Abstract
We have been working previously with the Differential Evolution algorithm by dynamically adapting the mutation parameter using a simple fuzzy system where we have one input as the generations and one output as the mutation, and we have obtained good results with this modification for simple problems. However, our new goal is to include diversity as another the input to the fuzzy system, this is an 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. This work is the beginning of an investigation to be able to adapt the diversity variable in the best form in the Differential Evolution algorithm just as our previous work the output of the new fuzzy system will be the mutation variable of the Differential evolution algorithm. For this article we work with a set of simple benchmark functions in order to observe the behavior of this new fuzzy system.
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Ochoa, P., Castillo, O., Soria, J. (2018). A New Approach for Dynamic Mutation Parameter in the Differential Evolution Algorithm Using Fuzzy Logic. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_9
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DOI: https://doi.org/10.1007/978-3-319-67137-6_9
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