Building Better Nurse Scheduling Algorithms

Aickelin, Uwe; White, Paul

Abstract

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 building 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.

Citation

Aickelin, U., & White, P. (2004). Building Better Nurse Scheduling Algorithms. Annals of Operations Research, 128, https://doi.org/10.1023/B%3AANOR.0000019103.31340.a6

• Journal Article Type: Article
• Publication Date: Jan 1, 2004
• Deposit Date: Oct 30, 2007
• Publicly Available Date: Oct 30, 2007
• Journal: Annals of Operations Research
• Print ISSN: 0254-5330
• Electronic ISSN: 1572-9338
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 128
• DOI: https://doi.org/10.1023/B%3AANOR.0000019103.31340.a6
• Keywords: Nurse scheduling, evolutionary algorithms, integer programming, statistical comparison method
• Public URL: https://nottingham-repository.worktribe.com/output/1021161
• Publisher URL: http://www.springerlink.com/content/q93031860641r204/?p=5f848c4af3294077a0535c6baba1a76f&pi=7
• Additional Information: The original publication is available at www.springerlink.com