Solving the nurse scheduling problem in crisis situations applying a genetic algorithm
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Author (Corporation)
Publication date
2023
Type of student thesis
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Collections
Type
04B - Conference paper
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Parent work
2023 10th International Conference on Soft Computing & Machine Intelligence (ISCMI 2023)
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Issue / Number
Pages / Duration
65-71
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Publisher / Publishing institution
IEEE
Place of publication / Event location
Mexico City
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Abstract
This paper analyzes the nurse scheduling problem and uses a genetic algorithm to solve it considering a crisis situation. The aim is to provide an additional crisis unit in a hospital, which is sourced with specially trained staff from other units. The focus of this optimization problem is to create a staff rostering with minimal impact on the physical and mental health of the employees, while handling the challenges of a crisis with less administrative overhead.
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Event
10th International Conference on Soft Computing & Machine Intelligence (ISCMI)
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ISBN
979-8-3503-5937-4
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Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
peer-reviewed
Open access category
Closed
License
Citation
Heiniger, N., Massaro, G., Hanne, T., & Dornberger, R. (2023). Solving the nurse scheduling problem in crisis situations applying a genetic algorithm. 2023 10th International Conference on Soft Computing & Machine Intelligence (ISCMI 2023), 65–71. https://doi.org/10.1109/ISCMI59957.2023.10458617