Book Chapter
Details
Citation
Li J & Aickelin U (2006) BOA for Nurse Scheduling. In: CantúPaz E, Pelikan M & Sastry K (eds.) Scalable Optimization via Probabilistic Modeling. Studies in Computational Intelligence, 33. Berlin Heidelberg: Springer, pp. 315-332. https://doi.org/10.1007/978-3-540-34954-9_14
Abstract
Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimization Algorithm (BOA) for the nurse scheduling problem that chooses such suitable scheduling rules from a set for each nurse’s assignment. Based on the idea of using probabilistic models, the BOA builds a Bayesian network for the set of promising solutions and samples these networks to generate new candidate solutions. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed algorithm may be suitable for other scheduling problems.
Keywords
Nurse Scheduling; Bayesian Optimization Algorithm; Probabilistic Modeling
Journal
Scalable Optimization via Probabilistic Modeling; Studies in Computational Intelligence
Status | Published |
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Title of series | Studies in Computational Intelligence |
Number in series | 33 |
Publication date | 31/12/2006 |
URL | http://hdl.handle.net/1893/31316 |
Publisher | Springer |
Place of publication | Berlin Heidelberg |
ISSN | 1860-949X |
eISSN | 1860-9503 |
ISSN of series | 1860-949X |
ISBN | 9783540349532 |
eISBN | 9783540349549 |