A faster iterative computation of the centroid of an interval type-2 fuzzy set

This paper presents a new iterative algorithm for computing the centroid of an interval type-2 fuzzy set (also known as interval-valued fuzzy set). The algorithm uses precomputation to speed up its calculations and an initialization based on the concept of uncertainty bounds. Computational experiments over different kind of footprints of uncertainty and several discretization levels show that the new algorithm is much faster than methods such as the Enhanced Karnik-Mendel Algorithm (EKMA) and the Enhanced Iterative Algorithm with Stop Conditon (EIASC).