Double strategy fusion improved sparrow search algorithm

Hua Fu; Hao Liu

doi:10.1117/12.2686566

10 August 2023 Double strategy fusion improved sparrow search algorithm

Hua Fu, Hao Liu

Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 1275915 (2023) https://doi.org/10.1117/12.2686566
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China

Abstract

Aiming at the shortcomings of sparrow search algorithm, such as dependence on initial solution, sudden drop of population diversity in the late iteration period, and easy to fall into local optimal value, a multi-strategy algorithm was proposed to improve sparrow search algorithm. In the initialization stage of the algorithm, the standard Brownian motion is introduced to enhance the global search ability of the algorithm and improve the population diversity. In the later stage of the algorithm iteration, the improved artificial bee colony search strategy is introduced to accelerate the convergence of the algorithm, and the influence of local extreme points on SSA can be reduced to improve the ability of the algorithm to jump out of the local optimal solution. The experimental results show that the improved sparrow search algorithm has faster global convergence speed, better optimization accuracy and stability in function optimization.

Citation Download Citation

Hua Fu and Hao Liu "Double strategy fusion improved sparrow search algorithm", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 1275915 (10 August 2023); https://doi.org/10.1117/12.2686566

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