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Robust shift generation in workforce planning

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Abstract

In this paper we apply robust optimization techniques to the shift generation problem in workforce planning. At the time that the shifts are generated, there is often much uncertainty in the workload predictions. We propose a model to generate shifts that are robust against this uncertainty. An adversarial approach is used to solve the resulting robust optimization model. In each iteration an integer nonlinear knapsack problem is solved to calculate the worst case workload scenario. We apply the approach to generate shifts in a real-life Air Traffic Controller workforce planning problem. The numerical results show the value of our approach.

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Authors and Affiliations

  1. Blue Rock Logistics, ‘s Hertogenbosch, The Netherlands

    Dori van Hulst

  2. Department of Econometrics and Operations Research, Tilburg University, Tilburg, The Netherlands

    Dick den Hertog

  3. Quintiq, ‘s Hertogenbosch, The Netherlands

    Wim Nuijten

  4. Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands

    Wim Nuijten

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  1. Dori van Hulst
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  2. Dick den Hertog
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  3. Wim Nuijten
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Correspondence to Dori van Hulst.

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van Hulst, D., den Hertog, D. & Nuijten, W. Robust shift generation in workforce planning. Comput Manag Sci 14, 115–134 (2017). https://doi.org/10.1007/s10287-016-0265-2

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  • DOI: https://doi.org/10.1007/s10287-016-0265-2

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