A review of general optimization studies that have been proposed for underground mining shows that previous works lack flexibility, operability and practicality in relation to cut-and-fill mining production scheduling. This paper presents a robust mixed integer linear programming (MILP) formulation for underground cut-and-fill mining. The objective function of the model is to maximize the net present value (NPV) of the operation while meeting all mining and processing operational and technical constraints. The MILP model features stope development and extraction sequencing constraints, mining and processing tonnage fluctuation constraints, and extraction duration and active levels control constraints. These features make the model more practical and expandable. The MILP model is verified and validated with two case studies from an existing mine and the results are compared with the actual mining strategy. The comparison shows a 9% to 17% improved NPV in both case studies resulting from mining higher grades and processing less tonnes thereby generating a better cash flow.

一项针对地下采矿的一般优化研究的综述表明，先前的工作在填埋式采矿生产调度方面缺乏灵活性，可操作性和实用性。本文提出了一种用于地下挖填的稳健的混合整数线性规划（MILP）公式。该模型的目标功能是在满足所有采矿和加工运营及技术约束的同时，最大化运营的净现值（NPV）。MILP模型具有采场开发和开采顺序约束，采矿和加工吨位波动约束以及开采持续时间和有效水平控制约束的特征。这些功能使模型更加实用和可扩展。通过对两个现有矿山进行案例研究，对MILP模型进行了验证和验证，并将结果与​​实际采矿策略进行了比较。比较显示，在两个案例研究中，由于开采较高品位和减少吨数而导致的净现值提高了9％至17％，从而产生了更好的现金流。