Abstract
We describe in this paper the Bat Algorithm and a new approach is proposed using a fuzzy system to dynamically adapt its parameters. The original method is compared with the proposed method and also compared with genetic algorithms, providing a more complete analysis of the effectiveness of the bat algorithm. Simulation results on a set of mathematical functions with the fuzzy bat algorithm outperform the traditional bat algorithm and genetic algorithms and proposed to implement the method in a controller to analyze the effectiveness of the algorithm.
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We would like to express our gratitude to the CONACYT and Tijuana Institute of Technology for the facilities and resources granted for the development of this research.
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Pérez, J., Valdez, F., Castillo, O. (2015). A New Bat Algorithm with Fuzzy Logic for Dynamical Parameter Adaptation and Its Applicability to Fuzzy Control Design. In: Castillo, O., Melin, P. (eds) Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics. Studies in Computational Intelligence, vol 574. Springer, Cham. https://doi.org/10.1007/978-3-319-10960-2_4
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DOI: https://doi.org/10.1007/978-3-319-10960-2_4
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