Hybrid Aquila Optimizer with Moth-Flame Optimization Algorithm for Global Optimization

Aquila Optimizer (AO) is a recent search method proposed in 2021 to solve different optimization problems (OPs). One of the best-published search methods in the literature is Moth-Flame Optimization (MFO) algorithm. This paper gives a new version of AO based on hybridizing the Aquila Optimizer and Moth-Flame Optimization algorithm, called AOMFO. The proposed method takes advantage of the Aquila search operators to conduct an exhaustive search (exploration) and takes advantage of the MFO algorithm to conduct a deep search (exploitation). To validate the ability of the proposed hybrid AOMFO method in solving the OPs, 23 slandered benchmark functions are used. The results of the proposed AOMFO are compared with other well-known methods. The results clearly showed that the proposed hybrid AOMFO obtained better results than other well-known methods and reached the best solutions in several test cases.