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Dragonfly algorithm: a comprehensive review and applications

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Abstract

Dragonfly algorithm (DA) is a novel swarm intelligence meta-heuristic optimization algorithm inspired by the dynamic and static swarming behaviors of artificial dragonflies in nature. It has proved its effectiveness and superiority compared to several well-known meta-heuristics available in the literature. This paper presents a comprehensive review of DA and its new variants classified into modified and hybrid versions. It also describes the main diverse applications of DA in several fields and areas such as machine learning, neural network, image processing, robotics, and engineering. Finally, the paper suggests some possible interesting research on the applications and hybridizations of DA for future works.

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Authors and Affiliations

  1. LIST Laboratory, University of M’Hamed Bougara Boumerdes, Avenue of Independence, 35000, Boumerdes, Algeria

    Yassine Meraihi

  2. LISV Laboratory, University of Versailles St-Quentin-en-Yvelines, 10-12 Avenue of Europe, 78140, Velizy, France

    Amar Ramdane-Cherif

  3. LAA Laboratory, University of M’Hamed Bougara Boumerdes, Avenue of Independence, 35000, Boumerdes, Algeria

    Dalila Acheli

  4. Faculty of Electronics and Informatics, University of Sciences and Technology Houari Boumediene, El Alia Bab Ezzouar, 16025, Algiers, Algeria

    Mohammed Mahseur

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  1. Yassine Meraihi
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  2. Amar Ramdane-Cherif
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  3. Dalila Acheli
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  4. Mohammed Mahseur
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Meraihi, Y., Ramdane-Cherif, A., Acheli, D. et al. Dragonfly algorithm: a comprehensive review and applications. Neural Comput & Applic 32, 16625–16646 (2020). https://doi.org/10.1007/s00521-020-04866-y

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