A biased random-key genetic algorithm for the unequal area facility layout problem
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://repositorio.inesctec.pt/handle/123456789/5387 http://dx.doi.org/10.1016/j.ejor.2015.04.029 |
Resumo: | This paper presents a biased random-key genetic algorithm (BRKGA) for the unequal area facility layout problem (UA-FLP) where a set of rectangular facilities with given area requirements has to be placed, without overlapping, on a rectangular floor space. The objective is to find the location and the dimensions of the facilities such that the sum of the weighted distances between the centroids of the facilities is minimized. A hybrid approach combining a BRKGA, to determine the order of placement and the dimensions of each facility, a novel placement strategy, to position each facility, and a linear programming model, to fine-tune the solutions, is developed. The proposed approach is tested on 100 random datasets and 28 of benchmark datasets taken from the literature and compared with 21 other benchmark approaches. The quality of the approach was validated by the improvement of the best known solutions for 19 of the 28 extensively studied benchmark datasets. |
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7160 |
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A biased random-key genetic algorithm for the unequal area facility layout problemThis paper presents a biased random-key genetic algorithm (BRKGA) for the unequal area facility layout problem (UA-FLP) where a set of rectangular facilities with given area requirements has to be placed, without overlapping, on a rectangular floor space. The objective is to find the location and the dimensions of the facilities such that the sum of the weighted distances between the centroids of the facilities is minimized. A hybrid approach combining a BRKGA, to determine the order of placement and the dimensions of each facility, a novel placement strategy, to position each facility, and a linear programming model, to fine-tune the solutions, is developed. The proposed approach is tested on 100 random datasets and 28 of benchmark datasets taken from the literature and compared with 21 other benchmark approaches. The quality of the approach was validated by the improvement of the best known solutions for 19 of the 28 extensively studied benchmark datasets.2018-01-03T11:39:21Z2015-01-01T00:00:00Z2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/5387http://dx.doi.org/10.1016/j.ejor.2015.04.029engJosé Fernando GonçalvesResende,MGCinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:34Zoai:repositorio.inesctec.pt:123456789/5387Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:20.116729Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A biased random-key genetic algorithm for the unequal area facility layout problem |
title |
A biased random-key genetic algorithm for the unequal area facility layout problem |
spellingShingle |
A biased random-key genetic algorithm for the unequal area facility layout problem José Fernando Gonçalves |
title_short |
A biased random-key genetic algorithm for the unequal area facility layout problem |
title_full |
A biased random-key genetic algorithm for the unequal area facility layout problem |
title_fullStr |
A biased random-key genetic algorithm for the unequal area facility layout problem |
title_full_unstemmed |
A biased random-key genetic algorithm for the unequal area facility layout problem |
title_sort |
A biased random-key genetic algorithm for the unequal area facility layout problem |
author |
José Fernando Gonçalves |
author_facet |
José Fernando Gonçalves Resende,MGC |
author_role |
author |
author2 |
Resende,MGC |
author2_role |
author |
dc.contributor.author.fl_str_mv |
José Fernando Gonçalves Resende,MGC |
description |
This paper presents a biased random-key genetic algorithm (BRKGA) for the unequal area facility layout problem (UA-FLP) where a set of rectangular facilities with given area requirements has to be placed, without overlapping, on a rectangular floor space. The objective is to find the location and the dimensions of the facilities such that the sum of the weighted distances between the centroids of the facilities is minimized. A hybrid approach combining a BRKGA, to determine the order of placement and the dimensions of each facility, a novel placement strategy, to position each facility, and a linear programming model, to fine-tune the solutions, is developed. The proposed approach is tested on 100 random datasets and 28 of benchmark datasets taken from the literature and compared with 21 other benchmark approaches. The quality of the approach was validated by the improvement of the best known solutions for 19 of the 28 extensively studied benchmark datasets. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01-01T00:00:00Z 2015 2018-01-03T11:39:21Z |
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://repositorio.inesctec.pt/handle/123456789/5387 http://dx.doi.org/10.1016/j.ejor.2015.04.029 |
url |
http://repositorio.inesctec.pt/handle/123456789/5387 http://dx.doi.org/10.1016/j.ejor.2015.04.029 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799131607627464704 |