A survey on firefly algorithms

•The different variants of firefly algorithm are classified and analyzed to summarize the latest research and developments related to nature-inspired computing in the most general sense.•This review has proved that firefly algorithms can be practically applied within every problem domain.Moreover, t...

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Bibliographic Details
Published inNeurocomputing (Amsterdam) Vol. 500; pp. 662 - 678
Main Authors Li, Jun, Wei, Xiaoyu, Li, Bo, Zeng, Zhigao
Format Journal Article
LanguageEnglish
Published Elsevier B.V 21.08.2022
Subjects
Applications
Firefly algorithm
Nature-inspired algorithm
Optimization
Swarm Intelligence
Nature-inspired algorithm
Applications
Firefly algorithm
Optimization
Swarm Intelligence
Online AccessGet full text
ISSN0925-2312
1872-8286
DOI10.1016/j.neucom.2022.05.100

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Summary:•The different variants of firefly algorithm are classified and analyzed to summarize the latest research and developments related to nature-inspired computing in the most general sense.•This review has proved that firefly algorithms can be practically applied within every problem domain.Moreover, this review has presented to researchers new technological trends and design challenges they have to cope with, while designing systems using this algorithm. Firefly algorithm (FA) is one of the popular algorithms of Swarm Intelligence domain. The literature has expanded significantly in the past few years. This paper provides a timely review of the FA and its new variants. The different variants of FA are classified and analyzed. The applications and case studies in the rapidly evolving domain are also reviewed and summarized in detail here. The problems to be further solved and future research directions of firefly algorithms will be given at the end of this paper.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2022.05.100