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Erschienen in:
A Blockchain-Controlled Physical Robot Swarm Communicating via an Ad-Hoc Network Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

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

verfasst von : Christian Leonardo Camacho Villalón, Thomas Stützle, Marco Dorigo

Erschienen in: Swarm Intelligence

Verlag: 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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Vorheriges Kapitel Dynamic Response Thresholds: Heterogeneous Ranges Allow Specialization While Mitigating Convergence to Sink States
Nächstes Kapitel Guerrilla Performance Analysis for Robot Swarms: Degrees of Collaboration and Chains of Interference Events
Fußnoten
1
Grey Wolf Optimizer  [14]: 3656 citations; Firefly Algorithm  [28]: 3018 citations; and Bat Algorithm  [29]: 3549 citations. Source: Google Scholar. Retrieved: July 10, 2020.
 
2
Although search is not an activity in the hunting phases of wolves, the authors explain it as “the divergence among wolves during hunting in order to find a fitter prey” [14, p. 50].
 
3
Note that in the following we will use the shorter notation \(\varphi ^{\textit{\textbf{w}},\textit{\textbf{m}}}_t\) when the meaning is clear from the context.
 
4
In this paper, we consider minimization problems; the obvious adaptation should be made in case of maximization problems.
 
5
Due to the constraint that both conditions have to be met, it may be the case that \(\textit{\textbf{z}}^{i}_{t}\) is rejected even when its quality is higher than that of \(\textit{\textbf{g}}_{t}\).
 
6
Note that, although in this paper we compared BA with PSO and SA, BA could also be interpreted as a variant of differential evolution (DE) [25]. This is because the probability \(\rho ^i_t\) and the \(\texttt {Accept}\) criterion in BA are used in the same way as the mutation probability and the acceptance between donor and trial vectors in DE [18].
 
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Metadaten
Titel
Grey Wolf, Firefly and Bat Algorithms: Three Widespread Algorithms that Do Not Contain Any Novelty
verfasst von
Christian Leonardo Camacho Villalón
Thomas Stützle
Marco Dorigo
Copyright-Jahr
2020
Buch
Swarm Intelligence

Print ISBN: 978-3-030-60375-5

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

Copyright-Jahr: 2020

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

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