Please use this identifier to cite or link to this item: 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
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.
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
DOI Link: 10.1007/978-3-540-34954-9_14

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