Abstract
An important problem in staff scheduling is roster generation. The task is to find an assignment of shifts to employees, such that qualification restrictions and demands are met as well as possible. This assignment problem is in particular challenging due to business rules concerning working time, day on/off patterns, rest times, or employee preferences. The present paper outlines INFORM’s staff rostering optimizer that is used to solve large-scale real-world rostering instances, and evaluates the performance of the optimizer on nurse rostering data. Moreover, we describe how we integrate the optimizer into our system and adapt it to the needs of our customers using a declarative programming framework.
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Bender, M., Berckey, S., Elberfeld, M., Herbers, J. (2019). Real-World Staff Rostering via Branch-and-Price in a Declarative Framework. In: Fortz, B., Labbé, M. (eds) Operations Research Proceedings 2018. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-030-18500-8_55
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DOI: https://doi.org/10.1007/978-3-030-18500-8_55
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