Abstract
We describe in this paper a new approach to enhance the bat algorithm 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 benchmark mathematical functions show that the fuzzy bat algorithm outperforms the traditional bat algorithm and genetic algorithms.
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Pérez, J., Valdez, F., Castillo, O. (2015). A New Bat Algorithm Augmentation Using Fuzzy Logic for Dynamical Parameter Adaptation. In: Sidorov, G., Galicia-Haro, S. (eds) Advances in Artificial Intelligence and Soft Computing. MICAI 2015. Lecture Notes in Computer Science(), vol 9413. Springer, Cham. https://doi.org/10.1007/978-3-319-27060-9_35
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DOI: https://doi.org/10.1007/978-3-319-27060-9_35
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