Optimisation in Underground Mining

  • Christopher Alford
  • Marcus Brazil
  • David H. Lee
Part of the International Series In Operations Research amp; Mana book series (ISOR, volume 99)

Efficient methods to model and optimise the design of open pit mines have been known for many years. Although the underground mine design problem is conceptually more difficult it has a similar potential for optimisation. Recent research demonstrates some useful progress in this topic. Here we provide an overview of some of this research.


Mixed Integer Programming Steiner Point Minimal Steiner Tree Machine Placement Stope Design 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. A. Akaike and K. Dagdelen, “A strategic production method for an open pit mine”, 28th APCOM Symposium, Golden, Colorado, 1999, 729-738.Google Scholar
  2. C. Alford “Optimization in underground mine design”, 25th APCOM AusIMM, 1995.Google Scholar
  3. C. Alford, Optimization in underground mine design. PhD, Department of Mathematics and Statistics, The University of Melbourne, 2006.Google Scholar
  4. M. Ataee-pour, A heuristic algorithm to optimize stope boundaries. PhD, Faculty of Engineering, University of Wollongong, 2000.Google Scholar
  5. R.W. Barbaro and R.V. Ramani, “Generalized multi-period MIP model for production scheduling and processing facilities selection”, Mining Engineering, 38 (1986), 107-114.Google Scholar
  6. A. Boucher, R. Dimitrakopoulos and J.A. Vargas-Guzman, “Joint simulations, optimal drillhole spacing and the role of the stockpile”, in Geostatistics Banff 2004 (Quantitative Geology and Geostatistics, 14), Springer, Berlin, 2005.Google Scholar
  7. M. Brazil, D. A. Thomas and J. F. Weng, “Gradient constrained minimal Steiner trees”, in Network Design: Connectivity and Facilities Location (DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Vol. 40), American Mathematical Society, Providence, 1998, pp. 23-38.Google Scholar
  8. M. Brazil, J. H. Rubinstein, D. A. Thomas, D. Lee, J. F. Weng and N. C. Wormald, “Network optimization of underground mine design”. The Australasian Institute for Mining and Metallurgy Proceedings, Vol. 305, No.1, pp. 57-65, 2000.Google Scholar
  9. M. Brazil, J. H. Rubinstein, D. A. Thomas, J. F.Weng and N. C. Wormald, “Gradient-constrained minimal Steiner trees (I). Fundamentals”, Journal of Global Optimization, 21, (2001), 139-155,.CrossRefGoogle Scholar
  10. M. Brazil, D.H. Lee, J.H. Rubinstein, D.A. Thomas, J.F. Weng, N.C. Wormald, “A network model to optimize cost in underground mine design”, Trans. South African Institute of Electrical Engineers, 93 (2002), 97-103.Google Scholar
  11. M. Brazil, D.H. Lee, M. Van Leuven, J.H. Rubinstein, D.A. Thomas, N.C. Wormald, “Optimizing declines in underground mines”, Mining Technology: Trans. of the Institution of Mining and Metallurgy, Section A, 112 (2003), 164-170.CrossRefGoogle Scholar
  12. M. Brazil, D.H. Lee, J.H. Rubinstein, D.A. Thomas, J.F. Weng, N.C. Wormald, “Optimization in the design of underground mine access”, Proceedings Orebody Modelling and Strategic Mine Planning, 2004, pp. 3-6.Google Scholar
  13. M. Brazil, D.A. Thomas, J.F. Weng, D.H. Lee, J.H. Rubinstein, “Cost optimization for underground mining networks”, Optimization and Engineering, 6 (2005), 241-256.CrossRefGoogle Scholar
  14. L. Caccetta and S. Hill, “An application of branch and cut to open pit mine scheduling”, Journal of Global Optimization, 27 (2003), 349-365,.CrossRefGoogle Scholar
  15. P.G. Carter, D.H. Lee and H. Baarsma, “Optimization methods for the selection of an underground mining method”, Proceedings Orebody Modelling and Strategic Mine Planning, 2004, pp. 7-12.Google Scholar
  16. N.M. Cheimanoff, E.P. Deliac and J.L. Mallet, “GEOCAD: An alternative CAD artificial intelligence tool that helps moving from geological resources to mineable reserves”, 21st APCOM, 1989.Google Scholar
  17. J. Deraisme, C. de Fouquent and H. Fraisse, “Geostatistical orebody model for computer optimization of profits from different underground mining methods”, 18th APCOM IMM, 1984.Google Scholar
  18. L.E. Dubins, “On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents”. American Journal of Mathematics, 79 (3) (1957), 497-516.CrossRefGoogle Scholar
