Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic
Main Author: | |
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Publication Date: | 2008 |
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Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10400.5/96350 |
Summary: | Nurse rerostering arises when at least one nurse announces that she will be unable to undertake the tasks previously assigned to her. The problem amounts to building a new roster that satisfies the hard constraints already met by the current one and, as much as possible, fulfils two groups of soft constraints which define the two objectives to be attained. A bi-objective genetic heuristic was designed on the basis of a population of individuals characterised by pairs of chromosomes, whose fitness complies with the Pareto ranking of the respective decoded solution. It includes an elitist policy, as well as a new utopic strategy, introduced for purposes of diversification. The computational experiments produced promising results for the practical application of this approach to real life instances arising from a public hospital in Lisbon. |
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Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristicNurse SchedulingRerosteringBi-Objective HeuristicsGenetic AlgorithmsNurse rerostering arises when at least one nurse announces that she will be unable to undertake the tasks previously assigned to her. The problem amounts to building a new roster that satisfies the hard constraints already met by the current one and, as much as possible, fulfils two groups of soft constraints which define the two objectives to be attained. A bi-objective genetic heuristic was designed on the basis of a population of individuals characterised by pairs of chromosomes, whose fitness complies with the Pareto ranking of the respective decoded solution. It includes an elitist policy, as well as a new utopic strategy, introduced for purposes of diversification. The computational experiments produced promising results for the practical application of this approach to real life instances arising from a public hospital in Lisbon.Springer NatureRepositório da Universidade de LisboaPato, Margarida VazMoz, Margarida2024-12-16T09:14:19Z20082008-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/96350engPato, Margarida Vaz and Margarida Moz .( 2008). “Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic”, Journal of Heuristics, Volume 14: pp. 359–374. 20081572-9397info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T16:29:59Zoai:repositorio.ulisboa.pt:10400.5/96350Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T04:17:01.857321Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic |
title |
Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic |
spellingShingle |
Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic Pato, Margarida Vaz Nurse Scheduling Rerostering Bi-Objective Heuristics Genetic Algorithms |
title_short |
Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic |
title_full |
Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic |
title_fullStr |
Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic |
title_full_unstemmed |
Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic |
title_sort |
Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic |
author |
Pato, Margarida Vaz |
author_facet |
Pato, Margarida Vaz Moz, Margarida |
author_role |
author |
author2 |
Moz, Margarida |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Pato, Margarida Vaz Moz, Margarida |
dc.subject.por.fl_str_mv |
Nurse Scheduling Rerostering Bi-Objective Heuristics Genetic Algorithms |
topic |
Nurse Scheduling Rerostering Bi-Objective Heuristics Genetic Algorithms |
description |
Nurse rerostering arises when at least one nurse announces that she will be unable to undertake the tasks previously assigned to her. The problem amounts to building a new roster that satisfies the hard constraints already met by the current one and, as much as possible, fulfils two groups of soft constraints which define the two objectives to be attained. A bi-objective genetic heuristic was designed on the basis of a population of individuals characterised by pairs of chromosomes, whose fitness complies with the Pareto ranking of the respective decoded solution. It includes an elitist policy, as well as a new utopic strategy, introduced for purposes of diversification. The computational experiments produced promising results for the practical application of this approach to real life instances arising from a public hospital in Lisbon. |
publishDate |
2008 |
dc.date.none.fl_str_mv |
2008 2008-01-01T00:00:00Z 2024-12-16T09:14:19Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.5/96350 |
url |
http://hdl.handle.net/10400.5/96350 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Pato, Margarida Vaz and Margarida Moz .( 2008). “Solving a bi-objective nurse rerostering problem by using a utopic Pareto genetic heuristic”, Journal of Heuristics, Volume 14: pp. 359–374. 2008 1572-9397 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Springer Nature |
publisher.none.fl_str_mv |
Springer Nature |
dc.source.none.fl_str_mv |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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