ABSTRACT

Short-term planning typically involves optimising different mining complex components individually, preventing unlocking value from intercorrelated activities. This paper proposes an integrated framework that defines diglines and shovel allocation decisions to improve the operation’s financial performance. This involves a clustering approach, defining diglines and material destination; a simulator of the mining complex operations, forecasting the material flow from benches to processors; and an actor-critic reinforcement learning approach, assigning shovels to mining areas given operating requirements. A case study at a copper mining complex shows 27% cash flow improvements compared to a non-adaptive baseline approach provided by recent advances in the field.

摘要

短期规划通常涉及单独优化不同的采矿复杂组件，从而防止从相互关联的活动中释放价值。本文提出了一个综合框架，该框架定义了挖掘线和铲子分配决策，以提高运营的财务绩效。这涉及到集群方法，定义线路和材料目的地；采矿复杂作业的模拟器，预测从工作台到处理器的物料流；以及演员批评家强化学习方法，根据操作要求将铲子分配给矿区。铜矿综合体的案例研究表明，与该领域最新进展提供的非自适应基线方法相比，现金流量改善了 27%。