Solving the nurse scheduling problem in crisis situations applying a genetic algorithm

dc.contributor.authorHeiniger, Nico
dc.contributor.authorMassaro, Gabriel
dc.contributor.authorHanne, Thomas
dc.contributor.authorDornberger, Rolf
dc.date.accessioned2025-02-10T07:45:49Z
dc.date.issued2023
dc.description.abstractThis 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.
dc.event10th International Conference on Soft Computing & Machine Intelligence (ISCMI)
dc.identifier.doi10.1109/ISCMI59957.2023.10458617
dc.identifier.isbn979-8-3503-5937-4
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/48255
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2023 10th International Conference on Soft Computing & Machine Intelligence (ISCMI 2023)
dc.spatialMexico City
dc.subject.ddc330 - Wirtschaft
dc.titleSolving the nurse scheduling problem in crisis situations applying a genetic algorithm
dc.type04B - Beitrag Konferenzschrift
dspace.entity.typePublication
fhnw.InventedHereYes
fhnw.ReviewTypeAnonymous ex ante peer review of a complete publication
fhnw.affiliation.hochschuleHochschule für Wirtschaft FHNWde_CH
fhnw.affiliation.institutInstitut für Wirtschaftsinformatikde_CH
fhnw.openAccessCategoryClosed
fhnw.pagination65-71
fhnw.publicationStatePublished
relation.isAuthorOfPublication3c3d987c-7860-4cd5-9179-18a5f54fc630
relation.isAuthorOfPublicationda0af49b-7230-498a-859b-0229516ba079
relation.isAuthorOfPublication35d8348b-4dae-448a-af2a-4c5a4504da04
relation.isAuthorOfPublication64196f63-c326-4e10-935d-6776cc91354c
relation.isAuthorOfPublication.latestForDiscovery35d8348b-4dae-448a-af2a-4c5a4504da04
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