Abstract
Over recent years, new methods have been developed to integrate uncertainty into the optimisation of life-of-mine production planning. One of these methods is based on scheduling with a simulated annealing (SA) algorithm and equally probable realisations of a given mineral deposit. The latter realisations are used to generate production schedules that minimise the possibility of deviating from production targets, and result in schedules with a substantial improvement in the net present value (NPV), shown to be in the order of 25% when compared to conventional scheduling within the conventionally optimal pit limits. To facilitate the utilisation of this method, a sensitivity analysis is presented in this study. The study documents the case of a copper deposit where 10 simulated realisations are sufficient to provide stable life-of-mine optimisation results. In addition, the study shows that the selected true optimal pit limits are larger than those derived through conventional optimisation. Stochastically optimised pit limits are found to be ∼17% larger, in terms of total tonnage, than the conventional (deterministic) optimal pit limits. The difference adds one year of mining and ∼10% of additional NPV when compared to the NPV of conventional optimal pit limits and a production schedule generated stochastically with the same simulated annealing algorithm.