Schedule Optimization Considering Ore Blending and Nonlinear Geometallurgical Variables

Blending inevitably occurs to some degree during mining and mineral processing operations. Traditional mine scheduling assumes that all variables average linearly, which allows the calculation of the blended material properties as a linear weighted average. However, metallurgical properties such as metal recovery and Bond Work Index (BWI) are known to average nonlinearly. The nonlinear properties of the blended material can be calculated using nonlinear blending models. A simulated annealing algorithm is developed and applied to a short‐term mining face optimization problem to maximize the total metal recovered considering nonlinear blending. Compared to a standard schedule plan, the optimized one shows relevant improvements in synergistic and antagonistic blending behaviors.