Abstract
Scheduling of employees is a common problem that can be found in most organizations all over the world. One example is the nurse scheduling problem (NSP), which is a complex combinatorial opti-mization problem faced by healthcare institutions in assigning working and nonworking days. The NSP comprises constraints for the nurses, for the hospital and considers specific labor regulations, as well as the skills and preferences of workers. In summary, it involves hard and soft constraints. It is essential to create a quality timetable that can lead to a more contented and thus, more effec-tive and productive workforce. To improve this process, it can be used automated approaches and techniques. In this study, a litera-ture review about the nurse scheduling problem and how to use the Google OR-Tools software to solve it is performed. Moreover, an example of an NSP involving 10 nurses being assigned to three shifts a day, seven days a week is presented. Some condi-tions/constraints have been added in order to reproduce a real situation.
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Acknowledgments
The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 587 and UIDP/05757/2020), SusTEC (LA/P/0007/2021) and ALGORITMI Research Centre/LASI (UIDB/00319/2020). Filipe Alves thanks the FCT for supporting its research with the PhD grant SFRH/BD/143745/2019.
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Oliveira, M., Rocha, A.M.A.C., Alves, F. (2024). Using OR-Tools When Solving the Nurse Scheduling Problem. In: Pereira, A.I., Mendes, A., Fernandes, F.P., Pacheco, M.F., Coelho, J.P., Lima, J. (eds) Optimization, Learning Algorithms and Applications. OL2A 2023. Communications in Computer and Information Science, vol 1981. Springer, Cham. https://doi.org/10.1007/978-3-031-53025-8_30
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