Underground mine scheduling under uncertainty

•We propose a stochastic integer programming framework.•It characterizes duration and value uncertainty for each underground mining activity.•An optimization-based heuristic solves the scheduling model.•We produce implementable, tactical schedules in a practical amount of time.•We provide correspond...

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Bibliographic Details
Published in:European journal of operational research Vol. 294; no. 1; pp. 340 - 352
Main Authors: Nesbitt, Peter, Blake, Lewis R., Lamas, Patricio, Goycoolea, Marcos, Pagnoncelli, Bernardo K., Newman, Alexandra, Brickey, Andrea
Format: Journal Article
Language:English
Published: Elsevier B.V 01.10.2021
Subjects:
Optimization-based heuristics
OR in natural resources
Project scheduling
Stochastic integer programming
Underground mining
OR in natural resources
Project scheduling
Optimization-based heuristics
Underground mining
Stochastic integer programming
ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary:•We propose a stochastic integer programming framework.•It characterizes duration and value uncertainty for each underground mining activity.•An optimization-based heuristic solves the scheduling model.•We produce implementable, tactical schedules in a practical amount of time.•We provide corresponding managerial insights. Underground mine schedules seek to determine start dates for activities related to the extraction of ore, often with an objective of maximizing net present value; constraints enforce geotechnical precedence between activities, and restrict resource consumption on a per-time-period basis, e.g., development footage and extracted tons. Strategic schedules address these start dates at a coarse level, whereas tactical schedules must account for the day-to-day variability of underground mine operations, such as unanticipated equipment breakdowns and ground conditions, both of which might slow production. At the time of this writing, the underground mine scheduling literature is dominated by a deterministic treatment of the problem, usually modeled as a Resource Constrained Project Scheduling Problem (RCPSP), which precludes mine operators from reacting to unforeseen circumstances. Therefore, we propose a stochastic integer programming framework that: (i) characterizes uncertainty in duration and economic value for each underground mining activity; (ii) formulates a new stochastic variant of the RCPSP; (iii) suggests an optimization-based heuristic; and, (iv) produces implementable, tactical schedules in a practical amount of time and provides corresponding managerial insights.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2021.01.011