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A review of optimization swarm intelligence-inspired algorithms with type-2 fuzzy logic parameter adaptation.

Authors :
Valdez, Fevrier
Source :
Soft Computing - A Fusion of Foundations, Methodologies & Applications. Jan2020, Vol. 24 Issue 1, p215-226. 12p.
Publication Year :
2020

Abstract

In this paper, a survey about the algorithms based on swarm intelligence with parameter adaptation using some techniques to achieve the best results is presented. In this case, we analyzed the most popular algorithms such as ant colony optimization, particle swarm optimization, bee colony optimization, bat algorithm, firefly algorithm and cuckoo search. These algorithms are referenced in the paper because they have demonstrated to be superior with respect to the other optimization methods based on swarms with parameter adaptation using type-2 fuzzy logic in some applications, and also the algorithms are inspired on swarm intelligence. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14327643
Volume :
24
Issue :
1
Database :
Academic Search Index
Journal :
Soft Computing - A Fusion of Foundations, Methodologies & Applications
Publication Type :
Academic Journal
Accession number :
141100767
Full Text :
https://doi.org/10.1007/s00500-019-04290-y