A New Bat Algorithm Augmentation Using Fuzzy Logic for Dynamical Parameter Adaptation

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.