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Optimizing the Cutoff Grade for an Operational Underground Mine

Author

Listed:
  • Barry King

    (Operations Research with Engineering PhD Program, Colorado School of Mines, Golden, Colorado 80401)

  • Alexandra Newman

    (Mechanical Engineering Department, Colorado School of Mines, Golden, Colorado 80401)

Abstract

An important strategic decision for any operational mine is the differentiation between ore and waste material; this differentiation is referred to as the cutoff grade. In underground mining, material classified as ore is extracted, while waste is left in situ. Our mixed-integer programming optimization framework determines the cutoff grades in three different, predetermined zones for a soon-to-be-operational underground mine. We fix all cutoff grades a priori to optimize the periods in which to complete each mining activity to maximize the net present value for this restricted problem. We then use an enumerative optimization framework that relaxes the fixed cutoff-grade assumption and constructs a schedule for each cutoff-grade combination for all three zones. This framework both exploits an underlying mathematical structure and identifies an optimum set of grades that unconditionally maximizes net present value under the existing zone configuration, thereby providing objective, repeatable, and superior solutions, verified by our industry partner, a major gold producer, for large-scale problems in a matter of days; current industry practice would produce solutions with lower net present value and based only on detailed analysis for a single zone, would require six to eight weeks and would preclude scenario analysis.

Suggested Citation

  • Barry King & Alexandra Newman, 2018. "Optimizing the Cutoff Grade for an Operational Underground Mine," Interfaces, INFORMS, vol. 48(4), pages 357-371, August.
    • Handle: RePEc:inm:orinte:v:48:y:2018:i:4:p:357-371
    DOI: 10.1287/inte.2017.0934
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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. Christopher Alford & Marcus Brazil & David H. Lee, 2007. "Optimisation in Underground Mining," International Series in Operations Research & Management Science, in: Andres Weintraub & Carlos Romero & Trond Bjørndal & Rafael Epstein & Jaime Miranda (ed.), Handbook Of Operations Research In Natural Resources, chapter 0, pages 561-577, Springer.
    3. Dónal O’Sullivan & Alexandra Newman, 2014. "Extraction and Backfill Scheduling in a Complex Underground Mine," Interfaces, INFORMS, vol. 44(2), pages 204-221, April.
    4. Renaud Chicoisne & Daniel Espinoza & Marcos Goycoolea & Eduardo Moreno & Enrique Rubio, 2012. "A New Algorithm for the Open-Pit Mine Production Scheduling Problem," Operations Research, INFORMS, vol. 60(3), pages 517-528, June.
    5. W. Matthew Carlyle & B. Curtis Eaves, 2001. "Underground Planning at Stillwater Mining Company," Interfaces, INFORMS, vol. 31(4), pages 50-60, August.
    6. Alexandra M. Newman & Enrique Rubio & Rodrigo Caro & Andrés Weintraub & Kelly Eurek, 2010. "A Review of Operations Research in Mine Planning," Interfaces, INFORMS, vol. 40(3), pages 222-245, June.
    7. Asad, Mohammad Waqar Ali & Dimitrakopoulos, Roussos, 2013. "A heuristic approach to stochastic cutoff grade optimization for open pit mining complexes with multiple processing streams," Resources Policy, Elsevier, vol. 38(4), pages 591-597.
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    Cited by:

    1. 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.
    2. Panos Markou & Daniel Corsten, 2021. "Financial and Operational Risk Management: Inventory Effects in the Gold Mining Industry," Production and Operations Management, Production and Operations Management Society, vol. 30(12), pages 4635-4655, December.

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