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A column generation-based heuristic for rostering with work patterns

Author

Listed:
  • R Lusby

    (Technical University of Denmark, Lyngby, Denmark)

  • A Dohn

    (Technical University of Denmark, Lyngby, Denmark)

  • T M Range

    (University of Southern Denmark, Odense M, Denmark)

  • J Larsen

    (Technical University of Denmark, Lyngby, Denmark)

Abstract

This paper addresses the Ground Crew Rostering Problem with Work Patterns, an important manpower planning problem arising in the ground operations of airline companies. We present a cutting stock-based integer programming formulation of the problem and describe a powerful heuristic decomposition approach, which utilizes column generation and variable fixing, to construct efficient rosters for a six-month time horizon. The time horizon is divided into smaller blocks, where overlaps between the blocks ensure continuity. The proposed methodology is able to circumvent one step of the conventional roster construction process by generating rosters directly based on the estimated workload. We demonstrate that this approach has the additional advantage of being able to easily incorporate robustness in the roster. Computational results on real-life instances confirm the efficiency of the approach.

Suggested Citation

  • R Lusby & A Dohn & T M Range & J Larsen, 2012. "A column generation-based heuristic for rostering with work patterns," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(2), pages 261-277, February.
    • Handle: RePEc:pal:jorsoc:v:63:y:2012:i:2:p:261-277
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    Citations

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    Cited by:

    1. Range, Troels Martin & Kozlowski, Dawid & Petersen, Niels Chr., 2016. "Dynamic job assignment: A column generation approach with an application to surgery allocation," Discussion Papers on Economics 4/2016, University of Southern Denmark, Department of Economics.
    2. Szymula, Christopher & Bešinović, Nikola, 2020. "Passenger-centered vulnerability assessment of railway networks," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 30-61.
    3. Feng, Tao & Lusby, Richard M. & Zhang, Yongxiang & Tao, Siyu & Zhang, Bojian & Peng, Qiyuan, 2024. "A branch-and-price algorithm for integrating urban rail crew scheduling and rostering problems," Transportation Research Part B: Methodological, Elsevier, vol. 183(C).
    4. Range, Troels Martin & Lusby, Richard Martin & Larsen, Jesper, 2013. "A column generation approach for solving the patient admission scheduling problem," Discussion Papers on Economics 1/2013, University of Southern Denmark, Department of Economics.
    5. Toni I. Wickert & Pieter Smet & Greet Vanden Berghe, 2021. "Quantifying and enforcing robustness in staff rostering," Journal of Scheduling, Springer, vol. 24(3), pages 347-366, June.
    6. Range, Troels Martin & Kozlowski, Dawid & Petersen, Niels Chr., 2019. "Dynamic job assignment: A column generation approach with an application to surgery allocation," European Journal of Operational Research, Elsevier, vol. 272(1), pages 78-93.
    7. Range, Troels Martin & Lusby, Richard Martin & Larsen, Jesper, 2014. "A column generation approach for solving the patient admission scheduling problem," European Journal of Operational Research, Elsevier, vol. 235(1), pages 252-264.
    8. Lusby, Richard Martin & Range, Troels Martin & Larsen, Jesper, 2016. "A Benders decomposition-based matheuristic for the Cardinality Constrained Shift Design Problem," European Journal of Operational Research, Elsevier, vol. 254(2), pages 385-397.
    9. Mesquita, Marta & Moz, Margarida & Paias, Ana & Pato, Margarida, 2015. "A decompose-and-fix heuristic based on multi-commodity flow models for driver rostering with days-off pattern," European Journal of Operational Research, Elsevier, vol. 245(2), pages 423-437.
    10. Range, Troels Martin & Kozlowski, Dawid & Petersen, Niels Chr., 2017. "A shortest-path-based approach for the stochastic knapsack problem with non-decreasing expected overfilling costs," Discussion Papers on Economics 9/2017, University of Southern Denmark, Department of Economics.

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