IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v44y2014i2p195-203.html
   My bibliography  Save this article

Improving Underground Mine Access Layouts Using Software Tools

Author

Listed:
  • Marcus Brazil

    (Department of Electrical and Electronic Engineering, The University of Melbourne, Victoria, Australia)

  • Peter Grossman

    (Department of Mechanical Engineering, The University of Melbourne, Victoria, Australia)

  • J. Hyam Rubinstein

    (Department of Mathematics and Statistics, The University of Melbourne, Victoria, Australia)

  • Doreen Thomas

    (Department of Mechanical Engineering, The University of Melbourne, Victoria, Australia)

Abstract

The authors have developed two software tools, PUNO and DOT, for optimally designing the layout of the system of tunnels in an underground mine, known as the access network for the mine. We recently applied these tools, which use principles from geometric optimization, to ore deposits at the Prominent Hill mine in South Australia and the Leeville gold mine in Nevada. When we compared the designs that the tools generated with the designs prepared by mining engineers, we found that our tools generated designs more quickly, were at least as cost efficient, and often revealed new design options by which the engineers’ original designs could be improved.

Suggested Citation

  • Marcus Brazil & Peter Grossman & J. Hyam Rubinstein & Doreen Thomas, 2014. "Improving Underground Mine Access Layouts Using Software Tools," Interfaces, INFORMS, vol. 44(2), pages 195-203, April.
    • Handle: RePEc:inm:orinte:v:44:y:2014:i:2:p:195-203
    DOI: 10.1287/inte.2013.0691
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2013.0691
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.2013.0691?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
    ---><---

    References listed on IDEAS

    as
    1. Christopher Alford & Marcus Brazil & David H. Lee, 2007. "Optimisation in Underground Mining," International Series in Operations Research & Management Science, in: Andres Weintraub & Carlos Romero & Trond Bjørndal & Rafael Epstein & Jaime Miranda (ed.), Handbook Of Operations Research In Natural Resources, chapter 0, pages 561-577, Springer.
    2. Alexandra M. Newman & Enrique Rubio & Rodrigo Caro & Andrés Weintraub & Kelly Eurek, 2010. "A Review of Operations Research in Mine Planning," Interfaces, INFORMS, vol. 40(3), pages 222-245, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Akshay Chowdu & Peter Nesbitt & Andrea Brickey & Alexandra M. Newman, 2022. "Operations Research in Underground Mine Planning: A Review," Interfaces, INFORMS, vol. 52(2), pages 109-132, March.

    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. 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.
    2. Gonzalo Muñoz & Daniel Espinoza & Marcos Goycoolea & Eduardo Moreno & Maurice Queyranne & Orlando Rivera Letelier, 2018. "A study of the Bienstock–Zuckerberg algorithm: applications in mining and resource constrained project scheduling," Computational Optimization and Applications, Springer, vol. 69(2), pages 501-534, March.
    3. Bisera Andrić Gušavac & Selman Karagoz & Milena Popović & Dragan Pamućar & Muhammet Deveci, 2023. "Reconcilement of conflicting goals: a novel operations research-based methodology for environmental management," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 7423-7460, August.
    4. Akshay Chowdu & Peter Nesbitt & Andrea Brickey & Alexandra M. Newman, 2022. "Operations Research in Underground Mine Planning: A Review," Interfaces, INFORMS, vol. 52(2), pages 109-132, March.
    5. Barry King & Alexandra Newman, 2018. "Optimizing the Cutoff Grade for an Operational Underground Mine," Interfaces, INFORMS, vol. 48(4), pages 357-371, August.
    6. Amina Lamghari & Roussos Dimitrakopoulos & Jacques Ferland, 2015. "A hybrid method based on linear programming and variable neighborhood descent for scheduling production in open-pit mines," Journal of Global Optimization, Springer, vol. 63(3), pages 555-582, November.
    7. K. Sirinanda & M. Brazil & P. Grossman & J. Rubinstein & D. Thomas, 2016. "Gradient-constrained discounted Steiner trees II: optimally locating a discounted Steiner point," Journal of Global Optimization, Springer, vol. 64(3), pages 515-532, March.
    8. 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.
    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. Nakousi, C. & Pascual, R. & Anani, A. & Kristjanpoller, F. & Lillo, P., 2018. "An asset-management oriented methodology for mine haul-fleet usage scheduling," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 336-344.
    11. Pérez, Juan & Maldonado, Sebastián & González-Ramírez, Rosa, 2018. "Decision support for fleet allocation and contract renegotiation in contracted open-pit mine blasting operations," International Journal of Production Economics, Elsevier, vol. 204(C), pages 59-69.
    12. 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).
    13. 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.
    14. Jyrki Savolainen & Ramin Rakhsha & Richard Durham, 2022. "Simulation-based decision-making system for optimal mine production plan selection," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 35(2), pages 267-281, June.
    15. Mikael Collan & Jyrki Savolainen & Pasi Luukka, 2017. "Investigating the effect of price process selection on the value of a metal mining asset portfolio," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 30(2), pages 107-115, July.
    16. Lorenzo Reus & Mathias Belbèze & Hans Feddersen & Enrique Rubio, 2018. "Extraction Planning Under Capacity Uncertainty at the Chuquicamata Underground Mine," Interfaces, INFORMS, vol. 48(6), pages 543-555, November.
    17. Omotehinse, Adeyinka O. & De Tomi, Giorgio, 2020. "Managing the challenges of obtaining a social license to operate in the pre-mining phase: A focus on the oil sands communities in Ondo State, Nigeria," World Development Perspectives, Elsevier, vol. 18(C).
    18. Lamghari, Amina & Dimitrakopoulos, Roussos, 2016. "Progressive hedging applied as a metaheuristic to schedule production in open-pit mines accounting for reserve uncertainty," European Journal of Operational Research, Elsevier, vol. 253(3), pages 843-855.
    19. Cinna Seifi & Marco Schulze & Jürgen Zimmermann, 2021. "Solution procedures for block selection and sequencing in flat-bedded potash underground mines," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(2), pages 409-440, June.
    20. K. Sirinanda & M. Brazil & P. Grossman & J. Rubinstein & D. Thomas, 2016. "Gradient-constrained discounted Steiner trees I: optimal tree configurations," Journal of Global Optimization, Springer, vol. 64(3), pages 497-513, March.

    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:inm:orinte:v:44:y:2014:i:2:p:195-203. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.