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Extraction and Backfill Scheduling in a Complex Underground Mine

Author

Listed:
  • Dónal O’Sullivan

    (Division of Economics and Business, Colorado School of Mines, Golden, Colorado 80401)

  • Alexandra Newman

    (Division of Economics and Business, Colorado School of Mines, Golden, Colorado 80401)

Abstract

We use mathematical optimization to determine a production schedule (i.e., a schedule of extraction and subsequent filling of the voids) for a complex underground mine in Ireland. The goal of the mining operation is to maximize metal production over the life of the mine, subject to constraints on maximum monthly extraction and backfilling quantities, maximum and minimum monthly metal production, and sequencing between extraction and backfilling operations. We solve our integer programming model with a heuristic to produce a schedule that adds value to the mining operation by (1) shifting metal production forward, (2) reducing waste mining and backfilling delays, (3) avoiding expensive mill-halting drops in ore production, and (4) enabling smoother workforce management.

Suggested Citation

  • Dónal O’Sullivan & Alexandra Newman, 2014. "Extraction and Backfill Scheduling in a Complex Underground Mine," Interfaces, INFORMS, vol. 44(2), pages 204-221, April.
    • Handle: RePEc:inm:orinte:v:44:y:2014:i:2:p:204-221
    DOI: 10.1287/inte.2013.0730
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    References listed on IDEAS

    as
    1. Martinez, Michael A. & Newman, Alexandra M., 2011. "A solution approach for optimizing long- and short-term production scheduling at LKAB's Kiruna mine," European Journal of Operational Research, Elsevier, vol. 211(1), pages 184-197, May.
    2. W. Matthew Carlyle & B. Curtis Eaves, 2001. "Underground Planning at Stillwater Mining Company," Interfaces, INFORMS, vol. 31(4), pages 50-60, August.
    3. Newman, Alexandra M. & Kuchta, Mark, 2007. "Using aggregation to optimize long-term production planning at an underground mine," European Journal of Operational Research, Elsevier, vol. 176(2), pages 1205-1218, January.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Siyu Tu & Mingtao Jia & Liguan Wang & Shuzhao Feng & Shuang Huang, 2022. "A Multi-Equipment Task Assignment Model for the Horizontal Stripe Pre-Cut Mining Method," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    2. Lorenzo Reus & Mathias Belbèze & Hans Feddersen & Enrique Rubio, 2018. "Extraction Planning Under Capacity Uncertainty at the Chuquicamata Underground Mine," Interfaces, INFORMS, vol. 48(6), pages 543-555, November.
    3. Furtado e Faria, Matheus & Dimitrakopoulos, Roussos & Lopes Pinto, Cláudio Lúcio, 2022. "Integrated stochastic optimization of stope design and long-term underground mine production scheduling," Resources Policy, Elsevier, vol. 78(C).
    4. Barry King & Alexandra Newman, 2018. "Optimizing the Cutoff Grade for an Operational Underground Mine," Interfaces, INFORMS, vol. 48(4), pages 357-371, August.
    5. Mousavi, Amin & Sellers, Ewan, 2019. "Optimisation of production planning for an innovative hybrid underground mining method," Resources Policy, Elsevier, vol. 62(C), pages 184-192.
    6. Akshay Chowdu & Peter Nesbitt & Andrea Brickey & Alexandra M. Newman, 2022. "Operations Research in Underground Mine Planning: A Review," Interfaces, INFORMS, vol. 52(2), pages 109-132, March.
    7. Gonzalo Muñoz & Daniel Espinoza & Marcos Goycoolea & Eduardo Moreno & Maurice Queyranne & Orlando Rivera Letelier, 2018. "A study of the Bienstock–Zuckerberg algorithm: applications in mining and resource constrained project scheduling," Computational Optimization and Applications, Springer, vol. 69(2), pages 501-534, March.
    8. O’Sullivan, Dónal & Newman, Alexandra, 2015. "Optimization-based heuristics for underground mine scheduling," European Journal of Operational Research, Elsevier, vol. 241(1), pages 248-259.
    9. Nesbitt, Peter & Blake, Lewis R. & Lamas, Patricio & Goycoolea, Marcos & Pagnoncelli, Bernardo K. & Newman, Alexandra & Brickey, Andrea, 2021. "Underground mine scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 294(1), pages 340-352.

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