Underground mine scheduling under uncertainty

Peter Nesbitt, Lewis R. Blake, Patricio Lamas, Marcos Goycoolea, Bernardo K. Pagnoncelli, Alexandra Newman, Andrea Brickey

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)340-352
Number of pages13
JournalEuropean Journal of Operational Research
Volume294
Issue number1
DOIs
StatePublished - 1 Oct 2021

Keywords

  • OR in natural resources
  • Optimization-based heuristics
  • Project scheduling
  • Stochastic integer programming
  • Underground mining

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