This paper considers the daily assignment of newborn infant patients to nurses in a hospital. The objective is to balance the workload of the nurses, while satisfying a variety of side constraints. Prior work proposed a MIP model for this problem, which unfortunately did not scale to large instances and only approximated the objective function, since minimizing the variance cannot be expressed in a linear model. This paper presents constraint programming (CP) models of increasing complexity to solve large instances with hundreds of patients and nurses in a few seconds using the Comet optimization system. The CP models use the recent spread global constraint to minimize the variance, as well as an exact decomposition technique. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Schaus, P., Van Hentenryck, P., & Régin, J. C. (2009). Scalable load balancing in nurse to patient assignment problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5547 LNCS, pp. 248–262). https://doi.org/10.1007/978-3-642-01929-6_19
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