An integrated material-financial risk-averse resilient supply chain model with a real-world application

Abstract

Nowadays supply chains are facing disruptive events, and their adverse effects on supply chain performance, more than ever before. Disruptions can impact supply chain operations considerably, therefore it is of paramount importance to design resilient supply chains that are able to perform well under risks caused by such events. Also, supply chain management involves making decisions regarding material and financial flows. Usually, these decisions are taken independently. Doing so can result in infeasible plans. That is why designing comprehensive models that integrate decisions regarding material and financial flows is important. In this paper, we offer a resilient supply chain model capable of performing well under disruptions and consider material and financial decisions concurrently. To increase the resilience of the supply chain we investigated several resilient strategies including multiple sourcing, emergency inventory, and additional production capacity. Possibilistic programming is used to model disruption risks. Two-stage stochastic programming is used to consider uncertain demand for products. Furthermore, to incorporate financial flows into the model, we considered financing strategies, including the use of trade-credit and bank-credit. Using Conditional-Value-at-risk, we formulated a robust optimization model capable of performing well under worst-case scenarios. Finally, based on the computational experiments performed on a real-world case study as well as several test problems, the applicability of the presented model is confirmed and important managerial insights are presented. Results show that all three resilient strategies can improve supply chain performance. Moreover, it is concluded that incorporating different financing sources to purchase raw materials can positively increase supply chain profitability and improve supply chain performance when disruptions happen.