Incorporating Drift in Long-hole Stope Optimization Using Network Flow Algorithm

We present an algorithm aimed at optimizing stope design accounting for drift development. The approach is typically suitable for the sublevel stope mining method with a vertical parallel drilling pattern. The algorithm consists of two parts. In the first part, a graph theory based stope optimizer is adapted to integrate the drift. In the stope optimizer, the raise initiates a stope and provides the parameters of drift level and draw point level. An ore model in cylindrical coordinates is defined around the raise. The geometric constraints on hanging wall and footwall slopes are translated as vertical precedence relations between blocks. The stope width is controlled by horizontal precedence relations. Similarly, the dependency of blocks in stope to blocks in drift is expressed in the graph. By solving the maximum flow problem with efficient push-relabel algorithm, the conditional optimal stope corresponding to the current raise location and height is obtained. The second part finds the best raise location and height. The genetic algorithm is used with the objective function defined as the (conditional) stope profit associated to a given raise location and height, computed in the first part. The performance of the algorithm is evaluated with a synthetic deposit and a real deposit. Comparison is made with the stope optimizer without a drift. The proposed method is shown to provide higher stope profit, with less dilution and less costs for the drift.