Robust shift generation in workforce planning

D. van Hulst, Dick den Hertog, W. Nuijten

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)115–134
JournalComputational Management Science
Issue number1
Publication statusPublished - Jan 2017


  • Robust optimization
  • Shift generation
  • Workforce planning


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