The applications of Artificial Hummingbird Algorithm (AHA) in the optimization problems: A review of the state-of-the-art
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Abstract
Nature-inspired algorithms have been developed and applied to solve a wide range of real-world optimization problems. Artificial Hummingbird Algorithm (AHA) is one of the recently introduced ones. The foraging and flight behaviors of hummingbirds inspire the mechanisms of the AHA. It has a simple structure and operates exploitation and exploration processes based on the visitation of hummingbirds, to find optimal solutions effectively with a few parameter settings. To the best of our knowledge, there has been no comprehensive and systematic review of the AHA, which is the objective of this paper. Researchers have demonstrated AHA's effectiveness in various applications, including antenna design, biomedical, networking, optimization, prediction and forecasting, scheduling, and power generation and controlling. Many studies have reported that the efficiency of AHA can be increased by modifying and hybridizing it with other algorithms. The most well-known problem that AHA has solved is the renewable energy issue. The AHA is also classified as a bio-inspired algorithm frequently used to compare performance. Although the AHA has been published recently and applied to many problems, there are limitations to some application areas, such as scheduling problems and robotics, security, fuzzy systems, data mining, and other interesting optimization problems.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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