An Ant Colony Optimization algorithm for a dynamic regional nurse-scheduling problem in Austria

An Ant Colony Optimization algorithm for a dynamic regional nurse-scheduling problem in Austria

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Article ID: iaor20073787
Country: United Kingdom
Volume: 34
Issue: 3
Start Page Number: 642
End Page Number: 666
Publication Date: Mar 2007
Journal: Computers and Operations Research
Authors: ,
Keywords: scheduling, heuristics: ant systems
Abstract:

To the best of our knowledge, this paper describes the first ant colony optimization (ACO) approach applied to nurse scheduling, analyzing adynamic regional problem which is currently under discussion at the Vienna hospital compound. Each day, pool nurses have to be assigned for the following days to public hospitals while taking into account a variety of soft and hard constraints regarding working date and time, working patterns, nurses' qualifications, nurses' and hospitals' preferences, as well as costs. Extensive computational experiments based on a four week simulation period were used to evaluate three different scenarios varying the number of nurses and hospitals for six different hospitals' demand intensities. The results of our simulations and optimizations reveal that the proposed ACO algorithm achieves highly significant improvements compared to a greedy assignment algorithm.

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