Abstract
The proposal described in this paper uses the Cuckoo Search (CS) Algorithm via Lévy flights as an optimization method and its enhancement using a fuzzy system to dynamically adapt its parameter. The original method is compared with the proposed method called Fuzzy Cuckoo Search (FCS). In this case we consider a fuzzy system to dynamically change the Pa variable. Simulation results on a set of mathematical functions with the FCS outperform the traditional CS.
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Acknowledgment
We thank CONACYT and Tijuana Institute of Technology for the facilities and resources granted for the development of this research.
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Guerrero, M., Castillo, O., García, M. (2015). Cuckoo Search Algorithm via Lévy Flight with Dynamic Adaptation of Parameter Using Fuzzy Logic for Benchmark Mathematical Functions. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization. Studies in Computational Intelligence, vol 601. Springer, Cham. https://doi.org/10.1007/978-3-319-17747-2_43
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DOI: https://doi.org/10.1007/978-3-319-17747-2_43
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