Underground mine scheduling under uncertainty
| Autor: | Peter Nesbitt, Patricio Lamas, Alexandra M. Newman, Lewis R. Blake, Bernardo K. Pagnoncelli, Marcos Goycoolea, Andrea Brickey |
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| Přispěvatelé: | Naval Postgraduate School (U.S.), Operations Research |
| Rok vydání: | 2021 |
| Předmět: |
Schedule
OR in natural resources Information Systems and Management General Computer Science Operations research Computer science Heuristic (computer science) 0211 other engineering and technologies Underground mining (hard rock) Scheduling (production processes) 02 engineering and technology Management Science and Operations Research Net present value Industrial and Manufacturing Engineering Optimization-based heuristics Scheduling (computing) Stochastic integer programming 0502 economics and business Production (economics) Duration (project management) 050210 logistics & transportation 021103 operations research Heuristic 05 social sciences Modeling and Simulation Project scheduling Underground mining |
| Zdroj: | European Journal of Operational Research. 294:340-352 |
| ISSN: | 0377-2217 |
| DOI: | 10.1016/j.ejor.2021.01.011 |
| Popis: | 17 USC 105 interim-entered record; under review. The article of record as published may be found at http://dx.doi.org/10.1016/j.ejor.2021.01.011 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. National Institute of Occupational Safety and Health National Agency for Research and Development (ANID) |
| Databáze: | OpenAIRE |
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