Dig-limit Optimization: Mixed Integer Linear Programming for grade control in open-pit mining

In open-pit mining on a bench level, the dig-limit optimization problem is deciding whether to classify a Selective Mining Unit(SMU) as waste or whether to classify it as ore. SMU’s with high ore grades are profitable for the mining operation, but due to equipment size a whole frame of SMU’s has to be classified as either ore or waste. In this thesis the dig-limit optimization problem will be solved using Mixed Integer Linear Programming (MILP). The model proposed in this thesis takes the frame constraint and the average grade constraint into account. The main results of the MILP model are in table 1. The results show that MILP can successfully be used to determine the optimal value of a mining operation, however the determination of the dig-limit for larger grids leads to exponential computation time.