Shehab Mohammad, Abu-Hashem Muhannad A, Shambour Mohd Khaled Yousef, Alsalibi Ahmed Izzat, Alomari Osama Ahmad, Gupta Jatinder N D, Alsoud Anas Ratib, Abuhaija Belal, Abualigah Laith
Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, 11953 Jordan.
Department of Geomatics, Faculty of Architecture and Planning, King Abdulaziz University, Jeddah, Saudi Arabia.
Arch Comput Methods Eng. 2023;30(2):765-797. doi: 10.1007/s11831-022-09817-5. Epub 2022 Sep 21.
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.
蝙蝠算法（BA）是一种很有前景的元启发式算法。它在处理电力和能源系统、经济负荷调度问题、工程设计、图像处理和医学应用等不同领域的各种优化问题时证明了其有效性。因此，本综述对蝙蝠算法进行了全面详尽的回顾，并通过与其他优化算法进行比较来评估其主要特性。该综述论文突出了蝙蝠算法在不同应用中的性能以及研究人员所做的改进（即蝙蝠算法的变体）。最后，结论聚焦于当前关于蝙蝠算法的研究工作，突出其弱点，并提出可能的未来研究方向。这篇综述论文将对来自优化、工程、医学、数据挖掘和聚类等广泛领域的蝙蝠算法研究人员和从业者有所帮助。此外，它在健康、环境和公共安全方面有丰富的研究。同时，它将通过为感兴趣的人提供潜在的未来研究方向来帮助他们。
