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On the trade-off between staff-decomposed and activity-decomposed column generation for a staff scheduling problem

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  • Jeroen Beliën
  • Erik Demeulemeester

Abstract

In this paper a comparison is made between two decomposition techniques to solve a staff scheduling problem with column generation. In the first approach, decomposition takes place on the staff members, whereas in the second approach decomposition takes place on the activities that have to be performed by the staff members. The resulting master LP is respectively a set partitioning problem and a capacitated multi-commodity flow problem. Both approaches have been implemented in a branch-and-price algorithm. We show a trade-off between modeling power and computation times of both techniques. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • Jeroen Beliën & Erik Demeulemeester, 2007. "On the trade-off between staff-decomposed and activity-decomposed column generation for a staff scheduling problem," Annals of Operations Research, Springer, vol. 155(1), pages 143-166, November.
    • Handle: RePEc:spr:annopr:v:155:y:2007:i:1:p:143-166:10.1007/s10479-007-0220-2
    DOI: 10.1007/s10479-007-0220-2
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    References listed on IDEAS

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    9. Belien, Jeroen & Demeulemeester, Erik, 2006. "Scheduling trainees at a hospital department using a branch-and-price approach," European Journal of Operational Research, Elsevier, vol. 175(1), pages 258-278, November.
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    Cited by:

    1. Jens Brunner & Günther Edenharter, 2011. "Long term staff scheduling of physicians with different experience levels in hospitals using column generation," Health Care Management Science, Springer, vol. 14(2), pages 189-202, June.
    2. Volland, Jonas & Fügener, Andreas & Brunner, Jens O., 2017. "A column generation approach for the integrated shift and task scheduling problem of logistics assistants in hospitals," European Journal of Operational Research, Elsevier, vol. 260(1), pages 316-334.
    3. Akbarzadeh, Babak & Maenhout, Broos, 2021. "A decomposition-based heuristic procedure for the Medical Student Scheduling problem," European Journal of Operational Research, Elsevier, vol. 288(1), pages 63-79.
    4. Junhong Guo & William Pozehl & Amy Cohn, 2023. "A two-stage partial fixing approach for solving the residency block scheduling problem," Health Care Management Science, Springer, vol. 26(2), pages 363-393, June.
    5. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    6. Burak Bilgin & Patrick Causmaecker & Benoît Rossie & Greet Vanden Berghe, 2012. "Local search neighbourhoods for dealing with a novel nurse rostering model," Annals of Operations Research, Springer, vol. 194(1), pages 33-57, April.
    7. Maenhout, Broos & Vanhoucke, Mario, 2013. "An integrated nurse staffing and scheduling analysis for longer-term nursing staff allocation problems," Omega, Elsevier, vol. 41(2), pages 485-499.
    8. Eyjólfur Ingi Ásgeirsson & Guðríður Lilla Sigurðardóttir, 2016. "Near-optimal MIP solutions for preference based self-scheduling," Annals of Operations Research, Springer, vol. 239(1), pages 273-293, April.
    9. Lin, Shih-Wei & Ying, Kuo-Ching, 2014. "Minimizing shifts for personnel task scheduling problems: A three-phase algorithm," European Journal of Operational Research, Elsevier, vol. 237(1), pages 323-334.
    10. Dohn, Anders & Mason, Andrew, 2013. "Branch-and-price for staff rostering: An efficient implementation using generic programming and nested column generation," European Journal of Operational Research, Elsevier, vol. 230(1), pages 157-169.
    11. Eyjólfur Ásgeirsson, 2014. "Bridging the gap between self schedules and feasible schedules in staff scheduling," Annals of Operations Research, Springer, vol. 218(1), pages 51-69, July.

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