Study on improved dung beetle optimization algorithm

Beibei Yan; Changyou Wu; Min Cong; Yige Sun

doi:10.1117/12.3038160

7 August 2024 Study on improved dung beetle optimization algorithm

Beibei Yan, Changyou Wu, Min Cong, Yige Sun

Proceedings Volume 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024); 1322921 (2024) https://doi.org/10.1117/12.3038160
Event: Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 2024, Nanchang, China

Abstract

Since the original dung beetle optimization algorithm suffers from the drawbacks of slow early convergence, low solution accuracy, easy to be trapped in locally optimal, a dung beetle optimization algorithm incorporating Lévy's flight strategy and lens imaging learning is proposed (OLBOA). Introducing firefly perturbations in the DBO algorithm for updating the position of the rolling ball dung beetle to prevent it from getting stuck in a partial optimum; The Levy flight strategy is used to effectively optimize the ability of the algorithm to search globally and locally; Mutation of optimal individuals in a population using convex lens imaging reverse engineering strategy to form new individuals and to increase the acceleration of acceleration of convergence of the algorithm. Compare the improved algorithm with other cluster intelligence methods on four of the functions tested. The outcome demonstrates that the modified DBO algorithm converges faster and the optimization accuracy is higher, which verifies the feasibility of the algorithm.

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

Citation Download Citation

Beibei Yan, Changyou Wu, Min Cong, and Yige Sun "Study on improved dung beetle optimization algorithm", Proc. SPIE 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 1322921 (7 August 2024); https://doi.org/10.1117/12.3038160

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