Abstract
This paper tackles a Nurse Scheduling Problem which consists of generating work schedules for a set of nurses while considering their shift preferences and other requirements. The objective is to maximize the satisfaction of nurses’ preferences and minimize the violation of soft constraints. This paper presents a new deterministic heuristic algorithm, called MAPA (multi-assignment problem-based algorithm), which is based on successive resolutions of the assignment problem. The algorithm has two phases: a constructive phase and an improvement phase. The constructive phase builds a full schedule by solving successive assignment problems, one for each day in the planning period. The improvement phase uses a couple of procedures that re-solve assignment problems to produce a better schedule. Given the deterministic nature of this algorithm, the same schedule is obtained each time that the algorithm is applied to the same problem instance. The performance of MAPA is benchmarked against published results for almost 250,000 instances from the NSPLib dataset. In most cases, particularly on large instances of the problem, the results produced by MAPA are better when compared to best-known solutions from the literature. The experiments reported here also show that the MAPA algorithm finds more feasible solutions compared with other algorithms in the literature, which suggest that this proposed approach is effective and robust.
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Notes
We excluded 33 cases involving 30 nurses and 5 cases involving 60 nurses for which NSPLib reports infeasible solutions.
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Acknowledgements
The authors thank the referees very much for their valuable input during the review process which helped a lot in improving earlier versions of this paper. Also, thanks to the CNPq (National Council for Scientific and Technological Development) and CAPES (Brazil’s Ministry of Education) for partial financial support to develop this work.
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Constantino, A.A., Landa-Silva, D., de Melo, E.L. et al. A heuristic algorithm based on multi-assignment procedures for nurse scheduling. Ann Oper Res 218, 165–183 (2014). https://doi.org/10.1007/s10479-013-1357-9
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DOI: https://doi.org/10.1007/s10479-013-1357-9