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Modeling and solving a real-life multi-skill shift design problem

Author

Listed:
  • Alex Bonutti

    (EasyStaff s.r.l.)

  • Sara Ceschia

    (University of Udine)

  • Fabio De Cesco

    (EasyStaff s.r.l.)

  • Nysret Musliu

    (Technische Universität)

  • Andrea Schaerf

    (University of Udine)

Abstract

In this work, we consider the shift design problem and we define a novel, complex formulation arising from practical cases. In addition, we propose a new search method based on a fast Simulated Annealing, that, differently from previous approaches, solves the overall problem as a single-stage procedure. The core of the method is a composite neighborhood that includes at the same time changes in the staffing of shifts, the shape of shifts, and the position of breaks. Finally, we present a statistically-principled experimental analysis on a set of instances obtained from real cases. Both instances and results are available on the web for future comparisons.

Suggested Citation

  • Alex Bonutti & Sara Ceschia & Fabio De Cesco & Nysret Musliu & Andrea Schaerf, 2017. "Modeling and solving a real-life multi-skill shift design problem," Annals of Operations Research, Springer, vol. 252(2), pages 365-382, May.
    • Handle: RePEc:spr:annopr:v:252:y:2017:i:2:d:10.1007_s10479-016-2175-7
    DOI: 10.1007/s10479-016-2175-7
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    References listed on IDEAS

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    Cited by:

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    2. Adibah Shuib & Faiq Izzuddin Kamarudin, 2019. "Solving shift scheduling problem with days-off preference for power station workers using binary integer goal programming model," Annals of Operations Research, Springer, vol. 272(1), pages 355-372, January.

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