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A new algorithm to determine optimum cut-off grades considering technical, economical, environmental and social aspects

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  • Rahimi, Esmaeil
  • Ghasemzadeh, Hasan

Abstract

Optimum cut-off grades with different types of objective functions are determined by optimization algorithms which recognized as the one of the basis of sustainable development indicators of mining. As different mineral processing methods are applied in mines, it is very essential to choose the most appropriate cut-off grades determination algorithm. The current paper is going to analyze the bioheap leaching method and their associated environmental considerations on optimum cut-off grades policy. Remarking the importance of capital costs, these costs are evaluated in the model. Since the recovery of processing methods are changed based upon copper content, the recovery is considered variable in determining optimum cut-off grades. Presented model is evaluated in Sungun Copper Mine where the hydrometallurgical tests confirm the possibility of using bioheap leaching method to extract copper from its sulfide ores. It is observed that using bio-heap leaching method for low grade copper ores is subjected not only to improve the NPV of copper mines but also to decrease the adverse environmental impacts and produce sustainable results from mining activities.

Suggested Citation

  • Rahimi, Esmaeil & Ghasemzadeh, Hasan, 2015. "A new algorithm to determine optimum cut-off grades considering technical, economical, environmental and social aspects," Resources Policy, Elsevier, vol. 46(P1), pages 51-63.
  • Handle: RePEc:eee:jrpoli:v:46:y:2015:i:p1:p:51-63
    DOI: 10.1016/j.resourpol.2015.06.004
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    References listed on IDEAS

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    1. Ahmadi, Mohammad Reza & Bazzazi, Abbas Aghajani, 2019. "Cutoff grades optimization in open pit mines using meta-heuristic algorithms," Resources Policy, Elsevier, vol. 60(C), pages 72-82.
    2. 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.
    3. 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.
    4. 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).
    5. Khan, Asif & Asad, Mohammad Waqar Ali, 2021. "A mixed integer programming based cut-off grade model for open-pit mining of complex poly-metallic resources," Resources Policy, Elsevier, vol. 72(C).
    6. 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.
    7. Nikbin, V. & Ataee-pour, M. & Anani, A., 2020. "Optimization of level intervals in steeply-dipping vein deposits: A two-step approach," Resources Policy, Elsevier, vol. 69(C).
    8. 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.
    9. Rahimi, Esmaeil & Akbari, Afshin, 2016. "Application of KKT in determining the final destination of mined material in multi-processing mines," Resources Policy, Elsevier, vol. 50(C), pages 10-18.
    10. Mikhail Zarubin & Larissa Statsenko & Pavel Spiridonov & Venera Zarubina & Noune Melkoumian & Olga Salykova, 2021. "A GIS Software Module for Environmental Impact Assessment of the Open Pit Mining Projects for Small Mining Operators in Kazakhstan," Sustainability, MDPI, vol. 13(12), pages 1-25, June.

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