This paper proposes a novel population-based optimization method, called Aquila Optimizer (AO), which is inspired by the Aquila’s behaviors in nature during the process of catching the prey. Hence, the optimization procedures of the proposed AO algorithm are represented in four methods; selecting the search space by high soar with the vertical stoop, exploring within a diverge search space by contour flight with short glide attack, exploiting within a converge search space by low flight with slow descent attack, and swooping by walk and grab prey. To validate the new optimizer’s ability to find the optimal solution for different optimization problems, a set of experimental series is conducted. For example, during the first experiment, AO is applied to find the solution of well-known 23 functions. The second and third experimental series aims to evaluate the AO’s performance to find solutions for more complex problems such as thirty CEC2017 test functions and ten CEC2019 test functions, respectively. Finally, a set of seven real-world engineering problems are used. From the experimental results of AO that compared with well-known meta-heuristic methods, the superiority of the developed AO algorithm is observed. Matlab codes of AO are available at https://www.mathworks.com/matlabcentral/fileexchange/89381-aquila-optimizer-a-meta-heuristic-optimization-algorithm and Java codes are available at https://www.mathworks.com/matlabcentral/fileexchange/89386-aquila-optimizer-a-meta-heuristic-optimization-algorithm.

本文提出了一种新的基于种群的优化方法，称为Aquila Optimizer（AO），该方法受Aquila在捕获猎物过程中自然行为的启发。因此，提出的AO算法的优化过程可以用四种方法表示。通过垂直弯曲高飞选择搜索空间，在短距离滑翔攻击下通过轮廓飞行在分散搜索空间内探索，在缓慢下降攻击下通过低速飞行在收敛搜索空间内探索，并通过步行和掠夺猛扑。为了验证新的优化程序找到针对不同优化问题的最佳解决方案的能力，我们进行了一系列实验。例如，在第一个实验中，使用AO来找到众所周知的23个函数的解。第二和第三个实验系列旨在评估AO的性能，以找到针对更复杂问题的解决方案，例如分别具有30个CEC2017测试功能和10个CEC2019测试功能。最后，使用了七个实际工程问题集。从与著名的元启发式方法相比的AO实验结果可以看出，所开发的AO算法具有优越性。AO的Matlab代码位于https://www.mathworks.com/matlabcentral/fileexchange/89381-aquila-optimizer-a-meta-heuristic-optimization-algorithm，而Java代码位于https：//www.mathworks。 com / matlabcentral / fileexchange / 89386-aquila-optimizer-a-meta-heuristic-optimization-algorithm。