A binary particle swarm optimization algorithm based on cauchy mutation operator and inertia weight dynamic adjustment

Rongqing Zhuo; Xin Sun

doi:10.1117/12.3005860

10 October 2023 A binary particle swarm optimization algorithm based on cauchy mutation operator and inertia weight dynamic adjustment

Rongqing Zhuo, Xin Sun

Author Affiliations +

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127990Y (2023) https://doi.org/10.1117/12.3005860
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

The conventional binary particle swarm optimization algorithm frequently encounters issues of sluggish convergence velocity and a proclivity to become ensnared in local optima. Within this paper, we present a new binary particle swarm optimization algorithm based on the Cauchy mutation operator and inertia weight dynamic adjustment to address these issues. Firstly, the population is initialized using the Tent chaotic mapping, which preserves the diversity of the population. Secondly, the inertia weight is dynamically adjusted to expedite the rate of convergence and enhance the algorithm's local exploitation capability. Lastly, the Cauchy mutation operator is introduced to improve The formula for updating the velocity, enlarging the search range of particles, enhancing algorithm diversity, and effectively avoiding Being entrapped within local optima. Empirical findings from six benchmark test functions showcase the enhanced capability of the proposed algorithm to evade local optima while simultaneously refining the convergence performance.

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

Citation Download Citation

Rongqing Zhuo and Xin Sun "A binary particle swarm optimization algorithm based on cauchy mutation operator and inertia weight dynamic adjustment", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127990Y (10 October 2023); https://doi.org/10.1117/12.3005860

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