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

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http://ifigenia.org/wiki/issue:nifs/22/2/87-98

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: Olivas, F., Valdez, F. & Castillo, O. (2013) Particle swarm optimization with dynamic parameter adaptation using interval type-2 fuzzy logic for benchmark mathematical functions, 2013 World Congress on Nature and Biologically Inspired Computing (NaBIC), 12-14 Aug 2013, Fargo, ND. Olivas, F., Valdez, F. & Castillo, O. (2015) Dynamic parameter adaptation in Ant Colony Optimization using a fuzzy system for TSP problems, IFSA-EUSFLAT 2015, Gijón, Asturias, Spain, 765–770. Wang, G. & Guo, L. (2013) A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization, Journal of Applied Mathematics, Volume 2013, 21 pages. Perez, J., Valdez, F. & Castillo, O. (2015) Modification of the Bat Algorithm using fuzzy logic for dynamic parameter adaptation, CEC2015 IEEE Congress on Evolutionary Computation, Sendai, Japan, May 26, 2015. Atanassov, K. (1986) Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20(1), 87–96. Atanassov, K. (1983) Intuitionistic Fuzzy Sets, VII ITKR Session, Sofia, 20-23 June 1983, Reprinted: Int. J. Bioautomation, 2016, 20(S1), S1–S6. Atanassov, K. (1999) Intuitionistic Fuzzy Sets: Theory and Applications, Springer, Heidelberg. Atanassov, K. (2012) On Intuitionistic Fuzzy Sets Theory, Springer Physica-Verlag, Berlin. Atanassov, K. Vassilev, P., Tsvetkov, R. (2013) Intuitionistic Fuzzy Sets, Measures and Integrals. Academic Publishing House "Prof. Marin Drinov", Sofia. Atanassov, K. (1988) Review and New Results on Intuitionistic Fuzzy Sets, Mathematical Foundations of Artificial Intelligence Seminar, Sofia, 1988, Preprint IM-MFAIS-1-88. Reprinted: Int. J. Bioautomation, 2016, 20(S1), S7–S16. L Amador-Angulo, L. & Castillo, O. (2014) Optimization of the Type-1 and Type-2 Fuzzy Controller Design for the Water Tank using the Bee Colony Optimization, Norbert Wiener in the 21st Century, (21CW), 2014 IEEE Conference, Boston, MA, 8 pages. Amador-Angulo, L. & Castillo, O. (2015) Statistical Analysis of Type-1 and Interval Type-2 Fuzzy Logic in dynamic parameter adaptation of the BCO, IFSA-EUSFLAT’2015, 776–783. Goel, N., Gupta, D. & Goel, S. (2013) Performance of Firefly and Bat Algorithm for Unconstrained Optimization Problems, International Journal of Advanced Research in Computer Science and Software Engineering, 3(5), 1405–1409. Castillo, O. & Melin, P. (2012) A review on the design and optimization of interval Type-2 fuzzy controllers, Appl. 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