(1. 北京科技大学 土木与资源工程学院，北京 100083；
2. 金属矿山高效开采与安全教育部重点实验室，北京 100083)
摘 要: 针对传统矿山生产计划编制忽略品位不确定性造成的地质资源风险问题，提出构建基于条件模拟和随机规划的地下矿山生产计划风险集成优化模型。条件模拟以一组等概率的矿体模拟实现反映品位估值的不确定性，并通过随机规划将地质品位风险的量化评估直接集成到矿山生产计划优化建模过程。在最大化经济收益的同时有效衡量和降低由于地质不确定性带来的风险，提高生产计划的可行性，实现生产计划编制的科学可靠和合理有效。以某地下黄金矿山的生产计划编制为应用案例，对未来12个时期的生产计划进行优化。结果表明：模型在优化经济效益的同时可对地质风险进行有效管控，为矿山生产计划中地质风险评估提供新的方法。
关键字: 品位不确定性；直接序贯模拟；随机规划；生产计划；地下矿山
（1. School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China;
2. Key Laboratory of High-Efficient Mining and Safety of Metal Mines, Ministry of Education, Beijing100083, China）
Abstract:Traditional mine planning optimization ignores the presence of geological uncertainty causing most of the mine forecasts to be unrealistic. To overcome these problems, a risk-integrated mine planning framework was presented to optimize the mining production schedule based on conditional simulation and stochastic mixed integer programming. With conditional simulation, the risks from grade uncertainty in ore reserves can be measured and managed through a set of equally probable orebody realizations. And stochastic programming allows the integration of grade uncertainty into the production scheduling optimization process directly. The stochastic optimization model presented herein is to maximize the net present value and minimize the risk of deviation from operating and financial targets simultaneously. To demonstrate the applicability of the formulation, a long-term production scheduling case study on an underground gold mining complex was implemented. The results show that the capability of the model to control the effects of grade uncertainty, which provides a new method for mining risk evaluation.
Key words: grade uncertainty; direct sequential simulation; stochastic programming; production scheduling; underground mine
