Responsible optimization of long-term production scheduling in open-pit mines

Conventional open-pit production scheduling models often neglect environmental costs, government royalties, and operational penalties, resulting in economically optimistic but practically unrealistic mine plans. This study develops a Mixed-Integer Non-Linear Programming (MINLP) model for long-term production scheduling at the Kal-e Kafi copper deposit in Iran. The model explicitly integrates environmental costs, government royalties, and penalty costs for deviations from target mill feed tonnage and grade directly into the objective function and block economic value calculation. Implemented on a scaled block model comprising 20, 746 selective mining units and solved using the BARON 23. 1. 7 solver within a Divide and Conquer framework, the MINLP model achieves a net present value of 129. 34 million, a stripping ratio of 0. 64: 1, a mine life of 14 years, and extractable ore tonnage of 14. 24 million tonnes. Comparative analysis against the industry-standard Datamine NPV Scheduler reveals that although the commercial software reports a higher nominal NPV, it does so by externalizing environmental liabilities, royalty obligations, and operational penalties. The MINLP model demonstrates comparatively better operational efficiency through a lower stripping ratio, a longer mine life, and higher ore recovery. A comprehensive sensitivity analysis confirms model robustness, with the environmental cost elasticity near zero, indicating that internalizing environmental expenditures does not compromise economic competitiveness. These findings demonstrate that responsible mining produces field-realistic, operationally feasible, and economically defensible mine plans, bridging the gap between theoretical optimization and practical sustainability.