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Nature inspired optimization algorithms or simply variations of metaheuristics?

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Abstract

In the last decade, we observe an increasing number of nature-inspired optimization algorithms, with authors often claiming their novelty and their capabilities of acting as powerful optimization techniques. However, a considerable number of these algorithms do not seem to draw inspiration from nature or to incorporate successful tactics, laws, or practices existing in natural systems, while also some of them have never been applied in any optimization field, since their first appearance in literature. This paper presents some interesting findings that have emerged after the extensive study of most of the existing nature-inspired algorithms. The need for irrationally introducing new nature inspired intelligent (NII) algorithms in literature is also questioned and possible drawbacks of NII algorithms met in literature are discussed. In addition, guidelines for the development of new nature-inspired algorithms are proposed, in an attempt to limit the misleading appearance of variation of metaheuristics as nature inspired optimization algorithms.

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  1. Management and Decision Engineering Laboratory, Department of Financial and Management Engineering, School of Engineering, University of the Aegean, 41 Kountouriotou Str., 82132, Chios, Greece

    Alexandros Tzanetos & Georgios Dounias

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  1. Alexandros Tzanetos
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  2. Georgios Dounias
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All authors contributed to the study conception and design. AT has performed the literature review needed for this work. Visualization of review results was performed also by AT. GD supervised this study. The first draft of the manuscript was written by both AT and GD, which also read and approved the final manuscript.

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Correspondence to Alexandros Tzanetos.

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Tzanetos, A., Dounias, G. Nature inspired optimization algorithms or simply variations of metaheuristics?. Artif Intell Rev 54, 1841–1862 (2021). https://doi.org/10.1007/s10462-020-09893-8

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