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Short-term underground mine planning with uncertain activity durations using constraint programming

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Abstract

The short-term scheduling of activities in underground mines is an important step in mining operations. This procedure is a challenging optimization problem since it deals with many resources and activities conducted in a confined working space. Moreover, underground mining operations deal with multiple uncertainties such as the variation of activity durations. In this paper, a constraint programming (CP) model is proposed for short-term planning in underground mines. The developed model takes into account the technical requirements of underground operations to build realistic mine schedules. Furthermore, two different approaches are proposed based on the CP model for robust short-term underground mine scheduling. The first approach aims to create a robust schedule using multiple scenarios of the problem. This stochastic CP model enables to find a set of ordered robust sequences of activities performed by each available disjunctive resource over several scenarios. In the second approach, a confidence constraint is introduced in the CP model to specify the probability that the schedule generated would not underestimate the duration of activities. The model allows the mine planner to control the risk level with which an optimized solution should be produced such that it can be implemented given the actual activity durations. The presented approaches are tested on real data sets of an underground gold mine in Canada. An evaluation model is designed to evaluate the robust performance of the proposed models. The experiments demonstrate that both scenario-based and confidence-constraint approaches outperform the deterministic model by generating schedules that are more robust to uncertainties in underground operations.

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References

  • André, J., Gamache, M., & Pesant, G. (2022). Constraint programming models for robust short-term underground mining scheduling using complementary approaches: a stochastic approach and a simulation model. Cahier du GERAD G-2022-43.

  • Åstrand, M., Johansson, M., & Greberg, J. (2018a). Underground mine scheduling modelled as a flow shop: a review of relevant work and future challenges. Journal of the Southern African Institute of Mining and Metallurgy, 118(12), 1265–1276.

  • Åstrand, M., Johansson, M., & Zanarini, A. (2018b). Fleet scheduling in underground mines using constraint programming. In International conference on the integration of constraint programming, artificial intelligence, and operations research (pp. 605–613). Springer.

  • Åstrand, M., Johansson, M., & Zanarini, A. (2020). Underground mine scheduling of mobile machines using constraint programming and large neighborhood search. Computers & Operations Research, 123, 105036.

    Article  Google Scholar 

  • Campeau, L. P., & Gamache, M. (2020). Short-term planning optimization model for underground mines. Computers & Operations Research, 115, 104642.

    Article  Google Scholar 

  • Campeau, L. P., & Gamache, M. (2022). Short-and medium-term optimization of underground mine planning using constraint programming. Constraints, 1–18.

  • Campeau, L. P., Gamache, M., & Martinelli, R. (2022). Integrated optimisation of short-and medium-term planning in underground mines. International Journal of Mining, Reclamation and Environment, 36(4), 235–253.

    Article  Google Scholar 

  • Chakrabortty, R. K., Sarker, R. A., & Essam, D. L. (2017). Resource constrained project scheduling with uncertain activity durations. Computers & Industrial Engineering, 112, 537–550.

    Article  Google Scholar 

  • Chanda, E. (1990). An application of integer programming and simulation to production planning for a stratiform ore body. Mining Science and Technology, 11(2), 165–172.

    Article  Google Scholar 

  • Davari, M., & Demeulemeester, E. (2019). The proactive and reactive resource-constrained project scheduling problem. Journal of Scheduling, 22, 211–237.

    Article  Google Scholar 

  • Deblaere, F., Demeulemeester, E., & Herroelen, W. (2011). Reactive scheduling in the multi-mode RCPSP. Computers & Operations Research, 38(1), 63–74.

    Article  Google Scholar 

  • Goel, V., & Grossmann, I. E. (2004). A stochastic programming approach to planning of offshore gas field developments under uncertainty in reserves. Computers & Chemical Engineering, 28(8), 1409–1429.

    Article  Google Scholar 

  • Kanet, J. J., Ahire, S. L., & Gorman M. F. (2004). Constraint programming for scheduling.

  • Laborie, P. (2018). An update on the comparison of MIP, CP and hybrid approaches for mixed resource allocation and scheduling NCS of Lecture Notes in Computer Science (Vol. 10848, pp. 403–411). Springer.

    Google Scholar 

  • Laborie, P., Rogerie, J., Shaw, P., & Vilím, P. (2018). IBM ILOG CP optimizer for scheduling: 20+ years of scheduling with constraints at IBM/ILOG. Constraints, 23, 210–250.

    Article  Google Scholar 

  • Lamas, P., Goycoolea, M., Pagnoncelli, B., & Newman, A. (2024). A target-time-windows technique for project scheduling under uncertainty. European Journal of Operational Research, 314(2), 792–806.

