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Applications of simulation and optimization techniques in optimizing room and pillar mining systems.

机译：模拟和优化技术在优化机房和矿井开采系统中的应用。

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摘要

The goal of this research was to apply simulation and optimization techniques in solving mine design and production sequencing problems in room and pillar mines (R&P). The specific objectives were to: (1) apply Discrete Event Simulation (DES) to determine the optimal width of coal R&P panels under specific mining conditions; (2) investigate if the shuttle car fleet size used to mine a particular panel width is optimal in different segments of the panel; (3) test the hypothesis that binary integer linear programming (BILP) can be used to account for mining risk in R&P long range mine production sequencing; and (4) test the hypothesis that heuristic pre-processing can be used to increase the computational efficiency of branch and cut solutions to the BILP problem of R&P mine sequencing.;A DES model of an existing R&P mine was built, that is capable of evaluating the effect of variable panel width on the unit cost and productivity of the mining system. For the system and operating conditions evaluated, the result showed that a 17-entry panel is optimal. The result also showed that, for the 17-entry panel studied, four shuttle cars per continuous miner is optimal for 80% of the defined mining segments with three shuttle cars optimal for the other 20%. The research successfully incorporated risk management into the R&P production sequencing problem, modeling the problem as BILP with block aggregation to minimize computational complexity. Three pre-processing algorithms based on generating problem-specific cutting planes were developed and used to investigate whether heuristic pre-processing can increase computational efficiency. Although, in some instances, the implemented pre-processing algorithms improved computational efficiency, the overall computational times were higher due to the high cost of generating the cutting planes.
机译：这项研究的目的是将模拟和优化技术应用于解决室内矿和支柱矿（R＆P）中的矿山设计和生产排序问题。具体目标是：（1）应用离散事件模拟（DES）确定在特定开采条件下煤炭R＆P板的最佳宽度； （2）研究用于开采特定面板宽度的穿梭车队规模在面板的不同部分是否最佳； （3）检验在R＆P远程矿山生产排序中可以使用二进制整数线性规划（BILP）来考虑采矿风险的假设； （4）检验可以使用启发式预处理来提高R＆P矿山排序BILP问题的分支和割解决方案的计算效率的假设。；建立了现有R＆P矿山的DES模型，该模型能够评估可变面板宽度对采矿系统的单位成本和生产率的影响。对于所评估的系统和操作条件，结果显示一个17个条目的面板是最佳的。结果还显示，对于所研究的17个入口的小组，每个连续采矿机四辆穿梭车对于80％的已定义采矿段而言是最佳的，而三辆穿梭车对于其他20％而言是最佳的。该研究成功地将风险管理纳入了R＆P生产排序问题中，将该问题建模为具有块聚合的BILP，以最大程度地减少了计算复杂性。开发了三种基于生成特定于问题的切割平面的预处理算法，并用于研究启发式预处理是否可以提高计算效率。尽管在某些情况下，已实施的预处理算法提高了计算效率，但由于生成切割平面的成本较高，因此总的计算时间更长。

著录项

  • 作者

    Anani, Angelina Konadu.;

  • 作者单位

    Missouri University of Science and Technology.;

  • 授予单位 Missouri University of Science and Technology.;
  • 学科 Mining engineering.;Operations research.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 242 p.
  • 总页数 242
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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