Abstract

Short-term planners must define an operational schedule based on blasthole data, which might be incomplete or imperfect. As a result, there is uncertainty in the true grade of each Selective Mining Unit. This can impact the definition of mining cuts and dig-limits, and the fulfillment of long-term targets. In this work, we propose a stochastic mixed integer program to define an operational mining cut configuration and a short-term schedule under grade uncertainty. The objective of the model is to maximize revenue and minimize deviations from production targets. We test the model using real data from a copper deposit and use grade simulations for quantifying the uncertainty in blasthole data. The results show that the stochastic model achieves higher profit margins and lower deviations from production targets compared to a deterministic variant based on a single estimated scenario. At the same time, the numerical experiments show the potential impact of blasthole uncertainty in profit and compliance of short-term schedules. Therefore, the use of this stochastic formulation can help planners find optimal mining cuts and improve target fulfillment and profitability of short-term operational plans in the presence of grade uncertainty. Finally, we propose several extensions to include new sources of uncertainty.