IDEAS home Printed from https://ideas.repec.org/p/zbw/cauman/592.html
   My bibliography  Save this paper

Long-term staffing based on qualification profiles

Author

Listed:
  • Drexl, Andreas
  • Mundschenk, Martin

Abstract

Manpower still is one of the most expansive resources, in spite of increasing automation. While employee scheduling and rostering has been the topic of extensive research over the past decades, usually it is assumed that the demand for staff is either given or can be obtained without difficulty. In this research we close the gap between practical needs and available models and methods. In particular, we provide an integer programming model for long-term staffing decisions. The model is based on qualification profiles, the number of which grows exponentially in terms of the number of processes considered. In order to compute tight lower bounds we provide a column generation technique. The subproblem is a shortest path problem in a network where the arcs have multiple weights. Upper bounds, that is, feasible solutions are calculated by means of local search. We present computational results for randomly generated instances and empirical results for examples from practice. From these results it is evident that the bounds are tight and that substantial cost savings can be achieved.

Suggested Citation

  • Drexl, Andreas & Mundschenk, Martin, 2005. "Long-term staffing based on qualification profiles," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 592, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    • Handle: RePEc:zbw:cauman:592
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/147650/1/manuskript_592.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David S. Johnson & Cecilia R. Aragon & Lyle A. McGeoch & Catherine Schevon, 1991. "Optimization by Simulated Annealing: An Experimental Evaluation; Part II, Graph Coloring and Number Partitioning," Operations Research, INFORMS, vol. 39(3), pages 378-406, June.
    2. David S. Johnson & Cecilia R. Aragon & Lyle A. McGeoch & Catherine Schevon, 1989. "Optimization by Simulated Annealing: An Experimental Evaluation; Part I, Graph Partitioning," Operations Research, INFORMS, vol. 37(6), pages 865-892, December.
    3. R. N. Burns & M. W. Carter, 1985. "Work Force Size and Single Shift Schedules with Variable Demands," Management Science, INFORMS, vol. 31(5), pages 599-607, May.
    4. Ernst, A. T. & Jiang, H. & Krishnamoorthy, M. & Sier, D., 2004. "Staff scheduling and rostering: A review of applications, methods and models," European Journal of Operational Research, Elsevier, vol. 153(1), pages 3-27, February.
    5. Mundschenk, Martin & Drexl, Andreas, 2005. "Work force planning in the printing industry," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 593, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre (Ed.), 2006. "Jahresbericht 2005," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 603, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andreas Drexl & Martin Mundschenk, 2008. "Long-term staffing based on qualification profiles," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 68(1), pages 21-47, August.
    2. Schlereth, Christian & Stepanchuk, Tanja & Skiera, Bernd, 2010. "Optimization and analysis of the profitability of tariff structures with two-part tariffs," European Journal of Operational Research, Elsevier, vol. 206(3), pages 691-701, November.
    3. Pirlot, Marc, 1996. "General local search methods," European Journal of Operational Research, Elsevier, vol. 92(3), pages 493-511, August.
    4. Andreas Fügener & Jens O. Brunner, 2019. "Planning for Overtime: The Value of Shift Extensions in Physician Scheduling," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 732-744, October.
    5. 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.
    6. Kim, Yeong-Dae & Lim, Hyeong-Gyu & Park, Moon-Won, 1996. "Search heuristics for a flowshop scheduling problem in a printed circuit board assembly process," European Journal of Operational Research, Elsevier, vol. 91(1), pages 124-143, May.
    7. B Suman & P Kumar, 2006. "A survey of simulated annealing as a tool for single and multiobjective optimization," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1143-1160, October.
    8. Khan, W. A. & Hayhurst, D. R. & Cannings, C., 1999. "Determination of optimal path under approach and exit constraints," European Journal of Operational Research, Elsevier, vol. 117(2), pages 310-325, September.
    9. Sabuncuoglu, Ihsan & Erel, Erdal & Alp, Arda, 2009. "Ant colony optimization for the single model U-type assembly line balancing problem," International Journal of Production Economics, Elsevier, vol. 120(2), pages 287-300, August.
    10. Drexl, Andreas & Haase, Knut, 1993. "Sequential-analysis-based randomized-regret-methods for lotsizing and scheduling," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 323, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    11. Robin C. Ball & Juergen Branke & Stephan Meisel, 2018. "Optimal Sampling for Simulated Annealing Under Noise," INFORMS Journal on Computing, INFORMS, vol. 30(1), pages 200-215, February.
    12. Jonathan Bard & David Morton & Yong Wang, 2007. "Workforce planning at USPS mail processing and distribution centers using stochastic optimization," Annals of Operations Research, Springer, vol. 155(1), pages 51-78, November.
    13. Michael J. Brusco & Larry W. Jacobs, 1993. "A simulated annealing approach to the cyclic staff‐scheduling problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(1), pages 69-84, February.
    14. Broos Maenhout & Mario Vanhoucke, 2017. "A resource type analysis of the integrated project scheduling and personnel staffing problem," Annals of Operations Research, Springer, vol. 252(2), pages 407-433, May.
    15. Laurent Michel & Pascal Van Hentenryck, 1999. "Localizer: A Modeling Language for Local Search," INFORMS Journal on Computing, INFORMS, vol. 11(1), pages 1-14, February.
    16. Van Breedam, Alex, 1995. "Improvement heuristics for the Vehicle Routing Problem based on simulated annealing," European Journal of Operational Research, Elsevier, vol. 86(3), pages 480-490, November.
    17. Voudouris, Christos & Tsang, Edward, 1999. "Guided local search and its application to the traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 113(2), pages 469-499, March.
    18. Goodson, Justin C. & Ohlmann, Jeffrey W. & Thomas, Barrett W., 2012. "Cyclic-order neighborhoods with application to the vehicle routing problem with stochastic demand," European Journal of Operational Research, Elsevier, vol. 217(2), pages 312-323.
    19. Jens Brunner & Jonathan Bard & Rainer Kolisch, 2009. "Flexible shift scheduling of physicians," Health Care Management Science, Springer, vol. 12(3), pages 285-305, September.
    20. Chang-Yong Lee & Dongju Lee, 2014. "Determination of initial temperature in fast simulated annealing," Computational Optimization and Applications, Springer, vol. 58(2), pages 503-522, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:cauman:592. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/ibkiede.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.