Dragonfly algorithm: a comprehensive survey of its results, variants, and applications

• Published in: Multimedia tools and applications Vol. 80; no. 10; pp. 14979 - 15016
• Main Authors: Alshinwan, Mohammad, Abualigah, Laith, Shehab, Mohammad, Elaziz, Mohamed Abd, Khasawneh, Ahmad M., Alabool, Hamzeh, Hamad, Husam Al
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2021; Springer Nature B.V
• Subjects: Algorithms; Clustering; Computer Communication Networks; Computer Science; Data mining; Data Structures and Information Theory; Design engineering; Image processing; Literature reviews; Multimedia Information Systems; Optimization; Power dispatch; Special Purpose and Application-Based Systems; Swarm intelligence; Dragonfly algorithm; Meta-heuristic optimization algorithms; Optimization problems; Nature-inspired algorithms
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-020-10255-3

This paper thoroughly introduces a comprehensive review of the so-called Dragonfly algorithm (DA) and highlights its main characteristics. DA is considered one of the promising swarm optimization algorithms because it successfully applied in a wide range of optimization problems in several fields, such as engineering design, medical applications, image processing, power and energy systems, and economic load dispatch problems. The review describes the available literature on DA, including its variants like binary, discrete, modify, and hybridization of DA. Conclusions focus on the current work on DA, highlighting its disadvantages with suggests possible future research directions. Researchers and practitioners of DA belonging to a wide range of audiences from the domains of optimization, engineering, medical, data mining, and clustering, among others will benefit from this study.