An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/27167 https://doi.org/10.1016/j.cad.2013.01.001 |
Resumo: | The drafting of floor plans is mostly hand made in today’s architectural design process. The use of computerized floor planning techniques may enhance the practitioner’s range of solutions and expedite the design process. However, despite the research work that has been carried out, the results obtained from these techniques do not convince many practitioners to accept them as part of their design methods. The existing literature shows that every research approach is different in the way in which architectural space planning is tackled. Consequently, each approach tends to be too specific or too abstract. The Space Allocation Problem in architecture may be stated as the process of determining the position and size of several rooms and openings according to the user’s specified design program requirements, and topological and geometric constraints in a two-dimensional space. This is the first part of a paper that describes an enhanced hybrid evolutionary computation scheme that couples an Evolutionary Strategy (ES) with a Stochastic Hill Climbing (SHC) technique to generate a set of floor plans to be used in the early design stages of architectural practice. It presents the mathematical model with the problem statement and how the individuals’ fitness is computed, the implemented methodological approach, how the adaptive operators are implemented, the summary of the overall procedure, and conclusions. |
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An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodologyEvolutionary strategyStochastic hill climbingSpace allocation problemSpace planningThe drafting of floor plans is mostly hand made in today’s architectural design process. The use of computerized floor planning techniques may enhance the practitioner’s range of solutions and expedite the design process. However, despite the research work that has been carried out, the results obtained from these techniques do not convince many practitioners to accept them as part of their design methods. The existing literature shows that every research approach is different in the way in which architectural space planning is tackled. Consequently, each approach tends to be too specific or too abstract. The Space Allocation Problem in architecture may be stated as the process of determining the position and size of several rooms and openings according to the user’s specified design program requirements, and topological and geometric constraints in a two-dimensional space. This is the first part of a paper that describes an enhanced hybrid evolutionary computation scheme that couples an Evolutionary Strategy (ES) with a Stochastic Hill Climbing (SHC) technique to generate a set of floor plans to be used in the early design stages of architectural practice. It presents the mathematical model with the problem statement and how the individuals’ fitness is computed, the implemented methodological approach, how the adaptive operators are implemented, the summary of the overall procedure, and conclusions.Elsevier2013-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/27167http://hdl.handle.net/10316/27167https://doi.org/10.1016/j.cad.2013.01.001engRODRIGUES, Eugénio; GASPAR, Adélio Rodrigues; GOMES, Álvaro - An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology. "Computer-Aided Design". ISSN 0010-4485. Vol. 45 Nº. 5 (2013) p. 887-8970010-4485http://www.sciencedirect.com/science/article/pii/S0010448513000031Rodrigues, EugénioGaspar, Adélio RodriguesGomes, Álvaroinfo: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:RCAAP2020-05-29T09:42:24Zoai:estudogeral.uc.pt:10316/27167Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:57:55.362326Repositório 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 |
An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology |
title |
An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology |
spellingShingle |
An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology Rodrigues, Eugénio Evolutionary strategy Stochastic hill climbing Space allocation problem Space planning |
title_short |
An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology |
title_full |
An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology |
title_fullStr |
An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology |
title_full_unstemmed |
An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology |
title_sort |
An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology |
author |
Rodrigues, Eugénio |
author_facet |
Rodrigues, Eugénio Gaspar, Adélio Rodrigues Gomes, Álvaro |
author_role |
author |
author2 |
Gaspar, Adélio Rodrigues Gomes, Álvaro |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Rodrigues, Eugénio Gaspar, Adélio Rodrigues Gomes, Álvaro |
dc.subject.por.fl_str_mv |
Evolutionary strategy Stochastic hill climbing Space allocation problem Space planning |
topic |
Evolutionary strategy Stochastic hill climbing Space allocation problem Space planning |
description |
The drafting of floor plans is mostly hand made in today’s architectural design process. The use of computerized floor planning techniques may enhance the practitioner’s range of solutions and expedite the design process. However, despite the research work that has been carried out, the results obtained from these techniques do not convince many practitioners to accept them as part of their design methods. The existing literature shows that every research approach is different in the way in which architectural space planning is tackled. Consequently, each approach tends to be too specific or too abstract. The Space Allocation Problem in architecture may be stated as the process of determining the position and size of several rooms and openings according to the user’s specified design program requirements, and topological and geometric constraints in a two-dimensional space. This is the first part of a paper that describes an enhanced hybrid evolutionary computation scheme that couples an Evolutionary Strategy (ES) with a Stochastic Hill Climbing (SHC) technique to generate a set of floor plans to be used in the early design stages of architectural practice. It presents the mathematical model with the problem statement and how the individuals’ fitness is computed, the implemented methodological approach, how the adaptive operators are implemented, the summary of the overall procedure, and conclusions. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-05 |
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/10316/27167 http://hdl.handle.net/10316/27167 https://doi.org/10.1016/j.cad.2013.01.001 |
url |
http://hdl.handle.net/10316/27167 https://doi.org/10.1016/j.cad.2013.01.001 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
RODRIGUES, Eugénio; GASPAR, Adélio Rodrigues; GOMES, Álvaro - An evolutionary strategy enhanced with a local search technique for the space allocation problem in architecture, Part 1: methodology. "Computer-Aided Design". ISSN 0010-4485. Vol. 45 Nº. 5 (2013) p. 887-897 0010-4485 http://www.sciencedirect.com/science/article/pii/S0010448513000031 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
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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1799133869328302080 |