Bonutti, A., Ceschia, S., De Cesco, F., Musliu, N., & Schaerf, A. (2017). Modeling and solving a real-life multi-skill shift design problem. Annals of Operations Research, 252(2), 365–382. https://doi.org/10.1007/s10479-016-2175-7
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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Journal:
Annals of Operations Research
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ISSN:
0254-5330
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Date (published):
2017
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Number of Pages:
18
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Publisher:
SPRINGER
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Peer reviewed:
Yes
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Keywords:
design; Modeling; Management Science and Operations Research; General Decision Sciences; solving; a real-life; multi-skill; shift; problem
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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.
en
Project title:
Artificial Intelligence in Employee Scheduling: P 24814-N23 (Fonds zur Förderung der wissenschaftlichen Forschung (FWF))
