Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/15766
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: A Pareto-based search methodology for multi-objective nurse scheduling
Authors: Burke, Edmund
Li, Jingpeng
Qu, Rong
Contact Email: e.k.burke@stir.ac.uk
Keywords: Multi-objective optimization
Integer programming
Meta-heuristic search
Nurse scheduling
Issue Date: Jul-2012
Publisher: Springer
Citation: Burke E, Li J & Qu R (2012) A Pareto-based search methodology for multi-objective nurse scheduling, Annals of Operations Research, 196 (1), pp. 91-109.
Abstract: In this paper, we propose a search technique for nurse scheduling, which deals with it as a multi-objective problem. For each nurse, we first randomly generate a set of legal shift patterns which satisfy all shift-related hard constraints. We then employ an adaptive heuristic to quickly find a solution with the least number of violations on the coverage-related hard constraint by assigning one of the available shift patterns of each nurse. Next, we apply a coverage repairing procedure to make the resulting solution feasible, by adding/removing any under-covered/over-covered shifts. Finally, to satisfy the soft constraints (or preferences), we present a simulated annealing based search method with the following two options: one with a weighted-sum evaluation function which encourages moves towards users' predefined preferences, and another one with a domination-based evaluation function which encourages moves towards a more diversified approximated Pareto set. Computational results demonstrate that the proposed technique is applicable to modern hospital environments.
Type: Journal Article
URI: http://hdl.handle.net/1893/15766
DOI Link: http://dx.doi.org/10.1007/s10479-009-0590-8
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Affiliation: Deputy Principal's Office
Computing Science and Mathematics
University of Nottingham

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