Computing centroid of general type-2 fuzzy set using constrained switching algorithm

Centroid of general type-2 fuzzy set can be used as a measure of uncertainty in highly uncertain environments. computing centroid of general type-2 fuzzy set has received an increasing research attention during recent years. although computation complexity of such sets is higher than that of interval type-2 fuzzy sets, with the advent of new representation techniques, e.g. α-planes and z-slices, computation efforts needed to deal with general type-2 fuzzy sets have decremented. a very first method to calculate the centroid of a general type-2 fuzzy set was to use karnik-mendel algorithm on each α- plane, independently. because of the iterative nature of this method, running time in this approach is rather high. to tackle such a drawback, several emerging algorithms such as sampling method, centroid-flow algorithm, and, recently, monotone centroid- flow algorithm have been proposed. the aim of this paper is to present a new method to calculate centroid intervals of each α-plane, independently, while reducing convergence time compared with other algorithms like iterative use of karnik-mendel algorithm on each α-plane. the proposed approach is based on estimating an initial switch point for each α-plane. exhaustive computations demonstrate that the proposed method is considerably faster than independent implementation of existing iterative methods on each α-plane.