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Issue:Parameter adaptation of the Bat Algorithm, using type-1, interval type-2 fuzzy logic and intuitionistic fuzzy logic

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Title of paper: Parameter adaptation of the Bat Algorithm, using type-1, interval type-2 fuzzy logic and intuitionistic fuzzy logic
Author(s):
Jonathan Pérez
Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico
tecjonathan@gmail.com
Fevrier Valdez
Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico
fevrier@tectijuana.mx
Olympia Roeva
Institute of Biophysics and Biomedical Engineering, BAS, Sofia, Bulgaria
olympia@biomed.bas.bg
Oscar Castillo
Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico
ocastillo@tectijuana.mx
Presented at: International Conference on Intuitionistic Fuzzy Sets Theory and Applications, 20–22 April 2016, Beni Mellal, Morocco
Published in: "Notes on IFS", Volume 22, 2016, Number 2, pages 87—98
Download:  PDF (127  Kb, File info)
Abstract: We describe in this paper the Bat Algorithm (BA) and a proposed enhancement using fuzzy and intuitionistic fuzzy systems to dynamically adapt BA parameters. BA is a metaheuristic algorithm inspired by the behavor of micro bats, which has been applied to different optimization problems obtaining good results. We propose a new method for dynamic parameter adaptation in the BA using Type-1, interval Type-2 fuzzy logic and intuitionistic fuzzy logic. The goal is improving the performance of the BA.
Keywords: Dynamic parameter adaptation, Bat algorithm, Type-1 fuzzy logic, Type-2 fuzzy logic, Intuitionistic fuzzy logic.
AMS Classification: 03E72.
References:
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