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.
翻译：在本文中,我们研究了矿矿矿先进优化的不确定性的影响。我们考虑了马普泰克的软件系统进化,根据进化计算技术优化提取序列,并根据神经网络组合的预测量化获得的矿石矿床解决方案的不确定性。此外,我们还调查了对获得的优化解决方案的集成影响,并讨论了这一大规模随机优化问题的广泛组成部分,这些组成部分可以缓解矿石矿床的不确定性,同时保持高利润率。
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