露天矿优化调度问题的自适应策略
Adaptive Strategies for The Open-Pit Mine Optimal Scheduling Problem
摘要：
在采矿学科中，矿山规划是研究如何将有关矿产资源的信息转化为所有者价值的组成部分。对于露天矿，最优块调度最大化提取块的贴现值（逐期），称为净现值（NPV）。然而，为了可行，采矿进度表必须考虑坡度限制。最优露天矿块调度问题（OPBSP），因此，在寻找这样一个最优的时间表。一方面，我们引入动态优化方法，在确定性的情况下，矿山调度，我们提出了一类（次优）自适应策略，所谓的索引策略。我们表明，他们提供了上界和下界的净现值，我们提供了数值结果。另一方面，我们介绍了一个理论框架下的不确定性和学习的OPBSP。
英文摘要：
Within the mining discipline, mine planning is the component that studies how to transform the information about the ore resources into value for the owner. For open-pit mines, an optimal block scheduling maximizes the discounted value of the extracted blocks (period by period), called the net present value (NPV). However, to be feasible, a mine schedule must respect the slope constraints. The optimal open-pit block scheduling problem (OPBSP) consists, therefore, in finding such an optimal schedule. On the one hand, we introduce the dynamical optimization approach to mine scheduling in the deterministic case, and we propose a class of (suboptimal) adaptive strategies, the so-called index strategies. We show that they provide upper and lower bounds for the NPV, and we provide numerical results. On the other hand, we introduce a theoretical framework for OPBSP under uncertainty and learning.
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