Abstract
In this article, an Interval Type-3 Fuzzy Logic System (IT3FLS) for enhancing the performance in Bee Colony Optimization (BCO) is outlined. The efficiency of the IT3FLS approach is verified with results on a set of benchmark mathematical functions. The IT3FLS provides an approach that helps to identify the optimal values in α and β parameters that allows to improve the performance in the original BCO. The IT3FLS approach exhibits advantages in the optimization of the benchmark functions. It can be noted that a IT3FLS exhibits better results in the minimal values of the set of mathematical functions. The experimentation demostrates that the implementation of the IT3FLS approach enhances the performance of BCO when compared with respect to the variants utilizing Generalized Type-2 FLS (GT2FLS), Interval Type-2 FLS (IT2FLS) and Type-1 FLS (T1FLS).
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