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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Memetic Algorithms for Nurse Rostering
verfasst von : Ender Özcan
Erschienen in: Computer and Information Sciences - ISCIS 2005
Verlag: Springer Berlin Heidelberg
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Nurse rostering problems represent a subclass of scheduling problems that are hard to solve. The goal is finding high quality shift and resource assignments, satisfying the needs and requirements of employees as well as the employers in healthcare institutions. In this paper, a real case of a nurse rostering problem is introduced. Memetic Algorithms utilizing different type of promising genetic operators and a self adaptive violation directed hierarchical hill climbing method are presented based on a previously proposed framework.