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Long-term staffing based on qualification profiles

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  • 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
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    File URL: https://www.econstor.eu/bitstream/10419/147650/1/manuskript_592.pdf
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    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.
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    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.

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