Intuitionistic Type-2 Fuzzy Soft Set based Decision Support Framework for Emergency Relief Supply Chain Planning

Abstract Hybrid uncertainty based models are more useful than the individual components. Earlier soft sets and intuitionistic fuzzy sets were combined to form intuitionistic fuzzy soft sets (IFSS) which are rich potentials for solving decision-making problems. Dan et al. (2020) introduced the concept of an intuitionistic type 2 fuzzy set (IT2FS), which is a direct extension of the intuitionistic fuzzy set. In this paper, using the concept of soft sets over the intuitionistic type-2 fuzzy sets, we define a new hybrid set and named it as Intuitionistic type-2 fuzzy soft sets (IT2FSS). After defining the set we present the set-theoretic operations such as complement, union, intersection over these sets and mention some algebraic properties with examples of these sets. After that, we define the level sets over IT2FSS and represent two decision-making algorithms based on level sets. We put forth definitions for score and accuracy functions and rules for the comparison of a group of IT2FSS. We carry out a IT2FSS based investigation to find out the key success factors for effective Humanitarian Supply Chain Management (HSCM) in emergency relief operations. We observe that supply chain financing, collaboration and coordination, and public governance are the three critical factors as opined by the experts for effective HSCM.