Resilient supply chain design under operational and disruption risks considering quantity discount: A case study of pharmaceutical supply chain

Abstract

Abstract Nowadays, one of the main objectives of supply chain design is to lessen the supply chain-threatening risks in order to reduce costs, preserve market share, and satisfy stakeholders. This paper presents an integrated hybrid approach based on data envelopment analysis (DEA) and mathematical programming method to design a resilient supply chain. First, the efficiency of potential suppliers is evaluated by a fuzzy DEA model. Afterwards, using the obtained efficiency, a two-stage possibilistic-stochastic programming model is developed for integrated supplier selection and supply chain design under disruption and operational risks. The model incorporates partial and complete disruptions of suppliers as well as quantity discount for procurement of various raw materials. Furthermore, we utilize several proactive strategies such as fortification and pre-positioning emergency inventory at fortified suppliers, and using multiple sourcing to enhance the resiliency of supply chain. Atra pharmaceutical company (APC) is used as a case study to investigate the applicability of the proposed model and analyze the solution results. The results indicate the validation of proposed model and the impact of various resiliency strategies.