BOA for nurse scheduling
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...
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| Other Authors: | |
| Format: | Book Section |
| Published: |
Springer
2006
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| Online Access: | https://eprints.nottingham.ac.uk/1248/ |
| _version_ | 1848790569600417792 |
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| author | Li, Jingpeng Aickelin, Uwe |
| author2 | Pelikan, Martin |
| author_facet | Pelikan, Martin Li, Jingpeng Aickelin, Uwe |
| author_sort | Li, Jingpeng |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T18:14:42Z |
| format | Book Section |
| id | nottingham-1248 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:14:42Z |
| publishDate | 2006 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-12482020-05-04T20:30:04Z https://eprints.nottingham.ac.uk/1248/ BOA for nurse scheduling Li, Jingpeng Aickelin, Uwe 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. Springer Pelikan, Martin Sastry, Kumara Cantú-Paz, Erick 2006 Book Section PeerReviewed Li, Jingpeng and Aickelin, Uwe (2006) BOA for nurse scheduling. In: Scalable optimization via probabilistic modeling: from algorithms to applications. Studies in computational intelligence, 33 (33). Springer. ISBN 9783540349532 |
| spellingShingle | Li, Jingpeng Aickelin, Uwe BOA for nurse scheduling |
| title | BOA for nurse scheduling |
| title_full | BOA for nurse scheduling |
| title_fullStr | BOA for nurse scheduling |
| title_full_unstemmed | BOA for nurse scheduling |
| title_short | BOA for nurse scheduling |
| title_sort | boa for nurse scheduling |
| url | https://eprints.nottingham.ac.uk/1248/ |