Since its inception, fuzzy set theory has been widely used to model uncertainty and imprecision in decision-making. However, conventional fuzzy sets, often referred to as type-1 fuzzy sets (T1FSs), have limitations in capturing higher levels of uncertainty, particularly when decision-makers (DMs) express hesitation or ambiguity in membership degrees. To address this, interval type-2 fuzzy sets (IT2FSs) have been introduced by incorporating uncertainty in membership degree allocation, enhancing f
