Abstract
The study of metaheuristics has become an important area for research, these metaheuristics contain parameters and the literature provides us with a range of values in which the algorithm can have good results. For this paper we propose to use the Differential Evolution algorithm combined with fuzzy logic to enable having dynamic crossover parameter, and to complement this work we include the diversity variable based on Euclidean distance, which will help us to know if the individuals of the population are separated or near in the search space in other words is the exploration and the exploitation in the search space, and for this article we work with two types of Simple Multimodal and Hybrid functions belonging to set of CEC 2015 benchmark functions.
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Ochoa, P., Castillo, O., Soria, J. (2018). Differential Evolution Algorithm Using a Dynamic Crossover Parameter with Fuzzy Logic Applied for the CEC 2015 Benchmark Functions. In: Barreto, G., Coelho, R. (eds) Fuzzy Information Processing. NAFIPS 2018. Communications in Computer and Information Science, vol 831. Springer, Cham. https://doi.org/10.1007/978-3-319-95312-0_51
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