  In this paper, we investigate the impact of uncertainty in advanced ore mine
optimisation. We consider Maptek's software system Evolution which optimizes
extraction sequences based on evolutionary computation techniques and quantify
the uncertainty of the obtained solutions with respect to the ore deposit based
on predictions obtained by ensembles of neural networks. Furthermore, we
investigate the impact of staging on the obtained optimized solutions and
discuss a wide range of components for this large scale stochastic optimisation
problem which allow to mitigate the uncertainty in the ore deposit while
maintaining high profitability.
