Several metaheuristic methods have been applied to tackling various global and engineering optimization problems. However, this method still needs more improvement since they require a suitable balance between exploration and exploitation. Therefore, this study presents an enhancement of the arithmetic optimization algorithm (AOA) as a global optimization method. The developed method, named AOASC, depends on using the sine-cosine algorithm’s operators to enhance the exploitation ability of AOA during the searching process. This leads to improving the convergence rate of the developed method toward the optimal solution. Besides, improve the process of avoiding the attraction toward the local point. Besides these behaviors, the quality of the final solution (best one) is improved. To validate the efficiency of the developed method, a set of experiments is conducted, including various optimization problems, such as ten benchmark functions and five engineering optimization problems. Besides, the results of the developed method are compared with other well-known metaheuristic methods. The results showed the high efficiency of the developed method over other methods in terms of performance measures.