Accelerated Arithmetic Optimization Algorithm by Cuckoo Search for Solving Engineering Design Problems

Abstract

Several metaheuristic algorithms have been implemented to solve global optimization issues. Nevertheless, these approaches require more enhancement to strike a suitable harmony between exploration and exploitation. Consequently, this paper proposes improving the arithmetic optimization algorithm (AOA) to solve engineering optimization issues based on the cuckoo search algorithm called AOACS. The developed approach uses cuckoo search algorithm operators to improve the ability of the exploitation operations of AOA. AOACS enhances the convergence ratio of the presented technique to find the optimum solution. The performance of the AOACS is examined using 23 benchmark functions and CEC-2019 functions to show the ability of the proposed work to solve different numerical optimization problems. The proposed AOACS is evaluated using four engineering design problems: the welded beam, the three-bar truss, the stepped cantilever beam, and the speed reducer design. Finally, the results of the proposed approach are compared with state-of-the-art approaches to prove the performance of the proposed AOACS approach. The results illustrated an outperformance of AOACS compared to other methods of performance measurement.

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“…After iterations, it frequently only produces modest, comparable solutions, stopping the search from moving forward. No one metaheuristic algorithm can solve every problem regarding the No Free Lunch (NFL) theory [31]- [33]. They all have drawbacks, such as early conver-gence, becoming stuck in local optimal, and the necessity for global search capability [32], [34].…”