A biased random-key genetic algorithm for the unequal area facility layout problem

Detalhes bibliográficos
Autor(a) principal: José Fernando Gonçalves
Data de Publicação: 2015
Outros Autores: Resende,MGC
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.
id RCAP_b9626f898e150542eae3e3d94df809d8
oai_identifier_str oai:repositorio.inesctec.pt:123456789/5387
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling 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
_version_ 1799131607627464704