Exact algorithms for production planning in mining considering the use of stockpiles and sequencing of power shovels in open-pit mines

Chile is the world's leading producer of copper, with a market share of 26.8% and accounting for approximately 10% of the gross domestic product. Given the importance of this industrial sector in the country, mine planning is a fundamental tool for achieving strategic, tactical and operational goals. This paper proposes methods to solve the problem of scheduling production in mining, considering the storage and sequencing of power shovels in open-pit mines. The first problem is tactical and operational and seeks to determine the extraction period and destination of each block. The second problem is of an operational nature and consists of defining the optimal sequence of block extraction, considering the mining power shovels. To solve both problems, two mixed integer linear programming models have been proposed and tested in real and random structured instances. The objective function of the proposed models is to maximize the net present value (NPV) of scheduling and maximize the work efficiency of the power shovels in the extraction. The proposed models have been implemented in AMPL and have been solved through the IBM CPLEX and Gurobi solvers. The results show the efficiency of the proposed models, demonstrating that including the storage option in the production schedule increases the operational NPV.