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Model of room and pillar production planning in small scale underground mines with metal price and operating cost uncertainty

Author

Listed:
  • Gligoric, Zoran
  • Gligoric, Milos
  • Dimitrijevic, Bojan
  • Grozdanovic, Ines
  • Milutinovic, Aleksandar
  • Ganic, Aleksandar
  • Gojkovic, Zoran

Abstract

Meeting investment and operating goals with presence of different sources of uncertainties and operational constraints is critical for a successful underground mining operation and even for a mining company to survive. Small and large mining businesses are all affected by business environment. Production planning that takes into account real strength of the mining company requires from the owner or management of the company to set up acceptable and achievable investment goals (targets). In this paper we propose the production planning model that minimizes deviation from Acceptable Rate Of Return (AROR). Besides the AROR, there are operating goals success that should be also realized with minimum deviation from target values. Accordingly, the production planning can be treated as a multi-objective problem. All these objectives are integrated in multi-variable weighted Frobenius distance function that measures the deviation from established targets. Ore body is represented as a set of mineable blocks and room and pillar mining method is selected as a way of mining. We apply a multi-objective iterated greedy algorithm to define a set of blocks that should be mined every year such that deviations from target values are less than or equal to given errors of minimization. Uncertainty of metal price and operating costs are treated by mean reversion process and Geometric Brownian motion respectively. Algorithm was tested on small hypothetical lead-zinc ore body.

Suggested Citation

  • Gligoric, Zoran & Gligoric, Milos & Dimitrijevic, Bojan & Grozdanovic, Ines & Milutinovic, Aleksandar & Ganic, Aleksandar & Gojkovic, Zoran, 2020. "Model of room and pillar production planning in small scale underground mines with metal price and operating cost uncertainty," Resources Policy, Elsevier, vol. 65(C).
  • Handle: RePEc:eee:jrpoli:v:65:y:2020:i:c:s0301420718302022
    DOI: 10.1016/j.resourpol.2018.07.011
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    References listed on IDEAS

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    1. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    2. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
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    Cited by:

    1. Guo, Jianxin & Tan, Xianchun & Zhu, Kaiwei & Cheng, Yonglong, 2024. "Integrated management of abatement technology investment and resource extraction," Resources Policy, Elsevier, vol. 92(C).
    2. Sotoudeh, Farzad & Nehring, Micah & Kizil, Mehmet & Knights, Peter & Mousavi, Amin, 2020. "Production scheduling optimisation for sublevel stoping mines using mathematical programming: A review of literature and future directions," Resources Policy, Elsevier, vol. 68(C).
    3. Yıldız, Taşkın Deniz, 2022. "Considering the recent increase in license fees in Turkey, how can the negative effect of the fees on the mining operating costs be reduced?," Resources Policy, Elsevier, vol. 77(C).
    4. Yıldız, Taşkın Deniz, 2022. "Supervisor fund expectation for the guarantee of salaries in the presence of the effect of permanent supervisor salaries on mining operating costs in Turkey," Resources Policy, Elsevier, vol. 77(C).
    5. Yıldız, Taşkın Deniz, 2023. "Changes in the salaries of mining engineers as they obtain managerial and OHS specialist positions in Turkey: By what criteria can salaries be increased?," Resources Policy, Elsevier, vol. 84(C).

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