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Issue:Generalized net model of artificial bee colony optimization algorithm with intuitionistic fuzzy parameter adaptation

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Title of paper: Generalized net model of artificial bee colony optimization algorithm with intuitionistic fuzzy parameter adaptation
Author(s):
Dafina Zoteva
Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. Georgi Bonchev Str., Sofia 1113, Bulgaria
Department of Computer Informatics, Faculty of Mathematics and Informatics, Sofia University “St. Kliment Ohridski”
dafy.zoteva@gmail.com
Olympia Roeva
Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. Georgi Bonchev Str., Sofia 1113, Bulgaria
olympia@biomed.bas.bg
Vassia Atanassova
Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. Georgi Bonchev Str., Sofia 1113, Bulgaria
vassia.atanassova@gmail.com
Published in: Notes on Intuitionistic Fuzzy Sets, Volume 24 (2018), Number 3, pages 79–91
DOI: https://doi.org/10.7546/nifs.2018.24.3.79-91
Download:  PDF (484 Kb  Kb, Info)
Abstract: A Generalized Net (GN) model of Intuitionistic Fuzzy Logic (IFL) control and parameter adaptation of the Artificial Bee Colony (ABC) algorithm is proposed in the present paper. The developed GN-model describes the internal logic of the ABC algorithm with an embedded IFL controller to determine the magnitude of perturbation, depending on the current iteration of the algorithm.
Keywords: Generalized net, Intuitionistic fuzzy logic, Artificial Bee Colony, Parameter adaptation.
AMS Classification: 03E72, 68Q85, 62H30.
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