Aquila optimizer integrating Gaussian walk and somersault strategy

Qiuxiang Yu; Kuntao Ye

doi:10.1117/12.2671237

28 April 2023 Aquila optimizer integrating Gaussian walk and somersault strategy

Qiuxiang Yu, Kuntao Ye

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126100F (2023) https://doi.org/10.1117/12.2671237
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

To solve the problems of insufficient local search capability and easily falling into local optimization in the Aquila Optimizer (AO), an aquila optimizer integrating Gaussian walk and somersault strategy (AO-IGWSS) is proposed. Strengthening the exploitation ability, a Gaussian walk strategy is used instead of Levy flight to generate step size adaptively controlled by iteration numbers. Furthermore, to enhance the capability of local optima avoidance, a somersault strategy is introduced to update individuals. The experimental results on nine benchmark test functions prove that the AO-IGWSS can achieve better results than the original AO algorithm, the differential evolution mutation and tangent flight aquila optimizer (DEtanAO), and four other intelligent optimization algorithms.

Citation Download Citation

Qiuxiang Yu and Kuntao Ye "Aquila optimizer integrating Gaussian walk and somersault strategy", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126100F (28 April 2023); https://doi.org/10.1117/12.2671237

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