ABSTRACT
Uncertainty in mineral deposits causes deviations from the long-term production schedules of mines. As underground mining has high development and operational costs, it is crucial to incorporate the uncertainty in the planning stage. In this research, a new mixed integer linear program that solves the sublevel stope sequencing problem while accounting for the block grade uncertainty is proposed. The new linear programming model incorporates chance constrained programming to manage the risk of the project and to stabilize the expected net present value. In a case study, the effect of varying levels of risk is studied by generating stope sequences for different risk levels. The trade-off between risk and expected net present value is studied. It was found that at higher risk levels the stopes with higher average grade are extracted earlier while at lower risk levels stopes with lower standard deviation are prioritized.
