A robust bi-level programming model to enhance resilience in supply chain network considering government role, taxing, and raw sale: An iron ore case study

The mining industry plays a substantial role in any economy because of its enormous influence on other sections of a country. Despite the significant challenges in this industry, such as government regulations, taxing policies, raw material sales, and disruptions, there are rare studies that have considered mining supply chain network design. Thus, this paper proposes a mixed-integer linear bi-level programming model under operational and disruption risks to design a robust and resilient mining supply chain network. The government is considered as the leader that aims to decrease the sales of raw materials, boost the export of final products, and maximize its profit. Moreover, the closed-loop mining supply chain is introduced as the follower level that maximizes the total profit. In other words, this study presents a bi-level model that balances the export of raw materials and final products, for the first time. Additionally, a data envelopment analysis approach is applied to rank the candidate mine areas and reduce the model's complexity. Finally, a real-world case study of the Iranian iron ore supply chain is applied to demonstrate the efficiency and applicability of the addressed model. The results indicate that the effect of raw material price on the upper level is 22% higher than the lower level under the same conditions. Moreover, the exchange rate has a great impact on the objective functions of both levels. Furthermore, Yazd province has great potential to be introduced as a steel pole in Iran.