蜻蜓算法及其在应用科学中的应用
Dragonfly Algorithm and its Applications in Applied Science -- Survey
摘要：
最近开发的启发式优化算法之一是Mirjalili提出的。蜻蜓算法已经显示出它的能力，以优化不同的现实世界的问题。它有三种变体。在这项工作中，概述了算法及其变体。此外，杂交版本的算法进行了讨论。最后，介绍了该算法在机器学习、图像处理、无线网络等领域的应用。然后，它与其他一些元启发式算法进行了比较。此外，该算法在CEC-C 06 2019基准测试函数上进行了测试。结果表明，该算法具有很强的探索能力，其收敛速度优于文献中的其他算法，如PSO和GA。在一般情况下，在这次调查的优点和缺点的算法进行了讨论。此外，一些未来的工作，这将有助于改善算法的弱点，建议。本文的研究希望能为研究该算法的学者提供有益的参考。
英文摘要：
One of the most recently developed heuristic optimization algorithms is dragonfly by Mirjalili. Dragonfly algorithm has shown its ability to optimizing different real world problems. It has three variants. In this work, an overview of the algorithm and its variants is presented. Moreover, the hybridization versions of the algorithm are discussed. Furthermore, the results of the applications that utilized dragonfly algorithm in applied science are offered in the following area: Machine Learning, Image Processing, Wireless, and Networking. It is then compared with some other metaheuristic algorithms. In addition, the algorithm is tested on the CEC-C06 2019 benchmark functions. The results prove that the algorithm has great exploration ability and its convergence rate is better than other algorithms in the literature, such as PSO and GA. In general, in this survey the strong and weak points of the algorithm are discussed. Furthermore, some future works that will help in improving the algorithm's weak points are recommended. This study is conducted with the hope of offering beneficial information about dragonfly algorithm to the researchers who want to study the algorithm.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
