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Decision Support for Power Plant Shift Configuration Using Stochastic Simulation

In: Operations Research Proceedings 2016

Author

Listed:
  • Pia Mareike Steenweg

    (Ruhr University Bochum)

  • Matthias Schacht

    (Ruhr University Bochum)

  • Brigitte Werners

    (Ruhr University Bochum)

Abstract

Power generation companies have to ensure a secure supply of power to their customers at any time. Hence, this particular application context implies a special feature of shift planning where a very robust solution of assignment is needed. In daily business this means all business functions have to be staffed competently at any time, otherwise a smooth power plant operation cannot take place. In this regard, optimal shift assignment is a highly important and complex task, where reliability is prioritized with respect to all other criteria, e.g. employee’s interests. In order to test a shift configuration on operational level, we conceptualise a reactive framework to support tactical decision making. The concept switches between optimisation and stochastic simulation which takes uncertainty associated with employee sickness into account. An exemplary case study with realistic data of a power generation company analyses the operational consequences of uncertain absences on the performance of a given shift configuration.

Suggested Citation

  • Pia Mareike Steenweg & Matthias Schacht & Brigitte Werners, 2018. "Decision Support for Power Plant Shift Configuration Using Stochastic Simulation," Operations Research Proceedings, in: Andreas Fink & Armin Fügenschuh & Martin Josef Geiger (ed.), Operations Research Proceedings 2016, pages 583-588, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-55702-1_77
    DOI: 10.1007/978-3-319-55702-1_77
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    Cited by:

    1. Tristan Becker & Pia Mareike Steenweg & Brigitte Werners, 2019. "Cyclic shift scheduling with on-call duties for emergency medical services," Health Care Management Science, Springer, vol. 22(4), pages 676-690, December.

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