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2020 | OriginalPaper | Chapter

Grey Wolf, Firefly and Bat Algorithms: Three Widespread Algorithms that Do Not Contain Any Novelty

Authors : Christian Leonardo Camacho Villalón, Thomas Stützle, Marco Dorigo

Published in: Swarm Intelligence

Publisher: Springer International Publishing

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Abstract

In this paper, we carry out a review of the grey wolf, the firefly and the bat algorithms. We identify the concepts involved in these three metaphor-based algorithms and compare them to those proposed in the context of particle swarm optimization. We provide compelling evidence that the grey wolf, the firefly, and the bat algorithms are not novel, but a reiteration of ideas introduced first for particle swarm optimization and reintroduced years later using new natural metaphors. These three algorithms can therefore be added to the growing list of metaphor-based algorithms—to which already belong algorithms such as harmony search and intelligent water drops—that are nothing else than repetitions of old ideas hidden by the usage of new terminology.

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previous chapter Dynamic Response Thresholds: Heterogeneous Ranges Allow Specialization While Mitigating Convergence to Sink States

next chapter Guerrilla Performance Analysis for Robot Swarms: Degrees of Collaboration and Chains of Interference Events

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Title: Grey Wolf, Firefly and Bat Algorithms: Three Widespread Algorithms that Do Not Contain Any Novelty
Authors: Christian Leonardo Camacho Villalón
Thomas Stützle
Marco Dorigo
Publisher: Springer International Publishing
Book: Swarm Intelligence
Print ISBN: 978-3-030-60375-5

Electronic ISBN: 978-3-030-60376-2

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-60376-2_10

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