论文标题
蜻蜓算法及其在应用科学中的应用 - 调查
Dragonfly Algorithm and its Applications in Applied Science -- Survey
论文作者
论文摘要
最近开发的启发式优化算法之一是Mirjalili的蜻蜓。蜻蜓算法已经显示出优化不同现实世界问题的能力。它有三个变体。在这项工作中，介绍了算法及其变体的概述。此外，讨论了算法的杂交版本。此外，在以下领域提供了应用科学中使用蜻蜓算法的应用程序的结果：机器学习，图像处理，无线和网络。然后将其与其他一些元启发式算法进行比较。此外，该算法在CEC-C06 2019基准功能上进行了测试。结果证明，该算法具有出色的勘探能力，其收敛速率优于文献中的其他算法，例如PSO和GA。通常，在这项调查中，讨论了算法的强和弱点。此外，建议一些未来的作品有助于改善算法的弱点。这项研究是为了向想要研究算法的研究人员提供有关蜻蜓算法的有益信息。
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.
