Hybrid simulation-optimization methods: A taxonomy and discussion

Detalhes bibliográficos
Autor(a) principal: Gonçalo Reis Figueira
Data de Publicação: 2014
Outros Autores: Bernardo Almada-Lobo
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/123456789/5682
http://dx.doi.org/10.1016/j.simpat.2014.03.007
Resumo: The possibilities of combining simulation and optimization are vast and the appropriate design highly depends on the problem characteristics. Therefore, it is very important to have a good overview of the different approaches. The taxonomies and classifications proposed in the literature do not cover the complete range of methods and overlook some important criteria. We provide a taxonomy that aims at giving an overview of the full spectrum of current simulation-optimization approaches. Our study may guide researchers who want to use one of the existing methods, give insights into the cross-fertilization of the ideas applied in those methods and create a standard for a better communication in the scientific community. Future reviews can use the taxonomy here described to classify both general approaches and methods for specific application fields.
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spelling Hybrid simulation-optimization methods: A taxonomy and discussionThe possibilities of combining simulation and optimization are vast and the appropriate design highly depends on the problem characteristics. Therefore, it is very important to have a good overview of the different approaches. The taxonomies and classifications proposed in the literature do not cover the complete range of methods and overlook some important criteria. We provide a taxonomy that aims at giving an overview of the full spectrum of current simulation-optimization approaches. Our study may guide researchers who want to use one of the existing methods, give insights into the cross-fertilization of the ideas applied in those methods and create a standard for a better communication in the scientific community. Future reviews can use the taxonomy here described to classify both general approaches and methods for specific application fields.2018-01-08T09:13:38Z2014-01-01T00:00:00Z2014info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/5682http://dx.doi.org/10.1016/j.simpat.2014.03.007engGonçalo Reis FigueiraBernardo Almada-Loboinfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:36Zoai:repositorio.inesctec.pt:123456789/5682Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:22.303793Repositório 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 Hybrid simulation-optimization methods: A taxonomy and discussion
title Hybrid simulation-optimization methods: A taxonomy and discussion
spellingShingle Hybrid simulation-optimization methods: A taxonomy and discussion
Gonçalo Reis Figueira
title_short Hybrid simulation-optimization methods: A taxonomy and discussion
title_full Hybrid simulation-optimization methods: A taxonomy and discussion
title_fullStr Hybrid simulation-optimization methods: A taxonomy and discussion
title_full_unstemmed Hybrid simulation-optimization methods: A taxonomy and discussion
title_sort Hybrid simulation-optimization methods: A taxonomy and discussion
author Gonçalo Reis Figueira
author_facet Gonçalo Reis Figueira
Bernardo Almada-Lobo
author_role author
author2 Bernardo Almada-Lobo
author2_role author
dc.contributor.author.fl_str_mv Gonçalo Reis Figueira
Bernardo Almada-Lobo
description The possibilities of combining simulation and optimization are vast and the appropriate design highly depends on the problem characteristics. Therefore, it is very important to have a good overview of the different approaches. The taxonomies and classifications proposed in the literature do not cover the complete range of methods and overlook some important criteria. We provide a taxonomy that aims at giving an overview of the full spectrum of current simulation-optimization approaches. Our study may guide researchers who want to use one of the existing methods, give insights into the cross-fertilization of the ideas applied in those methods and create a standard for a better communication in the scientific community. Future reviews can use the taxonomy here described to classify both general approaches and methods for specific application fields.
publishDate 2014
dc.date.none.fl_str_mv 2014-01-01T00:00:00Z
2014
2018-01-08T09:13:38Z
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http://dx.doi.org/10.1016/j.simpat.2014.03.007
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http://dx.doi.org/10.1016/j.simpat.2014.03.007
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