Type-2 Fuzzy Set based Hesitant Fuzzy Linguistic Term Sets for
  Linguistic Decision Making
  Approaches based on computing with words find good applicability in decision
making systems. Predominantly finding their basis in type-1 fuzzy sets,
computing with words approaches employ type-1 fuzzy sets as semantics of the
linguistic terms. However, type-2 fuzzy sets have been proven to be
scientifically more appropriate to represent linguistic information in
practical systems. They take into account both the intra-uncertainty as well as
the inter-uncertainty in cases where the linguistic information comes from a
group of experts. Hence in this paper, we propose to introduce linguistic terms
whose semantics are denoted by interval type-2 fuzzy sets within the hesitant
fuzzy linguistic term set framework, resulting in type-2 fuzzy sets based
hesitant fuzzy linguistic term sets. We also introduce a novel method of
computing type-2 fuzzy envelopes out of multiple interval type-2 fuzzy sets
with trapezoidal membership functions. Furthermore, the proposed framework with
interval type-2 fuzzy sets is applied on a supplier performance evaluation
scenario. Since humans are predominantly involved in the entire process of
supply chain, their feedback is crucial while deciding many factors. Towards
the end of the paper, we compare our presented model with various existing
models and demonstrate the advantages of the former.
