Group for Research in Decision Analysis

Mine Planning Optimization with Uncertainty: A Review of Concepts and Applications from Single Mines to Mining Complexes

Roussos Dimitrakopoulos Professor, Department of Mining and Materials Engineering, McGill University, Canada

Conventional approaches optimizing mine design and planning, production forecasting and valuation result in single, and often biased, forecasts. This is largely due to the non-linear propagation of errors in understanding orebodies being mined throughout the chain of mining to products, and is well documented and appreciated. A new stochastic mine planning paradigm is reviewed herein, integrating two broad elements: stochastic simulation and stochastic optimization. These elements provide an extended mathematical framework that allows modeling and direct integration of uncertainty in metal supply to mine design, production planning, and valuation of mining projects and operations. Several approaches and intricacies are overviewed along with applications in producing mines and are then extended to global optimization of mining complexes as a specific form of a supply chain. The stochastic framework is shown to increase the value of production schedules by about 25% and ore production is substantially increased when compared to deterministic approaches and industry standards to suggest a contribution to the sustainable utilization of natural resources.