Short-term underground mine planning with uncertain activity durations using constraint programming

IF 1.4 4区 工程技术 Q4 ENGINEERING, MANUFACTURING Journal of Scheduling Pub Date : 2024-04-26 DOI:10.1007/s10951-024-00808-x
Younes Aalian, Michel Gamache, Gilles Pesant
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Abstract

The short-term scheduling of activities in underground mines is an important step in mining operations. This procedure is a challenging optimization problem since it deals with many resources and activities conducted in a confined working space. Moreover, underground mining operations deal with multiple uncertainties such as the variation of activity durations. In this paper, a constraint programming (CP) model is proposed for short-term planning in underground mines. The developed model takes into account the technical requirements of underground operations to build realistic mine schedules. Furthermore, two different approaches are proposed based on the CP model for robust short-term underground mine scheduling. The first approach aims to create a robust schedule using multiple scenarios of the problem. This stochastic CP model enables to find a set of ordered robust sequences of activities performed by each available disjunctive resource over several scenarios. In the second approach, a confidence constraint is introduced in the CP model to specify the probability that the schedule generated would not underestimate the duration of activities. The model allows the mine planner to control the risk level with which an optimized solution should be produced such that it can be implemented given the actual activity durations. The presented approaches are tested on real data sets of an underground gold mine in Canada. An evaluation model is designed to evaluate the robust performance of the proposed models. The experiments demonstrate that both scenario-based and confidence-constraint approaches outperform the deterministic model by generating schedules that are more robust to uncertainties in underground operations.

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利用约束编程进行活动持续时间不确定的短期地下矿山规划
地下采矿活动的短期调度是采矿作业中的一个重要步骤。这个过程是一个具有挑战性的优化问题,因为它涉及到许多资源和在有限工作空间内开展的活动。此外,地下采矿作业还涉及多种不确定因素,如活动持续时间的变化。本文针对地下矿山的短期规划提出了一种约束编程(CP)模型。所开发的模型考虑了井下作业的技术要求,以制定切实可行的矿山计划。此外,本文还基于 CP 模型提出了两种不同的方法,用于制定稳健的短期地下矿山计划。第一种方法旨在利用问题的多种情景创建稳健的计划。这种随机 CP 模型能够在多个情景中找到一组有序的稳健活动序列,这些序列由每个可用的互不相关资源执行。在第二种方法中,CP 模型中引入了置信度约束,以规定生成的时间表不会低估活动持续时间的概率。通过该模型,矿山规划人员可以控制产生优化方案的风险水平,以便在实际活动持续时间的情况下实施优化方案。所介绍的方法在加拿大一个地下金矿的真实数据集上进行了测试。设计了一个评估模型来评估所提出模型的稳健性能。实验结果表明,基于情景和置信度约束的方法都优于确定性模型,它们生成的时间表对地下作业中的不确定性具有更强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Scheduling
Journal of Scheduling 工程技术-工程:制造
CiteScore
3.80
自引率
10.00%
发文量
49
审稿时长
6-12 weeks
期刊介绍: The Journal of Scheduling provides a recognized global forum for the publication of all forms of scheduling research. First published in June 1998, Journal of Scheduling covers advances in scheduling research, such as the latest techniques, applications, theoretical issues and novel approaches to problems. The journal is of direct relevance to the areas of Computer Science, Discrete Mathematics, Operational Research, Engineering, Management, Artificial Intelligence, Construction, Distribution, Manufacturing, Transport, Aerospace and Retail and Service Industries. These disciplines face complex scheduling needs and all stand to gain from advances in scheduling technology and understanding.
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