Resilient supplier selection under a fuzzy environment

The aim of this research is to develop a quantitative approach for strategic supplier selection under a fuzzy environment in a disaster scenario. Disruption is a low probability high intensity event which causes long term system turbulence/unbalance. So resiliency planning is becoming a crucial strategic issue in the supplier selection process to keep pace with serving a globally competitive scenario. While crisp data are inadequate to model real life situations in fuzzy multiple criteria decision making, decision makers used linguistic variables to describe the importance of degrees of specific attributes. Triangular and trapezoidal linguistic data are used in determining supplier scores for various sub-criteria under general and resilient strategies, respectively. This paper presents an integrated fuzzy group decision making approach based on a fuzzy technique for order preference by similarity to the ideal solution integrated with the aggregate fuzzy weight method to rank the suppliers of a manufacturing system. Suppliers' weights for a general strategy and a resilient strategy are combined in sensitivity analysis, where decision makers' attitude plays an important role. Using this approach, organizations can devise resiliency plans to alleviate the vulnerability of a supply chain system. Although the methodology is illustrated through an application in automobile manufacturing, it can also be used in other discrete and process manufacturing industries.