A penalty method and a regularization strategy to solve MPCC
Autor(a) principal: | |
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Data de Publicação: | 2011 |
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/1822/15436 |
Resumo: | The goal of this paper is to solve mathematical programme with complementarity constraints using nonlinear programming techniques. This work presents two algorithms based on several nonlinear techniques such as sequential quadratic programming, penalty techniques and regularization schemes. A set of AMPL (A Modeling Language for Mathematical Programming) problems were tested and the computational experience shows that both algorithms are effective. |
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A penalty method and a regularization strategy to solve MPCCMPCCSQPpenalty techniqueregularization schemeScience & TechnologyThe goal of this paper is to solve mathematical programme with complementarity constraints using nonlinear programming techniques. This work presents two algorithms based on several nonlinear techniques such as sequential quadratic programming, penalty techniques and regularization schemes. A set of AMPL (A Modeling Language for Mathematical Programming) problems were tested and the computational experience shows that both algorithms are effective.Fundação para a Ciência e a Tecnologia (FCT)Taylor and FrancisUniversidade do MinhoMonteiro, M. Teresa T.Meira, José Filipe P.2011-012011-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/15436eng0020-716010.1080/00207160903349580https://www.tandfonline.com/doi/abs/10.1080/00207160903349580info: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:RCAAP2023-07-21T12:36:24Zoai:repositorium.sdum.uminho.pt:1822/15436Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:32:30.245085Repositório 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 penalty method and a regularization strategy to solve MPCC |
title |
A penalty method and a regularization strategy to solve MPCC |
spellingShingle |
A penalty method and a regularization strategy to solve MPCC Monteiro, M. Teresa T. MPCC SQP penalty technique regularization scheme Science & Technology |
title_short |
A penalty method and a regularization strategy to solve MPCC |
title_full |
A penalty method and a regularization strategy to solve MPCC |
title_fullStr |
A penalty method and a regularization strategy to solve MPCC |
title_full_unstemmed |
A penalty method and a regularization strategy to solve MPCC |
title_sort |
A penalty method and a regularization strategy to solve MPCC |
author |
Monteiro, M. Teresa T. |
author_facet |
Monteiro, M. Teresa T. Meira, José Filipe P. |
author_role |
author |
author2 |
Meira, José Filipe P. |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Monteiro, M. Teresa T. Meira, José Filipe P. |
dc.subject.por.fl_str_mv |
MPCC SQP penalty technique regularization scheme Science & Technology |
topic |
MPCC SQP penalty technique regularization scheme Science & Technology |
description |
The goal of this paper is to solve mathematical programme with complementarity constraints using nonlinear programming techniques. This work presents two algorithms based on several nonlinear techniques such as sequential quadratic programming, penalty techniques and regularization schemes. A set of AMPL (A Modeling Language for Mathematical Programming) problems were tested and the computational experience shows that both algorithms are effective. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-01 2011-01-01T00:00:00Z |
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/1822/15436 |
url |
http://hdl.handle.net/1822/15436 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0020-7160 10.1080/00207160903349580 https://www.tandfonline.com/doi/abs/10.1080/00207160903349580 |
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.publisher.none.fl_str_mv |
Taylor and Francis |
publisher.none.fl_str_mv |
Taylor and Francis |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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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 |
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1799132837148884992 |