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An integrated approach to open-pit mines production scheduling

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  • Alipour, Aref
  • Khodaiari, Ali Asghar
  • Jafari, Ahmad
  • Tavakkoli-Moghaddam, Reza

Abstract

In an Open-Pit Production Scheduling (OPPS) problem, the aim is to determine the mining sequence of an orebody as a block model. In common research methods for scheduling, commodity price and consequently block economic value are considered as fixed values. Due to commodity price time series fluctuations throughout the time, it is necessary to consider the variation of commodity price in each period of the OPPS problem. This paper introduces a new approach for the integration of forecasted copper prices based on stochastic differential equations (SDE) with the conventional integer programming OPPS problem. If the block values are different in each period, the block value is referred to as dynamic, else it is considered static. Since OPPS is known to be an NP-Hard problem and block values vary according to the scheduling period, an efficient Genetic Algorithm (GA) is presented to find feasible solutions. Our proposed algorithm is implemented on Marvin copper orebody. Comparison of the design by the conventional static and the SDE simulation-based dynamic block value methods illustrates that compared to the static design; the total value of the dynamic design is 43% higher than that of static design.

Suggested Citation

  • Alipour, Aref & Khodaiari, Ali Asghar & Jafari, Ahmad & Tavakkoli-Moghaddam, Reza, 2022. "An integrated approach to open-pit mines production scheduling," Resources Policy, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:jrpoli:v:75:y:2022:i:c:s0301420721004670
    DOI: 10.1016/j.resourpol.2021.102459
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    References listed on IDEAS

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    1. Samavati, Mehran & Essam, Daryl & Nehring, Micah & Sarker, Ruhul, 2017. "A local branching heuristic for the open pit mine production scheduling problem," European Journal of Operational Research, Elsevier, vol. 257(1), pages 261-271.
    2. Jélvez, Enrique & Morales, Nelson & Nancel-Penard, Pierre & Cornillier, Fabien, 2020. "A new hybrid heuristic algorithm for the Precedence Constrained Production Scheduling Problem: A mining application," Omega, Elsevier, vol. 94(C).
    3. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    4. Gilani, Seyyed-Omid & Sattarvand, Javad & Hajihassani, Mohsen & Abdullah, Shahrum Shah, 2020. "A stochastic particle swarm based model for long term production planning of open pit mines considering the geological uncertainty," Resources Policy, Elsevier, vol. 68(C).
    5. Samavati, Mehran & Essam, Daryl & Nehring, Micah & Sarker, Ruhul, 2018. "A new methodology for the open-pit mine production scheduling problem," Omega, Elsevier, vol. 81(C), pages 169-182.
    6. Samavati, Mehran & Essam, Daryl & Nehring, Micah & Sarker, Ruhul, 2017. "A methodology for the large-scale multi-period precedence-constrained knapsack problem: an application in the mining industry," International Journal of Production Economics, Elsevier, vol. 193(C), pages 12-20.
    7. Dimitrakopoulos, Roussos G. & Abdel Sabour, Sabry A., 2007. "Evaluating mine plans under uncertainty: Can the real options make a difference?," Resources Policy, Elsevier, vol. 32(3), pages 116-125, September.
    8. Paithankar, Amol & Chatterjee, Snehamoy & Goodfellow, Ryan & Asad, Mohammad Waqar Ali, 2020. "Simultaneous stochastic optimization of production sequence and dynamic cut-off grades in an open pit mining operation," Resources Policy, Elsevier, vol. 66(C).
    9. 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.
    10. Shishvan, Masoud Soleymani & Sattarvand, Javad, 2015. "Long term production planning of open pit mines by ant colony optimization," European Journal of Operational Research, Elsevier, vol. 240(3), pages 825-836.
    11. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    12. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    13. 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.
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    1. Hazrathosseini, Arman & Moradi Afrapoli, Ali, 2023. "The advent of digital twins in surface mining: Its time has finally arrived," Resources Policy, Elsevier, vol. 80(C).

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