Improved chaos particle swarm optimization algorithm based on hybrid strategy

Xianhui Meng

doi:10.1117/12.3039325

4 September 2024 Improved chaos particle swarm optimization algorithm based on hybrid strategy

Xianhui Meng

Proceedings Volume 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024); 1325931 (2024) https://doi.org/10.1117/12.3039325
Event: Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ICAIB 2024), 2024, Yinchuan, China

Abstract

In response to the issues of basic Particle Swarm Optimization (PSO) being inclined to getting stuck in local bests, slow convergence precision, and low convergence rate, a Improved Chaotic Particle Swarm Optimization (ICPSO) based on hybrid strategies is proposed. This algorithm combines the adaptive inertia weight strategy, boundary symmetric mapping method, adaptive mutation idea, and chaotic optimization idea, enhancing the global search capability of the PSO, accelerating convergence rate, and increasing the likelihood of jump out of local bests. Finally, multiple classic test functions are picked to contrast the ICPSO with the basic PSO and other enhancement methods. The results indicate that the ICPSO converges faster, achieves higher convergence accuracy, and it is easier to converge to the global optimum.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xianhui Meng "Improved chaos particle swarm optimization algorithm based on hybrid strategy", Proc. SPIE 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024), 1325931 (4 September 2024); https://doi.org/10.1117/12.3039325

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