Robust Planning for an Open-Pit Mining Problem under Ore-Grade Uncertainty

Open-pit mining production planning is a risky problem: operation costs are considerable, many parameters are inherently subject to uncertainty and, moreover, the mining operation can only be done once. In this work we address uncertainty in the ore-grade, where we only assume the availability of an i.i.d. sample of the joint distribution of ore-grade in the blocks of the mining site. We consider an open-pit mining problem involving extraction and processing decisions under capacity constraints. We apply and compare the risk-hedging performance of three approaches for optimization under uncertainty: Value-at-Risk, Conditional Value-at-Risk and a proposed robust optimization approach. The latter is shown to have desirable risk-averse properties. Computational results on one small size vein-type mine are shown.