Abstract

According to the important role of the mining industry in the economic growth of developing countries, this industry is taken into consideration significantly. However, few studies have been conducted on developing mining supply chains that take into account the unique conditions of this industry, such as disruptions and product quality. This paper proposes a multi-period, multi-product mixed-integer quadratic programming problem to optimize a closed-loop stone supply chain network design. Compared to previous studies, we consider resilience in the mining supply chain for the first time. Furthermore, the quality characteristics of extracted and final stones are considered in a developed reliable model, and two-stage stochastic programming is applied to handle the quality uncertainty in the mining supply chain. Additionally, a price-dependent demand is considered in this research to investigate the competition between local and imported stone prices. A real-world case study on Iranian stone mining is analyzed to demonstrate the efficiency and applicability of the proposed model. Finally, some managerial insights are presented as guidance to managers of the mentioned supply chain to help them make better decisions. The results show that the transportation costs impact profit more than the operational costs. Moreover, West Azerbaijan and Isfahan have great potential for being the poles of stone in Iran. West Azerbaijan is also appropriate for exporting stones to neighboring countries, geographically.

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