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http://hdl.handle.net/1893/31316| Appears in Collections: | Computing Science and Mathematics Book Chapters and Sections |
| Title: | BOA for Nurse Scheduling |
| Author(s): | Li, Jingpeng Aickelin, Uwe |
| Contact Email: | jli@cs.stir.ac.uk |
| Editor(s): | CantúPaz, Erick Pelikan, Martin Sastry, Kumara |
| 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 |
| Keywords: | Nurse Scheduling Bayesian Optimization Algorithm Probabilistic Modeling |
| Issue Date: | 2006 |
| Date Deposited: | 19-Jun-2020 |
| Series/Report no.: | Studies in Computational Intelligence, 33 |
| 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. |
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| DOI Link: | 10.1007/978-3-540-34954-9_14 |
| Licence URL(s): | http://www.rioxx.net/licenses/under-embargo-all-rights-reserved |
| File | Description | Size | Format | |
|---|---|---|---|---|
| Li-Aickelin_Chapter_2006.pdf | Fulltext - Published Version | 1.84 MB | Adobe PDF | Under Permanent Embargo Request a copy |
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