A stochastic programming approach to design perishable product supply chain network under different disruptions

Abstract

Considering today’s market competition, operational challenges, uncertain events, and demand volatility, industry practitioners face tremendous challenges as a decision makers. The purpose of this study is to identify, examine and suggest feasible solutions to Supply Chain (SC) practitioners under various disruptions. The operational level challenges are high for perishable product supply chains due to lack of proper infrastructure, inadequate cold storage, government interventions and improper transportation etc. compared to traditional manufacturing and automobile SC. The attempt is made in this study to gauge the effect of supplier and quality disruption on SC operations. In order to achieve this, we have adopted a two stage stochastic programming approach to provide solutions related to ordering inventories, finding inefficient linkages in existing SC network and calculating respective SC cost. For this a SC configuration consists of two stages is considered along with two foreign suppliers and a local supplier with two distribution centers. The distribution centers receive supply of goods on regular basis from local suppliers as well as from foreign collaboration. However, in the face of uncertainty the distribution centers have to order emergency quantities from local supplier incurring extra cost depending on order size. The literature fails to consider partial order fulfillment even under cases of disruption. Our mathematical formulation has covered this missing gap and is solved using CPLEX (V.12) optimization package. Apart from this we have also performed an uncertainty analysis using @Risk. As the model is time-independent, we restrict our analysis without considering such parameters into proposed study. Moreover, incorporating such dimensions will always be a scope of future study.