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An estimation of distribution algorithm with intelligent local search for rule-based nurse rostering

Aickelin, U; Burke, Edmund; Li, Jingpeng

Authors

U Aickelin

Edmund Burke

Jingpeng Li



Abstract

This paper proposes a new memetic evolutionary algorithm to achieve explicit learning in rule-based nurse rostering, which involves applying a set of heuristic rules for each nurse's assignment. The main framework of the algorithm is an estimation of distribution algorithm, in which an ant-miner methodology improves the individual solutions produced in each generation. Unlike our previous work (where learning is implicit), the learning in the memetic estimation of distribution algorithm is explicit, i.e. we are able to identify building blocks directly. The overall approach learns by building a probabilistic model, i.e. an estimation of the probability distribution of individual nurse-rule pairs that are used to construct schedules. The local search processor (i.e. the ant-miner) reinforces nurse-rule pairs that receive higher rewards. A challenging real world nurse rostering problem is used as the test problem. Computational results show that the proposed approach outperforms most existing approaches. It is suggested that the learning methodologies suggested in this paper may be applied to other scheduling problems where schedules are built systematically according to specific rules.

Citation

Aickelin, U., Burke, E., & Li, J. (2007). An estimation of distribution algorithm with intelligent local search for rule-based nurse rostering. Journal of the Operational Research Society, 58(12), 1574-1585. https://doi.org/10.1057/palgrave.jors.2602308

Journal Article Type Article
Acceptance Date Aug 1, 2006
Online Publication Date Dec 21, 2017
Publication Date 2007-12
Deposit Date Oct 30, 2007
Publicly Available Date Dec 31, 2007
Journal Journal of the Operational Research Society
Print ISSN 0160-5682
Electronic ISSN 1476-9360
Publisher Taylor & Francis Open
Peer Reviewed Peer Reviewed
Volume 58
Issue 12
Pages 1574-1585
DOI https://doi.org/10.1057/palgrave.jors.2602308
Keywords Marketing; Management Science and Operations Research; Strategy and Management; Management Information Systems
Public URL http://eprints.nottingham.ac.uk/id/eprint/655
Publisher URL https://www.tandfonline.com/doi/full/10.1057/palgrave.jors.2602308
Additional Information This is a post-peer-review, pre-copyedit version of an article published in Journal of the Operational Research Society. The definitive publisher-authenticated version Aickelin, Uwe and Burke, Edmund and Li, Jingpeng (2007) An Estimation of Distribution Algorithm with Intelligent Local Search for Rule-based Nurse Rostering. Journal of the Operational Research Society is available online at the offical URL above.

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