    Article  Google Scholar 

  • Lambrechts, O., Demeulemeester, E., & Herroelen, W. (2008). Proactive and reactive strategies for resource-constrained project scheduling with uncertain resource availabilities. Journal of Scheduling, 11(2), 121–136.

    Article  Google Scholar 

  • Manríquez, F., Pérez, J., & Morales, N. (2020). A simulation-optimization framework for short-term underground mine production scheduling. Optimization and Engineering, 21(3), 939–971.

    Article  Google Scholar 

  • Mercier-Aubin, A., Dumetz, L., Gaudreault, J., & Quimper, C. G. (2020). The confidence constraint: A step towards stochastic CP solvers. In International conference on principles and practice of constraint programming (pp. 759–773). Springer.

  • Muge, F., & Pereira, H. . (1979). Short-term planning in sublevel stoping methods. In T. J. O’Neil (Ed.), 16th International symposium on the application of computers and or in the mineral industry (p. 323).

  • Nehring, M., Topal, E., & Knights, P. (2010). Dynamic short term production scheduling and machine allocation in underground mining using mathematical programming. Mining Technology, 119(4), 212–220.

    Article  Google Scholar 

  • O’Sullivan, D., & Newman, A. (2015). Optimization-based heuristics for underground mine scheduling. European Journal of Operational Research, 241(1), 248–259.

    Article  Google Scholar 

  • Paravarzar, S., Askari-Nasab, H., Pourrahimian, Y., & Emery, X. (2021a). Operational mine planning in block cave mining: A simulation-optimisation approach. International Journal of Mining, Reclamation and Environment, 35(3), 199–218.

  • Paravarzar, S., Askari-Nasab, H., Pourrahimian, Y., & Emery, X. (2021b). Simultaneous multi-sector block cave mine production scheduling considering operational uncertainties. Mining Technology, 130(1), 36–51.

  • Paravarzar, S., Pourrahimian, Y., Askari-Nasab, H., & Emery, X. (2021). Short-term underground mine planning: A review. International Journal of Mining and Mineral Engineering, 12(1), 1–33.

  • Pesant, G. (2014). A constraint programming primer. EURO Journal on Computational Optimization, 2(3), 89–97.

    Article  Google Scholar 

  • Rahal, S., Li, Z., & Papageorgiou, D. J. (2020). Proactive and reactive scheduling of the steelmaking and continuous casting process through adaptive robust optimization. Computers & Chemical Engineering, 133, 106658.

    Article  Google Scholar 

  • Schulze, M., Rieck, J., Seifi, C., & Zimmermann, J. (2016). Machine scheduling in underground mining: An application in the potash industry. OR Spectrum, 38(2), 365–403.

  • Schulze, M., & Zimmermann, J. (2017). Staff and machine shift scheduling in a German potash mine. Journal of Scheduling, 20(6), 635–656.

    Article  Google Scholar 

  • Seifi, C., Schulze, M., & Zimmermann, J. (2019). A two-stage solution approach for a shift scheduling problem with a simultaneous assignment of machines and workers. In The 39th international symposium on application of computers and operations research in the mineral industry (p. 377).

  • Sepulveda, J., Córdova, F., Quezada, L., Olivares, V., Hernandez, L., & Atero, L. (2005). A constraint-programming model for scheduling vehicles in underground mining operations. In 18th International conference on production research (ICPR), symposium proceedings.

  • Song, Z., Schunnesson, H., Rinne, M., & Sturgul, J. (2015). Intelligent scheduling for underground mobile mining equipment. PloS One, 10(6), e0131003.

    Article  Google Scholar 

  • Tan, C., & He, J. (2021). Integrated proactive and reactive strategies for sustainable berth allocation and quay crane assignment under uncertainty. Annals of Operations Research, 1–32.

  • Wang, W., Ge, X., Li, L., & Su, J. (2019). Proactive and reactive multi-project scheduling in uncertain environment. IEEE Access, 7, 88986–88997.

    Article  Google Scholar 

  • Wang, H., Tenorio, V., Li, G., Hou, J., & Hu, N. (2020). Optimization of trackless equipment scheduling in underground mines using genetic algorithms. Mining, Metallurgy & Exploration, 37(5), 1531–1544.

    Article  Google Scholar 

  • Yi, X., Goossens, D., & Nobibon, F. T. (2020). Proactive and reactive strategies for football league timetabling. European Journal of Operational Research, 282(2), 772–785.

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Correspondence to Younes Aalian.

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Aalian, Y., Gamache, M. & Pesant, G. Short-term underground mine planning with uncertain activity durations using constraint programming. J Sched (2024). https://doi.org/10.1007/s10951-024-00808-x

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