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Energy efficient scheduling of open-pit coal mine trucks

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  • Patterson, S.R.
  • Kozan, E.
  • Hyland, P.

Abstract

Mining companies are increasingly being challenged to improve energy efficiency, as a method of reducing both the cost and environmental impact of their operations. The haulage activity at an open-pit mine represents a large proportion of total energy consumption. In many other industries, state-of-the-art operations research techniques, such as advanced scheduling, have been applied to support energy efficiency improvements. Despite this, only a limited amount of research using these techniques has been conducted, to face the challenge of energy efficiency in mining. This research contributes an original mixed integer linear programming formulation that schedules haulage activity to minimise the truck and shovel energy consumption required to meet production targets. Since solving the model is found to be NP-hard and intractable for exact methods, a constructive algorithm and tabu search solution technique is developed to solve the model quickly enough for practical use. An operating mine in South East Queensland is used as a case study, to verify and validate the proposed model and solution technique using sensitivity and scenario analysis where significant potential for improvement is found. Several opportunities for using the model as a decision support tool are discussed, including examples of how it can be used for short, medium and long-term decision making.

Suggested Citation

  • Patterson, S.R. & Kozan, E. & Hyland, P., 2017. "Energy efficient scheduling of open-pit coal mine trucks," European Journal of Operational Research, Elsevier, vol. 262(2), pages 759-770.
  • Handle: RePEc:eee:ejores:v:262:y:2017:i:2:p:759-770
    DOI: 10.1016/j.ejor.2017.03.081
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    References listed on IDEAS

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    1. Gahm, Christian & Denz, Florian & Dirr, Martin & Tuma, Axel, 2016. "Energy-efficient scheduling in manufacturing companies: A review and research framework," European Journal of Operational Research, Elsevier, vol. 248(3), pages 744-757.
    2. Ta, Chung H. & Ingolfsson, Armann & Doucette, John, 2013. "A linear model for surface mining haul truck allocation incorporating shovel idle probabilities," European Journal of Operational Research, Elsevier, vol. 231(3), pages 770-778.
    3. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    4. S.R. Patterson & E. Kozan & P. Hyland, 2016. "An integrated model of an open-pit coal mine: improving energy efficiency decisions," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4213-4227, July.
    5. Vernon Topp & Leo Soames & Dean Parham & Harry Bloch, 2008. "Productivity in the Mining Industry: Measurement and Interpretation," Staff Working Papers 0807, Productivity Commission, Government of Australia.
    6. Chaowasakoo, Patarawan & Seppälä, Heikki & Koivo, Heikki & Zhou, Quan, 2017. "Improving fleet management in mines: The benefit of heterogeneous match factor," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1052-1065.
    7. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "Thirty years of heterogeneous vehicle routing," European Journal of Operational Research, Elsevier, vol. 249(1), pages 1-21.
    8. Yu, Shiwei & Zheng, Shuhong & Gao, Shiwei & Yang, Juan, 2017. "A multi-objective decision model for investment in energy savings and emission reductions in coal mining," European Journal of Operational Research, Elsevier, vol. 260(1), pages 335-347.
    9. Sahoo, Lalit Kumar & Bandyopadhyay, Santanu & Banerjee, Rangan, 2014. "Benchmarking energy consumption for dump trucks in mines," Applied Energy, Elsevier, vol. 113(C), pages 1382-1396.
    10. Dindarloo, Saeid R. & Siami-Irdemoosa, Elnaz, 2016. "Determinants of fuel consumption in mining trucks," Energy, Elsevier, vol. 112(C), pages 232-240.
    11. Souza, M.J.F. & Coelho, I.M. & Ribas, S. & Santos, H.G. & Merschmann, L.H.C., 2010. "A hybrid heuristic algorithm for the open-pit-mining operational planning problem," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1041-1051, December.
    12. Wang, Ning & Wen, Zongguo & Liu, Mingqi & Guo, Jie, 2016. "Constructing an energy efficiency benchmarking system for coal production," Applied Energy, Elsevier, vol. 169(C), pages 301-308.
    13. Bellamy, Drew & Pravica, Luka, 2011. "Assessing the impact of driverless haul trucks in Australian surface mining," Resources Policy, Elsevier, vol. 36(2), pages 149-158, June.
    14. Siami-Irdemoosa, Elnaz & Dindarloo, Saeid R., 2015. "Prediction of fuel consumption of mining dump trucks: A neural networks approach," Applied Energy, Elsevier, vol. 151(C), pages 77-84.
    15. Tang, Lixin & Zhao, Jiao & Liu, Jiyin, 2014. "Modeling and solution of the joint quay crane and truck scheduling problem," European Journal of Operational Research, Elsevier, vol. 236(3), pages 978-990.
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