GWO-WOA-AOA: Multistage Hybrid Metaheuristic Optimization Approach

A new hybrid optimization methodology merging the advantages of three distinct meta-heuristic techniquesGrey Wolf Optimization Algorithm (GWO), Whale Optimization Algorithm (WOA), and Arithmetic Optimization Algorithm (AOA)-is introduced in this study. The proposed hybrid framework addresses the optimization process with a three-stage approach: The exploration phase with GWO, the exploitation phase with WOA, and the fine-tuning phase with AOA. The performance of the proposed hybrid method is evaluated on CEC2019 benchmark functions (problems with different difficulties in total of $\mathbf{1 0}$). The experimental results show that the proposed hybrid model can achieve faster convergence and superior solution accuracy compared to conventional methods, especially in higher dimensions and problems with multiple optima.