  19. G. Froyland, M. Menabde, P. Stone, and D. Hodson, “The value of additional drilling to open pit mining projects”, Proceedings Orebody Modelling and Strategic Mine Planning, 2004, pp. 169-176.Google Scholar
  20. M.E. Gershon, “Mine scheduling optimization with mixed integer programming”, Society of Mining Engineers of AIME, Preprint No 82-324, 1982.Google Scholar
  21. M. Gershon and F.H. Murphy “Using dynamic programming for aggregating cuts in a single drillhole”, International Journal of Surface Mining, 1 (1987), 35-40.Google Scholar
  22. M. Gershon and F.H. Murphy “Optimizing single hole mine cuts by dynamic programming”, European Journal of Operational Research, 38 (1989), 56-62.CrossRefGoogle Scholar
  23. P. Goovaerts, Geostatistics for Natural Resources Evaluation. New York, Oxford University Press, 1997.Google Scholar
  24. N. Grieco and R. Dimitrakopoulos, “Grade uncertainty in stope design: Improving the optimization process”, Proceedings Orebody Modelling and Strategic Mine Planning, 2004, pp. 249-255.Google Scholar
  25. B. Hall and C. Stewart, “Optimising the strategic mine plan - methodologies, findings, successes and failures”, Proceedings Orebody Modelling and Strategic Mine Planning, 2004, pp. 49-58.Google Scholar
  26. F. K. Hwang, D. S. Richards, and P. Winter, The Steiner Tree Problem (Annals of Discrete Mathematics 53). Elsevier, Amsterdam, 1992.Google Scholar
  27. M. Kuchta, A. Newman and E. Topal, “Production scheduling at LKAB's Kiruna Mine using mixed integer programming”, Mining Engineering 55 (2003), 35-40.Google Scholar
  28. K.F. Lane, The Economic Definition of Ore. London, Mining Journal Books Limited, 1988.Google Scholar
  29. H. Lerchs, and I. F. Grossmann, “Optimum design of open-pit mines,” Trans. Canadian Institute of Mining and Metallurgy, Vol. LXVIII (1965) 17-24.Google Scholar
  30. Mineral Industries Computing Limited, Datamine Studio V2 User Documentation, 2005.Google Scholar
  31. F. Muge, P. Pina and J.L. Vieira, “Some applications of image analysis techniques to mine planning”, 24th APCOM IMM, 1995.Google Scholar
  32. A. Newman and M. Kuchta, “Eliminating variables and using aggregation to improve the performance of an integer programming production scheduling model for an underground mine”, preprint, 2003.Google Scholar
  33. J. Poniewierski, G. MacSporran and I. Sheppard, “Optimization of cut-off grade at Mount Isa Mines Limited's Enterprise Mine”, Conference Proceedings - Twelfth International Symposium on Mine Planning and Equipment Selection (MPES), 2003, pp. 531-538.Google Scholar
  34. J-M. Rendu, “Computerized estimation of ore and waste zones in complex mineral deposits”, Society of Mining Engineers of AIME, Preprint No 82-95, 1982.Google Scholar
  35. J-M. Rendu, “Orebody Modelling, mine planning, reserve evaluation and the regulatory environment”, Proceedings Orebody Modelling and Strategic Mine Planning, 2004, pp. 201-208.Google Scholar
  36. J. Serra, Image Analysis and Mathematical Morphology. New York, Academic Press, 1982.Google Scholar
  37. M.L. Smith, I. Sheppard and G. Karunatillake “Using MIP for strategic life-of-mine planning of the lead/zinc stream at Mount Isa Mines”, APCOM 2003 Conference, 2003, pp. 1-10.Google Scholar
  38. G. Thomas and A. Earl, “The application of second-generation stope optimization tools in underground cut-off grade analysis”, Whittle Strategic Mine Planning Conference, 1999.Google Scholar
  39. P. Trout, “Underground mine production scheduling using mixed integer programming”, APCOM XXV 1995 Conference, 1995, pp. 395-400.Google Scholar
  40. G. Whittle, “Global asset optimization”, Proceedings Orebody Modelling and Strategic Mine Planning, 2004, pp. 261-266.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Christopher Alford
    • 1
  • Marcus Brazil
    • 2
  • David H. Lee
    • 3
  1. 1.WH Bryan Mining Geology Research Centre, Sustainable Minerals InstituteThe University of QueenslandAustralia
  2. 2.Department of Electrical and Electronic EngineeringThe University of MelbourneAustralia
  3. 3.Department of Mathematics and StatisticsThe University of MelbourneAustralia

Personalised recommendations