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