Multiobjective engineering design optimization problems: a sensitivity analysis approach
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa operacional (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382012000300006 |
Resumo: | This paper proposes two new approaches for the sensitivity analysis of multiobjective design optimization problems whose performance functions are highly susceptible to small variations in the design variables and/or design environment parameters. In both methods, the less sensitive design alternatives are preferred over others during the multiobjective optimization process. While taking the first approach, the designer chooses the design variable and/or parameter that causes uncertainties. The designer then associates a robustness index with each design alternative and adds each index as an objective function in the optimization problem. For the second approach, the designer must know, a priori, the interval of variation in the design variables or in the design environment parameters, because the designer will be accepting the interval of variation in the objective functions. The second method does not require any law of probability distribution of uncontrollable variations. Finally, the authors give two illustrative examples to highlight the contributions of the paper. |
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Multiobjective engineering design optimization problems: a sensitivity analysis approachmultiobjective optimizationPareto-optimal solutionssensitivity analysisThis paper proposes two new approaches for the sensitivity analysis of multiobjective design optimization problems whose performance functions are highly susceptible to small variations in the design variables and/or design environment parameters. In both methods, the less sensitive design alternatives are preferred over others during the multiobjective optimization process. While taking the first approach, the designer chooses the design variable and/or parameter that causes uncertainties. The designer then associates a robustness index with each design alternative and adds each index as an objective function in the optimization problem. For the second approach, the designer must know, a priori, the interval of variation in the design variables or in the design environment parameters, because the designer will be accepting the interval of variation in the objective functions. The second method does not require any law of probability distribution of uncontrollable variations. Finally, the authors give two illustrative examples to highlight the contributions of the paper.Sociedade Brasileira de Pesquisa Operacional2012-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382012000300006Pesquisa Operacional v.32 n.3 2012reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/S0101-74382012005000028info:eu-repo/semantics/openAccessAugusto,Oscar BritoBennis,FouadCaro,Stephaneeng2012-12-10T00:00:00Zoai:scielo:S0101-74382012000300006Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2012-12-10T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false |
dc.title.none.fl_str_mv |
Multiobjective engineering design optimization problems: a sensitivity analysis approach |
title |
Multiobjective engineering design optimization problems: a sensitivity analysis approach |
spellingShingle |
Multiobjective engineering design optimization problems: a sensitivity analysis approach Augusto,Oscar Brito multiobjective optimization Pareto-optimal solutions sensitivity analysis |
title_short |
Multiobjective engineering design optimization problems: a sensitivity analysis approach |
title_full |
Multiobjective engineering design optimization problems: a sensitivity analysis approach |
title_fullStr |
Multiobjective engineering design optimization problems: a sensitivity analysis approach |
title_full_unstemmed |
Multiobjective engineering design optimization problems: a sensitivity analysis approach |
title_sort |
Multiobjective engineering design optimization problems: a sensitivity analysis approach |
author |
Augusto,Oscar Brito |
author_facet |
Augusto,Oscar Brito Bennis,Fouad Caro,Stephane |
author_role |
author |
author2 |
Bennis,Fouad Caro,Stephane |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Augusto,Oscar Brito Bennis,Fouad Caro,Stephane |
dc.subject.por.fl_str_mv |
multiobjective optimization Pareto-optimal solutions sensitivity analysis |
topic |
multiobjective optimization Pareto-optimal solutions sensitivity analysis |
description |
This paper proposes two new approaches for the sensitivity analysis of multiobjective design optimization problems whose performance functions are highly susceptible to small variations in the design variables and/or design environment parameters. In both methods, the less sensitive design alternatives are preferred over others during the multiobjective optimization process. While taking the first approach, the designer chooses the design variable and/or parameter that causes uncertainties. The designer then associates a robustness index with each design alternative and adds each index as an objective function in the optimization problem. For the second approach, the designer must know, a priori, the interval of variation in the design variables or in the design environment parameters, because the designer will be accepting the interval of variation in the objective functions. The second method does not require any law of probability distribution of uncontrollable variations. Finally, the authors give two illustrative examples to highlight the contributions of the paper. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-12-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382012000300006 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382012000300006 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0101-74382012005000028 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Pesquisa Operacional |
publisher.none.fl_str_mv |
Sociedade Brasileira de Pesquisa Operacional |
dc.source.none.fl_str_mv |
Pesquisa Operacional v.32 n.3 2012 reponame:Pesquisa operacional (Online) instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) instacron:SOBRAPO |
instname_str |
Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) |
instacron_str |
SOBRAPO |
institution |
SOBRAPO |
reponame_str |
Pesquisa operacional (Online) |
collection |
Pesquisa operacional (Online) |
repository.name.fl_str_mv |
Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) |
repository.mail.fl_str_mv |
||sobrapo@sobrapo.org.br |
_version_ |
1750318017429897216 |