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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

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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.

Item Type:	Book Section
RIS ID:	https://nottingham-repository.worktribe.com/output/1019208
Schools/Departments:	University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User:	Aickelin, Professor Uwe
Date Deposited:	10 Aug 2011 14:55
Last Modified:	04 May 2020 20:30
URI:	https://eprints.nottingham.ac.uk/id/eprint/1248

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