Operations research in mining industry: Literature review and research opportunities

Industry sectors such as mining, automotive, aviation, and steelmaking have long been areas of significant scientific and technological interest. Rapid technological advances, competitive markets, fluctuations in raw material availability, and growing environmental concerns pose constant challenges for decision-makers. In the mining industry, these challenges are even more critical to ensure operational efficiency and long-term sustainability. The rising global demand for minerals — such as iron ore, coal, and copper — together with advances in hardware and software, has made the integration of Operations Research and Artificial Intelligence essential for developing advanced mathematical models and decision-support algorithms. This literature review analyzes research published between 2015 and 2025 addressing optimization problems across the three central nodes of the mining supply chain: mine, railway, and port. For each node, the study identifies the most relevant problems, mathematical formulations, and solution methods. It also highlights the growing importance of integrated mine–rail–port optimization, the treatment of uncertainty, and hybrid approaches combining mathematical programming, heuristics, and AI-based techniques. The review further discusses practical challenges for implementation, including data fragmentation, system integration, and the need to operate within environmental and regulatory requirements. Finally, this article introduces an original taxonomy for classifying optimization problems in the mining sector. The proposed classification integrates Graham’s scheduling notation with descriptors capturing production and logistics complexity, supporting both research advances and more informed decision-making in real mining supply chains. • A comprehensive literature review covering the period from 2015 to 2025. • The review covers the integrated mining chain: the mine, the railroad, and the port. • A wide variety of operational research problems and their solution approaches. • A new taxonomy for classifying operational research problems in the mining industry. • Identification of research gaps in the integrated mining chain.