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A Polyhedral Approach for the Staff Rostering Problem

Author

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  • Giovanni Felici

    (Instituto di Analisi dei Sistemi ed Informatica "Antonio Ruberti" (IASI-CNR), Viale Manzoni 30, 00185 Roma, Italy)

  • Claudio Gentile

    (Instituto di Analisi dei Sistemi ed Informatica "Antonio Ruberti" (IASI-CNR), Viale Manzoni 30, 00185 Roma, Italy)

Abstract

In this paper we formulate and efficiently solve staff scheduling problems for large organizations that provide continuous services to customers. We describe an integer programming approach for a class of such problems, where solutions have to obey a number of constraints related to workload balancing, shift compatibility, and distribution of days off. The formulation of the constraints is general and can be extended to different personnel management problems where staff members must cover shifts, and management must assign a fixed number of days off per week. The model maximizes staff satisfaction, expressed by positive weights for pairs of shifts in consecutive days. We consider the associated polytope and study its structure, determining some classes of inequalities that are facet inducing for special subproblems and other valid classes. We also identify a particular subproblem whose solution can be used to determine strong cuts for the complete problem. In addition, we design special branching rules that break the symmetries that arise in the solution space and have a large impact in the efficiency of the method. The validity of this approach has been ascertained by extensive computational tests; moreover, the operations research (OR) department of an airline has implemented the method to solve ground staff management problems.

Suggested Citation

  • Giovanni Felici & Claudio Gentile, 2004. "A Polyhedral Approach for the Staff Rostering Problem," Management Science, INFORMS, vol. 50(3), pages 381-393, March.
  • Handle: RePEc:inm:ormnsc:v:50:y:2004:i:3:p:381-393
    DOI: 10.1287/mnsc.1030.0142
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    References listed on IDEAS

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    2. Jens O. Brunner & Jonathan F. Bard & Jan M. Köhler, 2013. "Bounded flexibility in days‐on and days‐off scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(8), pages 678-701, December.
    3. Broos Maenhout & Mario Vanhoucke, 2008. "Comparison and hybridization of crossover operators for the nurse scheduling problem," Annals of Operations Research, Springer, vol. 159(1), pages 333-353, March.
    4. Hadi W. Purnomo & Jonathan F. Bard, 2007. "Cyclic preference scheduling for nurses using branch and price," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(2), pages 200-220, March.
    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. Aleksandra Marcikic Horvat & Branislav Dudic & Boris Radovanov & Boban Melovic & Otilija Sedlak & Monika Davidekova, 2020. "Binary Programming Model for Rostering Ambulance Crew-Relevance for the Management and Business," Mathematics, MDPI, vol. 9(1), pages 1-13, December.
    7. Jordi Castro & Fernando Sarachaga, 2021. "An online optimization-based procedure for the assignment of airplane seats," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 204-247, April.
    8. Mariel Lavieri & Martin Puterman, 2009. "Optimizing nursing human resource planning in British Columbia," Health Care Management Science, Springer, vol. 12(2), pages 119-128, June.
    9. B Maenhout & M Vanhoucke, 2009. "The impact of incorporating nurse-specific characteristics in a cyclical scheduling approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1683-1698, December.
    10. Oyku Ahipasaoglu & Nesim Erkip & Oya Ekin Karasan, 2019. "The venue management problem: setting staffing levels, shifts and shift schedules at concession stands," Journal of Scheduling, Springer, vol. 22(1), pages 69-83, February.

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