A two-stage stochastic programming model for a perishable products supply chain network design considering resiliency and responsiveness

The present scenario of supply chain management is full of uncertainty due to the intrinsic complexity of operating environments. A perishable products supply chain is not an exception and is often vulnerable to disruptive incidents throughout all stages from upstream to downstream. To deal with such a challenge, a resilient structure of the supply chain with the capability to recover from or react to disruptions is approached in this study. To secure the supply chain operations, we investigate a set of proactive strategies, including signing contracts with backup suppliers, reserving extra capacity in production facilities, lateral transshipment, and keeping inventory. Using a two-stage stochastic programming model, this study examines the extent to which supply chain responsiveness and resilience are supportive. The proposed model is validated through a numerical example, and managerial insights are derived. The computational results are based on three analyses: (1) extracting the relationship between the cost function and the acceptable service levels, (2) examining the effectiveness of different strategies in managing disruptions, (3) and evaluating the accuracy of the two-stage stochastic programming approach in comparison with other approaches.