A mathematical model for optimizing cut-off grade and stockpiling policies in open pit mines with grade engineering

This paper investigates the optimization of cut-off grade (COG) and stockpiling policies for open-pit mines that integrate pre-concentration techniques, such as screening, as a distinct processing destination. A novel Grade Engineering (GE) model was developed, incorporating the variability of response ranking (RR) within the deposit, and the costs related to waste management. We employ a novel method combining grid search for comprehensive exploration and a real-coded genetic algorithm for efficient refinement to determine the optimal solution, considering geological, economic, operational, technical, and environmental aspects of the operation. Applied to a copper deposit, the framework demonstrates significant benefits, including a 5.2 % increase in metal recovery, a 11.6 % reduction in waste rock, a 19.7 % extension in mine life, and a 39.7 % boost in material classified as ore. These advancements translate into a 4.1 % increase in the project's net present value. The findings highlight the effectiveness of the proposed methodology in optimizing mining operations and underscore the potential of GE to advance sustainable and economically viable mining practices, providing practical insights for industry decision-makers.