A Column Generation-Based Diving Heuristic for Staff Scheduling at an Emergency Medical Service

  • Hendrik VermuytenEmail author
  • Joana Namorado Rosa
  • Inês Marques
  • Jeroen Beliën
  • Ana Barbosa-Póvoa
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 278)


Staff scheduling involves assigning people to tasks organized in working shifts. It is a complex and time-consuming activity common to several real-world companies while still typically a hand-made task. These problems are usually conditioned by legal and working rules, and by personal preferences. Thus, the challenge is to find schedules that most accurately fit the functionality of the services and equity issues. For this purpose, a column generation-based diving heuristic is proposed to solve a staff scheduling problem at an Emergency Medical Service. The approach is generic and possibly adjusted to several realities and companies. In this context, the heuristic is applied to a real-life problem at Instituto Nacional de Emergência Médica (INEM), obtaining good quality solutions in relatively short running times. The best-found solution is compared with an implemented schedule at INEM, strengthening the practical value of this approach. The ultimate goal is to develop automated tools to support INEM in their staff scheduling activities.


OR in health services Emergency medical services Staff scheduling Diving heuristic Column generation 



The authors thank the personnel of INEM for the fruitful meetings and discussions and for providing the data for the case study. Hendrik Vermuyten was sponsored by the Research Foundation Flanders (FWO), travel grant no. V418317N.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Hendrik Vermuyten
    • 1
    • 2
    Email author
  • Joana Namorado Rosa
    • 1
  • Inês Marques
    • 1
  • Jeroen Beliën
    • 2
  • Ana Barbosa-Póvoa
    • 1
  1. 1.Centre for Management Studies, Instituto Superior Técnico, University of LisbonLisbonPortugal
  2. 2.Faculty of Economics and Business, Department of Information Management, Modeling and SimulationKU Leuven Campus BrusselsBrusselsBelgium

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