  Thus far, limited research has been performed on resilient supplier selection
- a problem that requires simultaneous consideration of a set of numerical and
linguistic evaluation criteria, which are substantially different from
traditional supplier selection problem. Essentially, resilient supplier
selection entails key sourcing decision for an organization to gain competitive
advantage. In the presence of multiple conflicting evaluation criteria,
contradicting decision makers, and imprecise decision relevant information
(DRI), this problem becomes even more difficult to solve with the classical
optimization approaches. However, prior research focusing on MCDA based
supplier selection problem has been lacking in the ability to provide a
seamless integration of numerical and linguistic evaluation criteria along with
the consideration of multiple decision makers. To address these challenges, we
present a comprehensive decision-making framework for ranking a set of
suppliers from resiliency perspective. The proposed algorithm is capable of
leveraging imprecise and aggregated DRI obtained from crisp numerical
assessments and reliability adjusted linguistic appraisals from a group of
decision makers. We adapt two popular tools - Single Valued Neutrosophic Sets
(SVNS) and Interval-valued fuzzy sets (IVFS), and for the first time extend
them to incorporate both crisp and linguistic evaluations in a group decision
making platform to obtain aggregated SVNS and IVFS decision matrix. This
information is then used to rank the resilient suppliers by using TOPSIS
method. We present a case study to illustrate the mechanism of the proposed
algorithm.
