'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling'
Abstract. Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person's assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
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Springer-Verlag
2004
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| Online Access: | https://eprints.nottingham.ac.uk/620/ |
| _version_ | 1848790445883129856 |
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| author | Li, Jingpeng Aickelin, Uwe |
| author_facet | Li, Jingpeng Aickelin, Uwe |
| author_sort | Li, Jingpeng |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Abstract. Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person's assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning in both approaches is explicit, i.e. we are able to identify building blocks directly. To achieve this target, the Bayesian optimization algorithm builds a Bayesian network of the joint probability distribution of the rules used to construct solutions, while the adapted classifier system assigns each rule a strength value that is constantly updated according to its usefulness in the current situation. Computational results from 52 real data instances of nurse scheduling demonstrate the success of both approaches. It is also suggested that the learning mechanism in the proposed approaches might be suitable for other scheduling problems. |
| first_indexed | 2025-11-14T18:12:44Z |
| format | Conference or Workshop Item |
| id | nottingham-620 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:12:44Z |
| publishDate | 2004 |
| publisher | Springer-Verlag |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-6202020-05-04T20:31:36Z https://eprints.nottingham.ac.uk/620/ 'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling' Li, Jingpeng Aickelin, Uwe Abstract. Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person's assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning in both approaches is explicit, i.e. we are able to identify building blocks directly. To achieve this target, the Bayesian optimization algorithm builds a Bayesian network of the joint probability distribution of the rules used to construct solutions, while the adapted classifier system assigns each rule a strength value that is constantly updated according to its usefulness in the current situation. Computational results from 52 real data instances of nurse scheduling demonstrate the success of both approaches. It is also suggested that the learning mechanism in the proposed approaches might be suitable for other scheduling problems. Springer-Verlag 2004 Conference or Workshop Item PeerReviewed Li, Jingpeng and Aickelin, Uwe (2004) 'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling'. In: 8th International Conference on Parallel Problem Solving from Nature (PPSN VIII), LNCS 3242, 2004, Birmingham, UK. |
| spellingShingle | Li, Jingpeng Aickelin, Uwe 'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling' |
| title | 'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling' |
| title_full | 'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling' |
| title_fullStr | 'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling' |
| title_full_unstemmed | 'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling' |
| title_short | 'The application of Bayesian Optimization and Classifier Systems in Nurse Scheduling' |
| title_sort | 'the application of bayesian optimization and classifier systems in nurse scheduling' |
| url | https://eprints.nottingham.ac.uk/620/ |