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A simulated annealing based approach for open pit mine production scheduling with stockpiling option

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  • Danish, Abid Ali Khan
  • Khan, Asif
  • Muhammad, Khan
  • Ahmad, Waqas
  • Salman, Saad

Abstract

Production scheduling plays a pivotal role in successfully executing any open-pit mining operation. It defines the most profitable extraction sequence of mineralized material from the ground subject to various physical and operational constraints. Different mathematical formulations have been proposed to achieve this goal; however, solving these models for real-sized deposits with multiple constraints is a challenging and computationally expensive task. Moreover, the inclusion of stockpiling option further complicates this task. The stockpile option adds flexibility to the operation by allowing excess low-grade ore storage for processing at a later stage when processing capacity is available. Accurate integration of stockpiling option in the production scheduling process through mathematical approaches leads to nonlinear constraints. This could further complicate the already challenging task since linear approximation of these nonlinear constraints could lead to sub-optimal results. Metaheuristic techniques could play an essential role in handling such situations. Though several attempts have been made to solve this problem through these techniques, little effort has been made to incorporate stockpiling option in the optimization process. This article presents a Simulated Annealing based approach for production scheduling of open-pit mines with stockpiling option. The proposed approach uses a stockpile and a greedy heuristic with a Simulated Annealing algorithm to achieve this goal. The greedy heuristic improves the Simulated Annealing algorithm's computational efficiency by managing its randomness. The proposed approach's performance and efficiency are demonstrated through three case studies (A, B, and C) under different algorithmic settings. Results of these case studies reveals that compared with the CPLEX solver, the proposed approach produced near optimal solution, within reasonable amount of time, proving the applicability of the proposed approach.

Suggested Citation

  • Danish, Abid Ali Khan & Khan, Asif & Muhammad, Khan & Ahmad, Waqas & Salman, Saad, 2021. "A simulated annealing based approach for open pit mine production scheduling with stockpiling option," Resources Policy, Elsevier, vol. 71(C).
    • Handle: RePEc:eee:jrpoli:v:71:y:2021:i:c:s0301420721000337
    DOI: 10.1016/j.resourpol.2021.102016
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    References listed on IDEAS

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    1. W. Lambert & A. Newman, 2014. "Tailored Lagrangian Relaxation for the open pit block sequencing problem," Annals of Operations Research, Springer, vol. 222(1), pages 419-438, November.
    2. Daniel Espinoza & Marcos Goycoolea & Eduardo Moreno & Alexandra Newman, 2013. "MineLib: a library of open pit mining problems," Annals of Operations Research, Springer, vol. 206(1), pages 93-114, July.
    3. Renaud Chicoisne & Daniel Espinoza & Marcos Goycoolea & Eduardo Moreno & Enrique Rubio, 2012. "A New Algorithm for the Open-Pit Mine Production Scheduling Problem," Operations Research, INFORMS, vol. 60(3), pages 517-528, June.
    4. M Kumral & P A Dowd, 2005. "A simulated annealing approach to mine production scheduling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 922-930, August.
    5. Lamghari, Amina & Dimitrakopoulos, Roussos, 2012. "A diversified Tabu search approach for the open-pit mine production scheduling problem with metal uncertainty," European Journal of Operational Research, Elsevier, vol. 222(3), pages 642-652.
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    Cited by:

    1. Lu Chen & Qinghua Gu & Rui Wang & Zhidong Feng & Chao Zhang, 2022. "Comprehensive Utilization of Mineral Resources: Optimal Blending of Polymetallic Ore Using an Improved NSGA-III Algorithm," Sustainability, MDPI, vol. 14(17), pages 1-19, August.
    2. Noriega, Roberto & Pourrahimian, Yashar, 2022. "A systematic review of artificial intelligence and data-driven approaches in strategic open-pit mine planning," Resources Policy, Elsevier, vol. 77(C).
    3. 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).

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