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Optimization-based heuristics for underground mine scheduling

机译:基于优化的启发式地下矿井调度

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Underground mine production scheduling possesses mathematical structure similar to and yields many of the same challenges as general scheduling problems. That is, binary variables represent the time at which various activities are scheduled. Typical objectives seek to minimize costs or some measure of production time, or to maximize net present value; two principal types of constraints exist: (i) resource constraints and (ii) precedence constraints. In our setting, we maximize "discounted metal production" for the remaining life of an underground lead and zinc mine that uses three different underground methods to extract the ore. Resource constraints limit the grade, tonnage, and backfill paste (used for structural stability) in each time period, while precedence constraints enforce the sequence in which extraction (and backfill) is performed in accordance with the underground mining methods used. We tailor exact and heuristic approaches to reduce model size, and develop an optimization-based decomposition heuristic; both of these methods transform a computationally intractable problem to one for which we obtain solutions in seconds, or, at most, hours for problem instances based on data sets from the Lisheen mine near Thurles, Ireland. (C) 2014 Elsevier B.V. All rights reserved.
机译:地下矿山生产调度具有与常规调度问题类似的数学结构,并带来许多相同的挑战。即,二进制变量表示计划各种活动的时间。典型的目标是寻求最小化成本或某种程度的生产时间,或最大化净现值。存在两种主要类型的约束:(i)资源约束和(ii)优先约束。在我们的环境中,我们在使用三种不同的地下方法提取矿石的地下铅锌矿山的剩余寿命中,最大限度地提高了“折扣金属生产”。资源约束限制了每个时间段的品位,吨位和回填浆糊(用于结构稳定性),而优先约束则限制了根据使用的地下采矿方法进行提取(和回填)的顺序。我们量身定制精确而启发式的方法以减小模型大小,并开发基于优化的分解启发式方法;这两种方法都将计算上难以解决的问题转化为一个问题,我们可以根据来自爱尔兰瑟尔斯附近的Lisheen矿山的数据集,在几秒钟内(最多几小时)获得问题实例的解决方案。 (C)2014 Elsevier B.V.保留所有权利。

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