Fuzzy Flower Pollination Algorithm (FFPA): Comparative Study of Type-1 (T1FLS) and Interval Type-2 Fuzzy Logic System (IT2FLS) in Optimization Parameter Adaptation

Abstract

State-of-the-art algorithms are competitive, because they get the most out of available resources. Metaheuristic algorithms solve optimization problems from a search space. The proposal in this research work is to use the algorithm bio-inspired by nature Flower Pollination Algorithm (FPA) for the optimization of the membership functions of an Interval Type-2 Fuzzy Logic system, which we will call IT2FLS-FPA (Interval Type-2 Fuzzy Logic System-Flower Pollination Algorithm). This work is presented to continue with one that we developed before [6], in this investigation we made a comparison between a non-optimized IT2FLS-FPA and an optimized IT2FLS-FPA where we demonstrate that the latter is better by means of statistical hypothesis tests.