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Advanced Ore Mine Optimisation under Uncertainty Using Evolution

arXiv 2102.05235 ↗First posted 10 Feb 2021cs.LG cs.NEcited by 0

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Abstract (arXiv)

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.

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  1. 2016A study of the Bienstock-Zuckerberg algorithm, Applications in Mining and Resource Constrained Project Schedulingcited by 3

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