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A Survey on Dragonfly Algorithm and its Applications in Engineering
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  • Chnoor M. Rahman ,
  • Tarik A. Rashid ,
  • Abeer Alsadoon ,
  • Nebojsa Bacanin ,
  • Polla Fattah ,
  • Seyedali Mirjalili
Chnoor M. Rahman
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Tarik A. Rashid
University of Kurdistan Hewler, University of Kurdistan Hewler, University of Kurdistan Hewler, University of Kurdistan Hewler

Corresponding Author:[email protected]

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Abeer Alsadoon
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Nebojsa Bacanin
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Polla Fattah
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Seyedali Mirjalili
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Abstract

Dragonfly algorithm developed in 2016. It is one of the algorithms used by the researchers to optimize an extensive series of uses and applications in various areas. At times, it offers superior performance compared to the most well-known optimization techniques. However, this algorithm faces several difficulties when it is utilized to enhance complex optimization problems. This work addressed the robustness of the method to solve real-world optimization issues, and its deficiency to improve complex optimization problems. This review paper shows a comprehensive investigation of the dragonfly algorithm in the engineering area. First, an overview of the algorithm is discussed. Besides, we also examine the modifications of the algorithm. The merged forms of this algorithm with different techniques and the modifications that have been done to make the algorithm perform better are addressed. Additionally, a survey on applications in the engineering area that used the dragonfly algorithm is offered. A comparison is made between the algorithm and other metaheuristic techniques to show its ability to enhance various problems. The outcomes of the algorithm from the works that utilized the dragonfly algorithm previously and the outcomes of the benchmark test functions proved that in comparison with some techniques, the dragonfly algorithm owns an excellent performance, especially for small to intermediate applications. Moreover, the congestion facts of the technique and some future works are presented. The authors conducted this research to help other researchers who want to study the algorithm and utilize it to optimize engineering problems.
Feb 2023Published in Evolutionary Intelligence volume 16 issue 1 on pages 1-21. 10.1007/s12065-021-00659-x