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Production phase and ultimate pit limit design under commodity price uncertainty


  • Chatterjee, Snehamoy
  • Sethi, Manas Ranjan
  • Asad, Mohammad Waqar Ali


Open pit mine design optimization under uncertainty is one of the most critical and challenging tasks in the mine planning process. This paper describes the implementation of a minimum cut network flow algorithm for the optimal production phase and ultimate pit limit design under commodity price or market uncertainty. A new smoothing splines algorithm with sequential Gaussian simulation generates multiple commodity price scenarios, and a computationally efficient stochastic framework accommodates the joint representation and processing of the mining block economic values that result from these commodity price scenarios. A case study at an existing iron mining operation demonstrates the performance of the proposed method, and a comparison with conventional deterministic approach shows a higher cumulative metal production coupled with a 48% increase in the net present value (NPV) of the operation.

Suggested Citation

  • Chatterjee, Snehamoy & Sethi, Manas Ranjan & Asad, Mohammad Waqar Ali, 2016. "Production phase and ultimate pit limit design under commodity price uncertainty," European Journal of Operational Research, Elsevier, vol. 248(2), pages 658-667.
  • Handle: RePEc:eee:ejores:v:248:y:2016:i:2:p:658-667
    DOI: 10.1016/j.ejor.2015.07.012

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    References listed on IDEAS

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    Cited by:

    1. Dohnal, Mirko & Doubravsky, Karel, 2016. "Equationless and equation-based trend models of prohibitively complex technological and related forecasts," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 297-304.
    2. Dohnal, Mirko, 2016. "Complex biofuels related scenarios generated by qualitative reasoning under severe information shortages: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 676-684.
    3. Savolainen, Jyrki, 2016. "Real options in metal mining project valuation: Review of literature," Resources Policy, Elsevier, vol. 50(C), pages 49-65.
    4. Zhang, Jian & Dimitrakopoulos, Roussos G., 2017. "A dynamic-material-value-based decomposition method for optimizing a mineral value chain with uncertainty," European Journal of Operational Research, Elsevier, vol. 258(2), pages 617-625.


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