Inclusion of information costs in process design optimization under uncertainty
Autor(a) principal: | |
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Data de Publicação: | 2000 |
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/10316/3834 https://doi.org/10.1016/S0098-1354(00)00457-9 |
Resumo: | Recent developments in process design have focused on establishing optimization-based approaches to support decision-making under uncertainty, but few efforts have been made to study and consider how information regarding this uncertainty affects optimal decision. In this paper we develop an optimal design framework that, besides integrating process profitability, robustness and quality issues, allows one to decide how much it is worth to spend in research and experimentation for selectively reducing parameter uncertainties and guiding R&D activities. The design problem is thus formulated as a stochastic optimization problem, whose objective function includes an information cost term, leading to the identification of optimal parameter uncertainty levels one should end up with, as well as the corresponding amounts to be spent in R&D. A case study comprising a reactor and heart exchanger system is introduced and provides an illustrative application for the suggested methodology. |
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Inclusion of information costs in process design optimization under uncertaintyStochastic process designUncertaintyValue of informationR&D economicsRecent developments in process design have focused on establishing optimization-based approaches to support decision-making under uncertainty, but few efforts have been made to study and consider how information regarding this uncertainty affects optimal decision. In this paper we develop an optimal design framework that, besides integrating process profitability, robustness and quality issues, allows one to decide how much it is worth to spend in research and experimentation for selectively reducing parameter uncertainties and guiding R&D activities. The design problem is thus formulated as a stochastic optimization problem, whose objective function includes an information cost term, leading to the identification of optimal parameter uncertainty levels one should end up with, as well as the corresponding amounts to be spent in R&D. A case study comprising a reactor and heart exchanger system is introduced and provides an illustrative application for the suggested methodology.http://www.sciencedirect.com/science/article/B6TFT-448HNR0-80/1/6d7a6dc558dcacffcefc4d8b3d6500592000info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleaplication/PDFhttp://hdl.handle.net/10316/3834http://hdl.handle.net/10316/3834https://doi.org/10.1016/S0098-1354(00)00457-9engComputers & Chemical Engineering. 24:2-7 (2000) 1695-1701Bernardo, Fernando P.Saraiva, PedroEfstratios, Pistikopoulos N.info: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:RCAAP2021-10-12T12:24:40Zoai:estudogeral.uc.pt:10316/3834Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:59:16.600866Repositório 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 |
Inclusion of information costs in process design optimization under uncertainty |
title |
Inclusion of information costs in process design optimization under uncertainty |
spellingShingle |
Inclusion of information costs in process design optimization under uncertainty Bernardo, Fernando P. Stochastic process design Uncertainty Value of information R&D economics |
title_short |
Inclusion of information costs in process design optimization under uncertainty |
title_full |
Inclusion of information costs in process design optimization under uncertainty |
title_fullStr |
Inclusion of information costs in process design optimization under uncertainty |
title_full_unstemmed |
Inclusion of information costs in process design optimization under uncertainty |
title_sort |
Inclusion of information costs in process design optimization under uncertainty |
author |
Bernardo, Fernando P. |
author_facet |
Bernardo, Fernando P. Saraiva, Pedro Efstratios, Pistikopoulos N. |
author_role |
author |
author2 |
Saraiva, Pedro Efstratios, Pistikopoulos N. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Bernardo, Fernando P. Saraiva, Pedro Efstratios, Pistikopoulos N. |
dc.subject.por.fl_str_mv |
Stochastic process design Uncertainty Value of information R&D economics |
topic |
Stochastic process design Uncertainty Value of information R&D economics |
description |
Recent developments in process design have focused on establishing optimization-based approaches to support decision-making under uncertainty, but few efforts have been made to study and consider how information regarding this uncertainty affects optimal decision. In this paper we develop an optimal design framework that, besides integrating process profitability, robustness and quality issues, allows one to decide how much it is worth to spend in research and experimentation for selectively reducing parameter uncertainties and guiding R&D activities. The design problem is thus formulated as a stochastic optimization problem, whose objective function includes an information cost term, leading to the identification of optimal parameter uncertainty levels one should end up with, as well as the corresponding amounts to be spent in R&D. A case study comprising a reactor and heart exchanger system is introduced and provides an illustrative application for the suggested methodology. |
publishDate |
2000 |
dc.date.none.fl_str_mv |
2000 |
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/10316/3834 http://hdl.handle.net/10316/3834 https://doi.org/10.1016/S0098-1354(00)00457-9 |
url |
http://hdl.handle.net/10316/3834 https://doi.org/10.1016/S0098-1354(00)00457-9 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Computers & Chemical Engineering. 24:2-7 (2000) 1695-1701 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
aplication/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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1799133884093300736 |