Improved Aquila Optimizer Optimization Algorithm Based on Multi-strategy Fusion
Xin Shi Li, Yuxiang Ma, Yan Li, Hao Li, Hui Zuo, Weiman Sun · 2022 2nd International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI) · 2022
Aiming at the disadvantages of slow convergence speed and relatively weak local development ability of Aquila Optimizer optimization algorithm, a Tianying optimization algorithm based on adaptive cross mutation is proposed. Firstly, the inertia weight factor is introduced into the location update formula in the global development stage to adjust the influence degree of the optimal individual on the population. Secondly, the vertical and horizontal crossing strategy is introduced into the local development of the algorithm to exchange individual information across dimensions and improve the local development ability; Finally, Cauchy elite mutation is introduced to avoid the algorithm falling into local optimization. The function optimization simulation experiments of five representative comparison algorithms on 23 different feature benchmark functions show that the optimization accuracy and stability of the proposed improved algorithm are significantly improved. Keywords: Aquila Optimizer optimization algorithm; Inertia weight factor; Vertical and horizontal cross strategy; Cauchy elite variation