LAUSR

High production rates and low operating costs highlight block caving as one of the favorable underground mining methods. However, the uncertainties involved in the material flow make it complicated to optimize the production schedule for such operations. In this paper, a stochastic mixed-integer linear optimization model is proposed in order to capture horizontal mixing that occurs among the draw columns within the production scheduling optimization. The goal is to not only consider the material above each drawpoint for extraction from the same drawpoint, as traditional production scheduling does, but also to capture the horizontal movements among the adjacent draw columns. In this approach, different scenarios are generated to simulate the horizontal mixing among adjacent slices within a neighborhood radius. The best height of draw for draw columns is also calculated as part of the optimization. The model is tested for a block-cave mine with 640 drawpoints to feed a processing plant for 15 years. The resulting NPV is 473M$ while the deviations from the targets in all scenarios during the life of the mine are minimized. Using the proposed model will result in more reliable mine plans as it takes the horizontal mixing into account in addition to achieving the production goals. Using different penalties for grade deviations shows that the model is a flexible tool in which the mine planners can achieve their goals based on their priorities.