An integrated simulation and optimization tool for short-term mining planning problems with different prioritization among competing plant targets

This work proposes a tool that integrates a hierarchical mixed-integer linear programming (MILP) model with a discrete event simulation (DES) model to simulate an annual mining plan discretized in shift-by-shift periods. The hierarchical MILP model has ten objectives and optimizes the shift schedule according to the available materials in the free faces at each simulation moment. The DES model simulates the realization of this schedule considering the uncertainties and interactions between the mine’s equipment. Four scenarios from a Brazilian mining company were analyzed. These differ regarding the prioritization order of the MILP goals and the plants’ grade tolerance. The results report that prioritizing the plant with the highest value-added product results in a 7.0% production gain. Additionally, prioritizing the particle size target of the plants leads to a 2.5% production gain compared to prioritizing the element grade targets.