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

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Abstract

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.

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Affiliations

  1. Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, 11953, Jordan

    Mohammad Alshinwan, Laith Abualigah, Ahmad M. Khasawneh & Husam Al Hamad

  2. Computer Science Department, Aqaba University of Technology, Aqaba, 77110, Jordan

    Mohammad Shehab

  3. School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China

    Mohamed Abd Elaziz

  4. Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, Egypt

    Mohamed Abd Elaziz

  5. College of Computing and Informatics, Saudi Electronic University, Abha, Saudi Arabia

    Hamzeh Alabool

Authors
  1. Mohammad Alshinwan
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  2. Laith Abualigah
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  3. Mohammad Shehab
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  4. Mohamed Abd Elaziz
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  5. Ahmad M. Khasawneh
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  6. Hamzeh Alabool
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  7. Husam Al Hamad
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Correspondence to Mohammad Alshinwan.

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Alshinwan, M., Abualigah, L., Shehab, M. et al. Dragonfly algorithm: a comprehensive survey of its results, variants, and applications. Multimed Tools Appl (2021). https://doi.org/10.1007/s11042-020-10255-3

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Keywords

  • Dragonfly algorithm
  • Meta-heuristic optimization algorithms
  • Optimization problems
  • Nature-inspired algorithms
  • Swarm intelligence