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An uncertainty based multi-criteria ranking system for open pit mining cut-off grade strategy selection

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  • Azimi, Yousuf
  • Osanloo, Morteza
  • Esfahanipour, Akbar

Abstract

Cut-off grade strategy (COGS) is a concept that directly influences the financial, technical, economical, and environmental issues in relation to the exploitation of a mineral resource. Despite the simple definition of cut-off grade, the COGS problem is one of the complex and complicated problems in the mine planning process. From the optimization point of view, the COGS with an objective of maximizing the present value of future cash flows is a non-linear and a non-convex problem that even in its deterministic form can be solved using approximate optimization methods. This optimization problem will also be more complex and complicated under uncertainty conditions. This paper proposes an uncertainty based multi-criteria ranking system to investigate the problem of COGS selection considering metal price and geological uncertainties. The proposed system aims at selection of the best COGS among technically feasible alternative COGSs under uncertainty circumstances. Our developed system is based on integrating metal price and geological uncertainties as well as operating flexibility to close the mine early. We incorporate this operating flexibility into the proposed system using a Monte Carlo based real options (RO) valuation model. For this purpose, in addition to the expected value, other risk criteria are considered to rank the alternatives. These risk criteria include abilities of strategies in producing extra profits, minimizing losses, and achieving the predefined goals of the production. In this study, the technically possible COGSs are generated using the Lane comprehensive algorithm. To demonstrate the effectiveness of the proposed system, we utilize data of an Iranian gold mine. Results show that the proposed system outperforms conventional methods in the sense that it shows significantly lower average mis-ranking than the other methods and also selects a strategy with a higher value. The sensitivity analysis of the proposed system relative to the gold price shows that the system is highly dependent on the parameters of the stochastic process used to model the evolution of the metal price. Therefore, special consideration should be given in estimating stochastic process parameters.

Suggested Citation

  • Azimi, Yousuf & Osanloo, Morteza & Esfahanipour, Akbar, 2013. "An uncertainty based multi-criteria ranking system for open pit mining cut-off grade strategy selection," Resources Policy, Elsevier, vol. 38(2), pages 212-223.
    • Handle: RePEc:eee:jrpoli:v:38:y:2013:i:2:p:212-223
    DOI: 10.1016/j.resourpol.2013.01.004
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    3. Inthavongsa, Inthanongsone & Drebenstedt, Carsten & Bongaerts, Jan & Sontamino, Phongpat, 2016. "Real options decision framework: Strategic operating policies for open pit mine planning," Resources Policy, Elsevier, vol. 47(C), pages 142-153.
    4. Ahmadi, Mohammad Reza & Shahabi, Reza Shakoor, 2018. "Cutoff grade optimization in open pit mines using genetic algorithm," Resources Policy, Elsevier, vol. 55(C), pages 184-191.
    5. Khan, Asif & Asad, Mohammad Waqar Ali, 2019. "A method for optimal cut-off grade policy in open pit mining operations under uncertain supply," Resources Policy, Elsevier, vol. 60(C), pages 178-184.
    6. Mai, Ngoc Luan & Topal, Erkan & Erten, Oktay & Sommerville, Bruce, 2019. "A new risk-based optimisation method for the iron ore production scheduling using stochastic integer programming," Resources Policy, Elsevier, vol. 62(C), pages 571-579.
    7. Mohammadi, Sadjad & Kakaie, Reza & Ataei, Mohammad & Pourzamani, Eshagh, 2017. "Determination of the optimum cut-off grades and production scheduling in multi-product open pit mines using imperialist competitive algorithm (ICA)," Resources Policy, Elsevier, vol. 51(C), pages 39-48.
    8. Biswas, Pritam & Sinha, Rabindra Kumar & Sen, Phalguni, 2023. "A review of state-of-the-art techniques for the determination of the optimum cut-off grade of a metalliferous deposit with a bibliometric mapping in a surface mine planning context," Resources Policy, Elsevier, vol. 83(C).
    9. Kuangyuan Zhang & Richard Olawoyin & Antonio Nieto & Andrew N. Kleit, 2018. "Risk of commodity price, production cost and time to build in resource economics," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(6), pages 2521-2544, December.
    10. Aleksandr Rakhmangulov & Konstantin Burmistrov & Nikita Osintsev, 2022. "Selection of Open-Pit Mining and Technical System’s Sustainable Development Strategies Based on MCDM," Sustainability, MDPI, vol. 14(13), pages 1-31, June.
    11. Asad, Mohammad Waqar Ali & Qureshi, Muhammad Asim & Jang, Hyongdoo, 2016. "A review of cut-off grade policy models for open pit mining operations," Resources Policy, Elsevier, vol. 49(C), pages 142-152.
    12. Savolainen, Jyrki, 2016. "Real options in metal mining project valuation: Review of literature," Resources Policy, Elsevier, vol. 50(C), pages 49-65.
    13. Jyrki Savolainen & Ramin Rakhsha & Richard Durham, 2022. "Simulation-based decision-making system for optimal mine production plan selection," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 35(2), pages 267-281, June.
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    More about this item

    Keywords

    Open pit mining; Cut-off grade strategy (COGS); Least-Squares Monte Carlo real options valuation; Metal price uncertainty; Geological uncertainty; Multi-criteria ranking system;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • L72 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Other Nonrenewable Resources
    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development

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