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Approaches based on computing with words find good applicability in decisionmaking systems. Predominantly finding their basis in type-1 fuzzy sets,computing with words approaches employ type-1 fuzzy sets as semantics of thelinguistic terms. However, type-2 fuzzy sets have been proven to bescientifically more appropriate to represent linguistic information inpractical systems. They take into account both the intra-uncertainty as well asthe inter-uncertainty in cases where the linguistic information comes from agroup of experts. Hence in this paper, we propose to introduce linguistic termswhose semantics are denoted by interval type-2 fuzzy sets within the hesitantfuzzy linguistic term set framework, resulting in type-2 fuzzy sets basedhesitant fuzzy linguistic term sets. We also introduce a novel method ofcomputing type-2 fuzzy envelopes out of multiple interval type-2 fuzzy setswith trapezoidal membership functions. Furthermore, the proposed framework withinterval type-2 fuzzy sets is applied on a supplier performance evaluationscenario. Since humans are predominantly involved in the entire process ofsupply chain, their feedback is crucial while deciding many factors. Towardsthe end of the paper, we compare our presented model with various existingmodels and demonstrate the advantages of the former.

Type-2 Fuzzy Set based Hesitant Fuzzy Linguistic Term Sets for Linguistic Decision Making