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Building better nurse scheduling algorithms

Aickelin, Uwe; White, Paul


Uwe Aickelin

Paul White
Professor in Applied Statistics


The aim of this research is twofold: Firstly, to model and solve a complex nurse scheduling problem with an integer programming formulation and evolutionary algorithms. Secondly, to detail a novel statistical method of comparing and hence build better scheduling algorithms by identifying successful algorithm modifications. The comparison method captures the results of algorithms in a single figure that can then be compared using traditional statistical techniques. Thus, the proposed method of comparing algorithms is an objective procedure designed to assist in the process of improving an algorithm. This is achieved even when some results are non-numeric or missing due to infeasibility. The final algorithm outperforms all previous evolutionary algorithms, which relied on human expertise for modification.


Aickelin, U., & White, P. (2004). Building better nurse scheduling algorithms. Annals of Operations Research, 128(1-4), 159-177.

Journal Article Type Article
Publication Date Jan 1, 2004
Journal Annals of Operations Research
Print ISSN 0254-5330
Electronic ISSN 1572-9338
Publisher Springer (part of Springer Nature)
Peer Reviewed Peer Reviewed
Volume 128
Issue 1-4
Pages 159-177
Keywords nurse scheduling, evolutionary algorithms, integer programming, statistical comparison method
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