A Survey on Dragonfly Algorithm and its Applications in Engineering
- Chnoor M. Rahman ,
- Tarik A. Rashid ,
- Abeer Alsadoon ,
- Nebojsa Bacanin ,
- Polla Fattah ,
- Seyedali Mirjalili
Tarik A. Rashid
University of Kurdistan Hewler, University of Kurdistan Hewler, University of Kurdistan Hewler, University of Kurdistan Hewler
Corresponding Author:[email protected]
Author ProfileAbstract
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.