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Optimizing mining complexes with multiple processing and transportation alternatives: An uncertainty-based approach

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  • Montiel, Luis
  • Dimitrakopoulos, Roussos

Abstract

Mining complexes contain multiple sequential activities that are strongly interrelated. Extracting the material from different sources may be seen as the first main activity, and any change in the sequence of extraction of the mining blocks modify the activities downstream, including blending, processing and transporting the processed material to final stocks or ports. Similarly, modifying the conditions of operation at a given processing path or the transportation systems implemented may affect the suitability of using a mining sequence previously optimized. This paper presents a method to generate mining, processing and transportation schedules that account for the previously mentioned activities (or stages) associated with the mining complex simultaneously. The method uses an initial solution generated using conventional optimizers and improves it by mean of perturbations associated to three different levels of decision: block based perturbations, operating alternative based perturbations and transportation system based perturbation. The method accounts for geological uncertainty of several deposits by considering scenarios originated from combinations of their respective stochastic orebody simulations. The implementation of the method in a multipit copper operation shows its ability to reduce deviations from capacity and blending targets while improving the expected NPV (cumulative discounted cash flows), which highlight the importance of stochastic optimizers given their ability to generate more value with less risk.

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  • Montiel, Luis & Dimitrakopoulos, Roussos, 2015. "Optimizing mining complexes with multiple processing and transportation alternatives: An uncertainty-based approach," European Journal of Operational Research, Elsevier, vol. 247(1), pages 166-178.
    • Handle: RePEc:eee:ejores:v:247:y:2015:i:1:p:166-178
    DOI: 10.1016/j.ejor.2015.05.002
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    1. Ulrich Faigle & Walter Kern, 1994. "Computational Complexity of Some Maximum Average Weight Problems with Precedence Constraints," Operations Research, INFORMS, vol. 42(4), pages 688-693, August.
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    Cited by:

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