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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. [ABSTRACT FROM AUTHOR]

This work addresses open-pit mining operational planning with dynamic truck allocation. The problem involves determining the number of trips that each mining truck would do to each mining face, as well as deciding to which face the shovels are to be allocated, in order to meet the production and quality targets, and to achieve the best utilization of the available fleet. Due to the combinatorial complexity of the problem, it is solved using a heuristic algorithm based on the Iterated Local Search metaheuristic. The proposed algorithm is tested using real data and the results are compared against those produced by a LINGO-based mathematical programming model. [ABSTRACT FROM AUTHOR]