Comparative Study of Type-1 and Interval Type-2 Fuzzy Systems in Parameter Adaptation of the Fuzzy Flower Pollination Algorithm Hector Carreon and Fevrier Valdez Abstract Combining Interval Type-2 Fuzzy Logic Systems with metaheuristics has shown in most investigations that better results are obtained than with Type-1 Fuzzy Logic Systems. In this comparative study, experiments were carried out with Type-1 and Interval Type-2 Fuzzy Logic Systems, each one in combination with the Flower Pollination Algorithm. In the modification of parameters, with this combination of hybrid methods we carried out the comparative study. Previously, experiments were carried out with the flower pollination algorithm and the Type-1 Fuzzy Logic System (T1FLS), with the results of both methods, and we have concluded that better results are obtained with the hybrid method of Interval Type-2 Fuzzy Logic System (IT2FLS) and the Flower Pollination Algorithm (FPA). Keywords Type-1 fuzzy logic · Type-2 fuzzy logic · Flower pollination algorithm · Metaheuristic · Bioinspired algorithm 1 Introduction Nature is a great source of inspiration to develop new optimization algorithms. Opti- mizing systems in real life is complex and difficult and many applications face these problems, optimization algorithms can be used to solve them, which does not guarantee that an optimal solution can be obtained [1], nature has been able through millions of years to solve these problems, many biological systems have demonstrated very effectively in problem solving [2–4]. Many difficult problems in industry, commerce, medicine, etc., have been solved with the help of bioinspired optimization algorithms [2, 4, 5]. Science has been developing nature-inspired optimization algorithms like the Bat Algorithm (BA) [1] and the Flower Pollination Algorithm (FPA) [6], to name a few. Since its origin, flower plants have been evolving and dominate the landscape [5, H. Carreon · F. Valdez (B ) Tijuana Institute of Technology, Tijuana, BC, Mexico e-mail: fevrier@tectijuana.mx © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Melin et al. (eds.), Recent Advances of Hybrid Intelligent Systems Based on Soft Computing, Studies in Computational Intelligence 915, https://doi.org/10.1007/978-3-030-58728-4_8 145