Mining cutoff grade strategy to optimise NPV based on multiyear GRG iterative factor

Abstract

One of the most difficult problems in a mining operation is how to determine the optimum minable cutoff grade over the lifespan of the mine that will maximise the operation net present value (NPV). Maximising the NPV in a mining operation, subject to different constraints, is a non-linear programming problem. Cutoff grade optimisation is used to determine the operating mining strategy that will maximise the total profit value of the mine. Constrained by the production capacity of the mill, and by sacrificing the mining low grade material, this approach enables the mill to process ore that delivers an improved time discounted cashflow. The cutoff grade policy calculated from the algorithm introduced in this paper has a significant influence on the overall economics of the mining operation. This paper describes the process to determine the cutoff grade strategy used in a mining operation based on Lane's algorithm using an optimisation factor which is iteratively calculated for every production year which dynamically adjusts the remaining reserves and thus the total life of the mine to maximise the project NPV. The introduced algorithm is an adaptation from Lane's algorithm that incorporates an iterative routine used to calculate the optimisation factor embedded in the cutoff grade equation. The algorithm was developed at Virginia Tech and runs using a windows visual basic program linked to a spreadsheet interface. The benefits of the methodology are demonstrated using a hypothetical case study. The authors have observed an improvement of the total NPV using the general reduced gradient (GRG) approach to iteratively calculate the optimisation factor for every production year.