Robust shift generation in workforce planning

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

Research output: Contribution to journalArticleScientificpeer-review

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.
Original languageEnglish
Pages (from-to)115–134
JournalComputational Management Science
Volume14
Issue number1
DOIs
Publication statusPublished - Jan 2017

Fingerprint

Planning
Controllers
Air
Uncertainty
Workforce planning
Robust optimization
Workload
Prediction
Optimization techniques
Scenarios
Controller
Integer
Knapsack problem
Optimization model

Keywords

  • Robust optimization
  • Shift generation
  • Workforce planning

Cite this

van Hulst, D. ; den Hertog, Dick ; Nuijten, W. / Robust shift generation in workforce planning. In: Computational Management Science. 2017 ; Vol. 14, No. 1. pp. 115–134 .
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Robust shift generation in workforce planning. / van Hulst, D.; den Hertog, Dick; Nuijten, W.

In: Computational Management Science, Vol. 14, No. 1, 01.2017, p. 115–134 .

Research output: Contribution to journalArticleScientificpeer-review

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