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Paper detail

Advanced Ore Mine Optimisation under Uncertainty Using Evolution

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.

preprint2021arXivOpen access
William ReidAneta NeumannSimon RatcliffeFrank Neumann
Neural and Evolutionary ComputingMachine Learning
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William ReidAneta NeumannSimon RatcliffeFrank Neumann

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