@article { , title = {Building better nurse scheduling algorithms}, 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 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.}, doi = {10.1023/B:ANOR.0000019103.31340.a6}, eissn = {1572-9338}, issn = {0254-5330}, issue = {1-4}, journal = {Annals of Operations Research}, pages = {159-177}, publicationstatus = {Published}, publisher = {Springer (part of Springer Nature)}, url = {https://uwe-repository.worktribe.com/output/1064134}, volume = {128}, keyword = {Mathematics and Statistics Research Group, nurse scheduling, evolutionary algorithms, integer programming, statistical comparison method}, year = {2004}, author = {Aickelin, Uwe and White, Paul} }