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Modeling and optimization of vehicle operations in underground copper mining

In underground mining, daily a fleet of LHDs must be allocated to a haulage network of drifts for extracting ore according to a plan-driven strategy. This plan is hierarchically decided by a higher management level and it contains the number of ore bucketfuls to be extracted from each drawpoint within a drift for each working shift. In this paper, an integer programming (IP) model for minimizing the makespan of drift workload is formulated and a polynomial time optimal algorithm for its resolution is proposed. Next, a set of decision rules obtained from the algorithm above is integrated into the decision-making process (DMP). This DMP is simple to execute for LHD operators, determines the optimal makespan, and whether or not it can be carried out in the working shift. Finally, a comparative analysis between the DMP proposed and the DMP used in El Teniente copper underground Chilean mine is studied. The results show that the cumulative operators experience has converged to solutions near to optimal makespan.

Operations research in mining; polynomial time optimal algorithm; decision making process; mining vehicles fleet management


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