Dragonfly algorithm: a comprehensive survey of its results, variants, and applications - Alshinwan, Mohammad; Abualigah, Laith; Shehab, Mohammad; Elaziz, Mohamed Abd; Khasawneh, Ahmad M.; Alabool, Hamzeh; Hamad, Husam Al (Multimedia tools and applications, 2021)
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.