Performance Evaluation Of A New Stochastic Network Flow Approach To Optimal Open Pit Mine Design?Application At A Gold Mine - Synopsis

The optimal design of production phases and ultimate pit limit for an open pit mining operation may be generated using conventional or stochastic approaches. Unlike the conventional approach, the stochastic framework accounts for expected variability and uncertainty in metal content by considering a set of equally probable realizations (models) of the orebody. This paper evaluates the performance of a new stochastic network flow approach for the development of optimal phase design and ultimate pit limit using a gold deposit as the case study. The stochastic and conventional frameworks as considered here utilize the maximum flow and Lerchs-Grossman (LG) algorithms, respectively. The LG algorithm is restricted to considering an estimated (average-type) orebody model, while the stochastic maximum flow algorithm is developed to simultaneously use a set of simulated orebody realizations as an input. The case study demonstrates that, when compared to the conventional LG algorithm as used in the industry, the stochastic approach generates a 30 per cent increase in discounted cash flow, a 21 per cent larger ultimate pit limit, and about 7 per cent more metal, while it maintains a consistency in phase size.