Sasmal Buddhadev, Hussien Abdelazim G, Das Arunita, Dhal Krishna Gopal
Department of Computer Science and Application, Midnapore College (Autonomous), Paschim Medinipur, West Bengal India.
Department of Computer and Information Science, Linköping University, 58183 Linköping, Sweden.
Arch Comput Methods Eng. 2023 Jun 7:1-28. doi: 10.1007/s11831-023-09945-6.
Aquila Optimizer (AO) is a well-known nature-inspired optimization algorithm (NIOA) that was created in 2021 based on the prey grabbing behavior of Aquila. AO is a population-based NIOA that has demonstrated its effectiveness in the field of complex and nonlinear optimization in a short period of time. As a result, the purpose of this study is to provide an updated survey on the topic. This survey accurately reports on the designed enhanced AO variations and their applications. In order to properly assess AO, a rigorous comparison between AO and its peer NIOAs is conducted over mathematical benchmark functions. The experimental results show the AO provides competitive outcomes.
天鹰座优化器（AO）是一种著名的自然启发式优化算法（NIOA），它于2021年基于天鹰座的捕食行为创建。AO是一种基于种群的NIOA，在短时间内已在复杂和非线性优化领域证明了其有效性。因此，本研究的目的是提供关于该主题的最新综述。本综述准确报告了设计的增强型AO变体及其应用。为了正确评估AO，在数学基准函数上对AO与其同类NIOA进行了严格比较。实验结果表明AO提供了具有竞争力的结果。
