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A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks Over Multiple Time Periods

Author

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  • Michelle L. Blom

    (Department of Computing and Information Systems, University of Melbourne, Parkville 3010, Victoria, Australia)

  • Adrian R. Pearce

    (Department of Computing and Information Systems, University of Melbourne, Parkville 3010, Victoria, Australia)

  • Peter J. Stuckey

    (Department of Computing and Information Systems, University of Melbourne, Parkville 3010, Victoria, Australia)

Abstract

We consider the multiple-time-period, short-term production scheduling problem for a network of multiple open-pit mines and ports. Ore produced at each mine, in each period, is transported by rail to a set of ports and blended into products for shipping. Each port forms these blends to a specification, as stipulated in contracts with downstream customers. This problem belongs to a class of multiple producer/consumer scheduling problems in which producers are able to generate a range of products, a combination of which are required by consumers to meet specified demands. In practice, short-term schedules are formed independently at each mine, tasked with achieving a grade and quality target outlined in a medium-term plan. Because of uncertainty in the data available to a medium-term planner and the dynamics of the mining environment, such targets may not be feasible in the short term. In this paper, we present an algorithm in which the grade and quality targets assigned to each mine are iteratively adapted, ensuring the satisfaction of blending constraints at each port while generating schedules for each mine that maximise resource utilisation. This paper was accepted by Yinyu Ye, optimization .

Suggested Citation

  • Michelle L. Blom & Adrian R. Pearce & Peter J. Stuckey, 2016. "A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks Over Multiple Time Periods," Management Science, INFORMS, vol. 62(10), pages 3059-3084, October.
  • Handle: RePEc:inm:ormnsc:v:62:y:2016:i:10:p:3059-3084
    DOI: 10.1287/mnsc.2015.2284
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    References listed on IDEAS

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    Cited by:

    1. Lu Chen & Qinghua Gu & Rui Wang & Zhidong Feng & Chao Zhang, 2022. "Comprehensive Utilization of Mineral Resources: Optimal Blending of Polymetallic Ore Using an Improved NSGA-III Algorithm," Sustainability, MDPI, vol. 14(17), pages 1-19, August.
    2. Zeng, Lanyan & Liu, Shi Qiang & Kozan, Erhan & Corry, Paul & Masoud, Mahmoud, 2021. "A comprehensive interdisciplinary review of mine supply chain management," Resources Policy, Elsevier, vol. 74(C).
    3. Yifu Chen & Christos T. Maravelias, 2020. "Preprocessing algorithm and tightening constraints for multiperiod blend scheduling: cost minimization," Journal of Global Optimization, Springer, vol. 77(3), pages 603-625, July.
    4. Haonan, Zhou & Samavati, Mehran & Hill, Andrew J., 2021. "Heuristics for integrated blending optimisation in a mining supply chain," Omega, Elsevier, vol. 102(C).
    5. Nelis, Gonzalo & Morales, Nelson & Jelvez, Enrique, 2023. "Optimal mining cut definition and short-term open pit production scheduling under geological uncertainty," Resources Policy, Elsevier, vol. 81(C).
    6. Yifu Chen & Christos T. Maravelias, 2022. "Variable Bound Tightening and Valid Constraints for Multiperiod Blending," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 2073-2090, July.
    7. 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.
    8. Zhang, Jian & Nault, Barrie R. & Dimitrakopoulos, Roussos G., 2019. "Optimizing a mineral value chain with market uncertainty using benders decomposition," European Journal of Operational Research, Elsevier, vol. 274(1), pages 227-239.

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