Innovation mine optimization tailored to iron ore operations: long and short term planning with dynamic truck dispatching

加拿大拥有约63亿吨粗铁矿石储量，在世界上排名第八。铁精矿（含铁62%）价格暴跌（从2011年2月的每吨187美元降至2016年初的每吨45美元）导致加拿大的一些业务停止，许多开发项目暂停。采矿业为当地社区和政府做出了重大贡献。因此，价格大幅下跌可能会产生深远的社会影响。应对这种负面经济氛围的唯一方法是找到创新的方法，确保运营的效率，性能，生产力，可持续性和/或盈利能力。这项研究提出了有效的矿山规划和优化方法，利用尖端的运营研究，决策，机器学习和不确定性管理工具，解决露天铁矿石运营的具体特点。首先，将进行多变量分析，以了解铁矿石变量之间的关系。考虑到矿石中可以包含一些低品位的物质，以一定的混合成本，以最大化矿石吨位的方式开发了一个新的矿石-废物鉴别模型。这一模式将作为投入用于长期规划。在整个参数化过程中，应不断更新这一矿石-废物方案。一个拉格朗日松弛的方法将进行调查，以找到适当的乘数，使年产量与能力的要求是兼容的。然后，短期规划和床层混合设计将优化连接克里格的关系。当短期计划通过计算效率高的元启发式算法解决处理设计的品位要求时，混床设计将使处理输入材料的品位波动最小化。短期计划的成功在一定程度上取决于设备管理。在这个范围内，一个有效的卡车调度策略将被探索。最后，将进一步调查与数据不确定性有关的敏感性和风险。因此，采矿业将有新的规划工具，侧重于铁矿石的具体特点。

Canada has approximately 6.3 billion tonnes crude iron ore reserves, which is ranked eighth in the world. The slump in iron ore concentrate (62% Fe) prices (from USD 187 per tonne in February 2011 to USD 45 per tonne at early 2016) led to cessations of some operations and suspensions of many development projects in Canada. Mining industry makes significant contribution to local communities and governments. As such, dramatic price decline may have profound societal effects. Only way to respond to this negative economic aura is to find innovative ways such that efficiency, performance, productivity, sustainability and/or profitability of an operation are ensured. This research proposes efficient mine planning and optimization approaches addressing to specific characteristics of open pit iron ore operations using cutting-edge operation research, decision making, machine learning and uncertainty management tools. First of all, a multi-variate analysis will be implemented to understand relationships among iron ore variables. A new ore - waste discrimination model will be developed in such a way as to maximize ore tonnage considering that some low grade material can be included in ore at a blending cost. This model will be used in long-term planning as an input. Throughout the parameterization, this ore - waste scheme should be updated continuously. A Lagrengian relaxation approach will be investigated to find appropriate multipliers such that annual productions are compatible with capacity requirements. Then, a short-term planning and bed-blending design will be optimized in connection to Krige's relationship. When short-term planning addresses grade requirements of processing design through a computationally efficient meta-heuristic, bed-blending design will minimize grade fluctuations of processing input material. The success of short-term planning, a certain extent, depends upon equipment management. In this scope, an efficient truck dispatching strategy will be explored. Finally, sensitivities and risks associated with data uncertainties will be further investigated. Thus, mining industry will have new planning tools that focuses on specific characteristics of iron ore.