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Modelling and evaluation issues in nurse rostering
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AI
DOI：10.1007/s10479-012-1116-3.png)
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Abstract
En 中文
In practice nurse rostering problems are often too complex to be expressed through available academic models. Such models are not rich enough to represent the variegated nature of real world scenarios, and therefore have no practical relevance. This article focuses on two particular modelling issues that require careful consideration in making academic nurse rostering approaches re-usable in a real world environment. First: introducing several complex problem characteristics, resulting in a rich, generic model. A detailed description is provided for researchers interested in using this new model. We also present a novel benchmark dataset based on this rich model. Second: the consideration of a consistent evaluation procedure that corresponds to realistic quality measurement. These contributions will enable faster implementation of academic nurse rostering achievements in real hospital environments. A suite of hyper-heuristics is presented. These are capable of solving these rich personnel rostering problems using the presented evaluation procedures. Their performance is compared to that of another meta-heuristic.
Keywords:
Nurse rostering
Personnel scheduling
Evaluation function
Generic model
Hyper-heuristics
Journal
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4.5
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2.1W
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