IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v80y2023ics0301420722007085.html
   My bibliography  Save this article

Determination of sublevel stoping layout using a network flow algorithm and the MRMR classification system

Author

Listed:
  • Esmaeili, Ahmadreza
  • Hamidi, Jafar Khademi
  • Mousavi, Amin

Abstract

Reduced access to shallow mineral resources, increased demand for minerals, and advances in technology have led to the development of deep underground mines. The location of the stopes and, finally, the determination of the mine layout is one of the problems in the design of any underground mine. In this study, a network flow algorithm was used to optimize the underground mine layout where sublevel stoping was chosen as the mining method. Due to the geomechanical constraints, the empirical Mining Rock Mass Rating classification system was used to determine the maximum stable width of the mineable stopes in the mine layout of each mining level. The model was run on a copper deposit and optimized for one mining level. The results obtained from running the model showed that 40 mineable stopes with a total recovery of 97% could be achieved. For validity check, the results were compared with those obtained from the algorithm of maximum value neighborhood. Application of the proposed model into the example block model revealed approximately 7% more economic value for the network flow algorithm than the maximum value neighborhood algorithm.

Suggested Citation

  • Esmaeili, Ahmadreza & Hamidi, Jafar Khademi & Mousavi, Amin, 2023. "Determination of sublevel stoping layout using a network flow algorithm and the MRMR classification system," Resources Policy, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722007085
    DOI: 10.1016/j.resourpol.2022.103265
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420722007085
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2022.103265?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    2. Mousavi, Amin & Sellers, Ewan, 2019. "Optimisation of production planning for an innovative hybrid underground mining method," Resources Policy, Elsevier, vol. 62(C), pages 184-192.
    3. Jean-Claude Picard, 1976. "Maximal Closure of a Graph and Applications to Combinatorial Problems," Management Science, INFORMS, vol. 22(11), pages 1268-1272, July.
    4. Foroughi, Sorayya & Hamidi, Jafar Khademi & Monjezi, Masoud & Nehring, Micah, 2019. "The integrated optimization of underground stope layout designing and production scheduling incorporating a non-dominated sorting genetic algorithm (NSGA-II)," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sotoudeh, Farzad & Nehring, Micah & Kizil, Mehmet & Knights, Peter & Mousavi, Amin, 2020. "Production scheduling optimisation for sublevel stoping mines using mathematical programming: A review of literature and future directions," Resources Policy, Elsevier, vol. 68(C).
    2. Rafael Epstein & Marcel Goic & Andrés Weintraub & Jaime Catalán & Pablo Santibáñez & Rodolfo Urrutia & Raúl Cancino & Sergio Gaete & Augusto Aguayo & Felipe Caro, 2012. "Optimizing Long-Term Production Plans in Underground and Open-Pit Copper Mines," Operations Research, INFORMS, vol. 60(1), pages 4-17, February.
    3. 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.
    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. Gary Kochenberger & Jin-Kao Hao & Fred Glover & Mark Lewis & Zhipeng Lü & Haibo Wang & Yang Wang, 2014. "The unconstrained binary quadratic programming problem: a survey," Journal of Combinatorial Optimization, Springer, vol. 28(1), pages 58-81, July.
    6. Csapó, Gergely & Müller, Rudolf, 2013. "Optimal mechanism design for the private supply of a public good," Games and Economic Behavior, Elsevier, vol. 80(C), pages 229-242.
    7. Domenico Moramarco & Umutcan Salman, 2023. "Equal opportunities in many-to-one matching markets," Working Papers 649, ECINEQ, Society for the Study of Economic Inequality.
    8. Dorit S. Hochbaum, 2003. "Efficient Algorithms for the Inverse Spanning-Tree Problem," Operations Research, INFORMS, vol. 51(5), pages 785-797, October.
    9. Nancel-Penard, Pierre & Morales, Nelson & Cornillier, Fabien, 2022. "A recursive time aggregation-disaggregation heuristic for the multidimensional and multiperiod precedence-constrained knapsack problem: An application to the open-pit mine block sequencing problem," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1088-1099.
    10. Jélvez, Enrique & Morales, Nelson & Nancel-Penard, Pierre & Peypouquet, Juan & Reyes, Patricio, 2016. "Aggregation heuristic for the open-pit block scheduling problem," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1169-1177.
    11. Pavlos Eirinakis & Dimitrios Magos & Ioannis Mourtos & Panayiotis Miliotis, 2012. "Finding All Stable Pairs and Solutions to the Many-to-Many Stable Matching Problem," INFORMS Journal on Computing, INFORMS, vol. 24(2), pages 245-259, May.
    12. M. Vanhoucke, 2006. "An efficient hybrid search algorithm for various optimization problems," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/365, Ghent University, Faculty of Economics and Business Administration.
    13. Bradley Sturt, 2021. "A nonparametric algorithm for optimal stopping based on robust optimization," Papers 2103.03300, arXiv.org, revised Mar 2023.
    14. 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).
    15. José R. Correa & Andreas S. Schulz, 2005. "Single-Machine Scheduling with Precedence Constraints," Mathematics of Operations Research, INFORMS, vol. 30(4), pages 1005-1021, November.
    16. Whittle, D. & Brazil, M. & Grossman, P.A. & Rubinstein, J.H. & Thomas, D.A., 2018. "Combined optimisation of an open-pit mine outline and the transition depth to underground mining," European Journal of Operational Research, Elsevier, vol. 268(2), pages 624-634.
    17. Gonczarowski, Yannai A. & Nisan, Noam & Ostrovsky, Rafail & Rosenbaum, Will, 2019. "A stable marriage requires communication," Games and Economic Behavior, Elsevier, vol. 118(C), pages 626-647.
    18. Madziwa, Lawrence & Pillalamarry, Mallikarjun & Chatterjee, Snehamoy, 2023. "Integrating stochastic mine planning model with ARDL commodity price forecasting," Resources Policy, Elsevier, vol. 85(PB).
    19. François Margot & Maurice Queyranne & Yaoguang Wang, 2003. "Decompositions, Network Flows, and a Precedence Constrained Single-Machine Scheduling Problem," Operations Research, INFORMS, vol. 51(6), pages 981-992, December.
    20. Dorit S. Hochbaum, 2008. "The Pseudoflow Algorithm: A New Algorithm for the Maximum-Flow Problem," Operations Research, INFORMS, vol. 56(4), pages 992-1009, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722007085. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.