ORE extraction and blending optimization model in poly- metallic open PIT mines by chance constrained one-sided goal programming

Abstract

Determination a sequence of extracting ore is one of the most important problems in mine annual production scheduling. Production scheduling affects mining performance especially in a poly-metallic open pit mine with considering the imposed operational and physical constraints mandated by high levels of reliability in relation to the obtained actual results. One of the important operational constraints for optimization is the uniformity of metallic minerals grade after the blending process. This constraint directly affects the performance of the mineral processing plant. The sequence of extracting ore is usually determined by the order of pushbacks, which should be mined. Metallic minerals' grade in each pushback is stochastic in nature that comes from some statistical errors committed by the sampling. In such situations, decision making about the order of pushbacks for extraction as an exact defined process is not possible. Moreover, the decision-maker should maximize the total Net Present Value NPV as the main objective of mining operations by considering the high performance of mineral processing plant. To deal with such cases, this research proposes a model based on the chance-constrained one-sided goal-programming and the obtained results from this procedure confirms the model's reliability and correctness.