle generation, effectively enriches population diversity, expands the initial particle swarm search space, and improves convergence speed and accuracy.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Debin Lu, Jiawen Wang, Xinsheng Wang, Zheng Ren, Jiaqi Liu, and Hao Liu "Hybrid particle swarm optimization algorithm based on arena competitive learning strategy", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128000K (11 October 2023); https://doi.org/10.1117/12.3004105

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