A Comprehensive Review of Bat Inspired Algorithm: Variants, Applications, and Hybridization

Autor: Mohammad Shehab, Muhannad A. Abu-Hashem, Mohd Khaled Yousef Shambour, Ahmed Izzat Alsalibi, Osama Ahmad Alomari, Jatinder N. D. Gupta, Anas Ratib Alsoud, Belal Abuhaija, Laith Abualigah
Rok vydání: 2022
Předmět:
Zdroj: Archives of computational methods in engineering : state of the art reviews.
ISSN: 1886-1784
Popis: Bat algorithm (BA) is one of the promising metaheuristic algorithms. It proved its efficiency in dealing with various optimization problems in diverse fields, such as power and energy systems, economic load dispatch problems, engineering design, image processing and medical applications. Thus, this review introduces a comprehensive and exhaustive review of the BA, as well as evaluates its main characteristics by comparing it with other optimization algorithms. The review paper highlights the performance of BA in different applications and the modifications that have been conducted by researchers (i.e., variants of BA). At the end, the conclusions focus on the current work on BA, highlighting its weaknesses, and suggest possible future research directions. The review paper will be helpful for the researchers and practitioners of BA belonging to a wide range of audiences from the domains of optimization, engineering, medical, data mining and clustering. As well, it is wealthy in research on health, environment and public safety. Also, it will aid those who are interested by providing them with potential future research.
Databáze: OpenAIRE