Multi-Sourcing Resilient Supplier Selection Under Operational Disruptions

Abstract

Recognizing the inevitability of large scale disruptions, managers in supply chains have shifted their focus in decision making from prevention and protection to resilience. Resilience is the ability of a supply chain to withstand, adapt to and recover from a disruption to a desired performance level. With the rise in global interconnectivity supply chain networks have become highly dependent on suppliers located in various offshore locations. The interdependency of these networks has made them prone to disruptive events depending on their location. Disruptions are caused by events like malevolent attacks, natural disasters, production failures etc. One such event could hamper the functioning of supply chains; hence it is important for suppliers to have contingency plans to return the network to desired level of performance. The resilience capacity of the suppliers can be improved from three dimensions: absorptive capacity (their ability to pre-position inventory), adaptive capacity (their ability to subcontract proportionate goods to another party) and restorative capacity (their ability to recover lost capacity). This work addresses resilient supplier selection by improving the absorptive capacity of the suppliers. This problem has been modeled as a supplier selection decision framework that implements a multi objective optimization framework which includes traditional supplier selection objectives like cost, lead time and added objectives related to the absorptive capacity. This work demonstrates the use of the framework through an illustrative example of a supply chain network under various scenarios of disruption. These scenarios help to understand how the resilience of the network improves with added absorptive capacity.