Advanced Ore Mine Optimisation under Uncertainty Using Evolution
This addresses uncertainty management in large-scale stochastic optimization for mining operations, but appears incremental as it builds on existing software and methods.
The paper tackles uncertainty in ore mine optimization using Maptek's Evolution software, quantifying solution uncertainty with neural network ensembles and investigating staging to maintain profitability while mitigating deposit uncertainty.
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.