Industrial Engineering and Management Systems

Korean Institute of Industrial Engineers (대한산업공학회)
권호 표지
DOI QR코드

DOI QR Code

An Interactive Planning and Scheduling Framework for Optimising Pits-to-Crushers Operations

  • Liu, Shi Qiang (School of Mathematical Sciences, Queensland University of Technology) ;
  • Kozan, Erhan (School of Mathematical Sciences, Queensland University of Technology)
  • Received : 2011.11.09
  • Accepted : 2012.02.11
  • Published : 2012.03.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, an interactive planning and scheduling framework are proposed for optimising operations from pits to crushers in ore mining industry. Series of theoretical and practical operations research techniques are investigated to improve the overall efficiency of mining systems due to the facts that mining managers need to tackle optimisation problems within different horizons and with different levels of detail. Under this framework, mine design planning, mine production sequencing and mine transportation scheduling models are integrated and interacted within a whole optimisation system. The proposed integrated framework could be used by mining industry for reducing equipment costs, improving the production efficiency and maximising the net present value.

Keywords

References

  1. Baker, K. R. (1974), Introduction to sequencing and scheduling: John Wiley and Sons, Inc.
  2. Bley, A., Boland, N., Fricke, C., and Froyland, G. (2010), A strengthened formulation and cutting planes for the open pit mine production scheduling problem, Computers and Operations Research, 37, 1641-1647. https://doi.org/10.1016/j.cor.2009.12.008
  3. Boland, N., Dumitrescu, I., Froyland, G., and Gleixner, A. M. (2009), LP-based disaggregation approaches to solving the open pit mining production scheduling problem with block processing selectivity, Computers and Operations Research, 36, 1064-1089. https://doi.org/10.1016/j.cor.2007.12.006
  4. Caccetta, L. and Giannini, L. M. (1988), An application of discrete mathematics in the design of an open pit mine, Discrete Applied Mathematics, 21, 1-19. https://doi.org/10.1016/0166-218X(88)90030-3
  5. Caccetta, L. and Hill, S. P. (2003), An application of branch and cut to open pit mine scheduling, Journal of Global Optimisation, 27, 349-365. https://doi.org/10.1023/A:1024835022186
  6. Caccetta, L., Giannini, L. M., and Kelsey, P. (1994), On the implementation of exact optimisation techniques for open pit design, Asia-Pacific Journal of Operational Research, 11, 155-170.
  7. Chicoisne, R., Espinoza, D., Goycoolea, M., Moreno, E., and Rubio, E. (2009), A new algorithm for the open-pit mine scheduling problem: Working paper, University Blaise Pascal, Clermont-Ferrand, France.
  8. Choi, Y., Park, H., Sunwoo, C., and Clarke, K. C. (2009), Multi-criteria evaluation and least-cost path analysis for optimal haulage routing of dump trucks in large scale open-pit mines, International Journal of Geographical Information Science, 23(12), 1541-1567. https://doi.org/10.1080/13658810802385245
  9. Cullenbine, C., Wood, R. K., and Newman, A. (2011), A sliding time window heuristic for open pit mine block sequencing, Optimisation Letters, doi: 10.1007/s11590-011-0306-2.
  10. Hochbaum, D. S. and Chen, A. (2000), Performance analysis and best implementations of old and new algorithms for the open-pit mining problem, Operations Research, 48(6), 894-914. https://doi.org/10.1287/opre.48.6.894.12392
  11. Kozan, E. and Liu S. Q. (2011), Operations Research for Mining: A Classification and Literature Review, ASOR Bulletin, 30(1), 2-23.
  12. Kumral, M. and Dowd, P. A. (2005), A simulated annealing approach to mine production scheduling, Journal of the Operational Research Society, 56, 922-930. https://doi.org/10.1057/palgrave.jors.2601902
  13. Lerchs, H. and Grossmann, I. F. (1965), Optimum design of open-pit mines, Transactions on CIM, LX VIII, 17-24.
  14. Myburgh, C. and Deb, K. (2010), Evolutionary algorithms in large-scale open pit mine scheduling, GECCO'10, Portland, Oregon, USA.
  15. Ramazan, S. (2007), The new fundamental tree algorithm for production scheduling of open pit mines, European Journal of Operational Research, 177, 1153-1166. https://doi.org/10.1016/j.ejor.2005.12.035
  16. Souza, M. J. F., Coelho, I. M., Ribas, S., Santos, H. G., and Merschmann, L. H. C. (2010), A hybrid heuristic algorithm for the open-pit-mining operational planning problem, European Journal of Operational Research, 207, 1041-1051. https://doi.org/10.1016/j.ejor.2010.05.031
  17. Sundar, D. K. and Acharya, D. (1995), Blast schedule planning and shift wise production scheduling of an opencast iron ore mine, Computers and Industrial Engineering, 28(4), 927-935. https://doi.org/10.1016/0360-8352(94)00221-8
  18. Tolwinski, B. and Underwood, R. (1996), A scheduling algorithm for open pit mines, IMA Journal of Mathematics Applied in Business and Industry, 7, 247-270.
  19. Topal, E. and Ramazan, S. (2010), A new MIP model for mine equipment scheduling by minimizing maintenance cost, European Journal of Operational Research, doi: 10.1016/j.ejor.2010.05.037.
  20. Underwood, R. and Tolwinski, B. (1998), A mathematical programming viewpoint for solving the ultimate pit problem, European Journal of Operational Research, 107(1), 96-107. https://doi.org/10.1016/S0377-2217(97)00141-0

Cited by

  1. A new open-pit multi-stage mine production timetabling model for drilling, blasting and excavating operations vol.125, pp.1, 2016, https://doi.org/10.1179/1743286315Y.0000000031
  2. Evaluating crusher system location in an open pit mine using Markov chains vol.31, pp.1, 2017, https://doi.org/10.1080/17480930.2015.1105649
  3. Job shop scheduling with a combination of four buffering constraints pp.1366-588X, 2017, https://doi.org/10.1080/00207543.2017.1401240
  4. Integration of mathematical models for ore mining industry pp.2330-2682, 2017, https://doi.org/10.1080/23302674.2017.1344330
  5. Open-pit block sequencing optimization: A mathematical model and solution technique vol.48, pp.11, 2012, https://doi.org/10.1080/0305215x.2016.1142080
  6. A review of factors affecting mining operation vol.17, pp.3, 2012, https://doi.org/10.1108/wje-03-2019-0082