Parameter estimation of the kinetic α-Pinene isomerization model using the MCSfilter algorithm

Detalhes bibliográficos
Autor(a) principal: Amador, Andreia
Data de Publicação: 2018
Outros Autores: Fernandes, Florbela P., Santos, Lino O., Romanenko, Andrey, Rocha, Ana Maria A. C.
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/1822/57913
Resumo: This paper aims to illustrate the application of a derivative-free multistart algorithm with coordinate search filter, designated as the MCSFilter algorithm. The problem used in this study is the parameter estimation problem of the kinetic α -pinene isomerization model. This is a well known nonlinear optimization problem (NLP) that has been investigated as a case study for performance testing of most derivative based methods proposed in the literature. Since the MCSFilter algorithm features a stochastic component, it was run ten times to solve the NLP problem. The optimization problem was successfully solved in all the runs and the optimal solution demonstrates that the MCSFilter provides a good quality solution.
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spelling Parameter estimation of the kinetic α-Pinene isomerization model using the MCSfilter algorithmDerivative-free optimizationMCSFilterMultistartα-Pinene isomerization modelScience & TechnologyThis paper aims to illustrate the application of a derivative-free multistart algorithm with coordinate search filter, designated as the MCSFilter algorithm. The problem used in this study is the parameter estimation problem of the kinetic α -pinene isomerization model. This is a well known nonlinear optimization problem (NLP) that has been investigated as a case study for performance testing of most derivative based methods proposed in the literature. Since the MCSFilter algorithm features a stochastic component, it was run ten times to solve the NLP problem. The optimization problem was successfully solved in all the runs and the optimal solution demonstrates that the MCSFilter provides a good quality solution.(undefined)info:eu-repo/semantics/publishedVersionSpringerUniversidade do MinhoAmador, AndreiaFernandes, Florbela P.Santos, Lino O.Romanenko, AndreyRocha, Ana Maria A. C.20182018-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/57913eng97833199516450302-974310.1007/978-3-319-95165-2_44info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:22:26Zoai:repositorium.sdum.uminho.pt:1822/57913Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:24:54.216457Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Parameter estimation of the kinetic α-Pinene isomerization model using the MCSfilter algorithm
title Parameter estimation of the kinetic α-Pinene isomerization model using the MCSfilter algorithm
spellingShingle Parameter estimation of the kinetic α-Pinene isomerization model using the MCSfilter algorithm
Amador, Andreia
Derivative-free optimization
MCSFilter
Multistart
α-Pinene isomerization model
Science & Technology
title_short Parameter estimation of the kinetic α-Pinene isomerization model using the MCSfilter algorithm
title_full Parameter estimation of the kinetic α-Pinene isomerization model using the MCSfilter algorithm
title_fullStr Parameter estimation of the kinetic α-Pinene isomerization model using the MCSfilter algorithm
title_full_unstemmed Parameter estimation of the kinetic α-Pinene isomerization model using the MCSfilter algorithm
title_sort Parameter estimation of the kinetic α-Pinene isomerization model using the MCSfilter algorithm
author Amador, Andreia
author_facet Amador, Andreia
Fernandes, Florbela P.
Santos, Lino O.
Romanenko, Andrey
Rocha, Ana Maria A. C.
author_role author
author2 Fernandes, Florbela P.
Santos, Lino O.
Romanenko, Andrey
Rocha, Ana Maria A. C.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Amador, Andreia
Fernandes, Florbela P.
Santos, Lino O.
Romanenko, Andrey
Rocha, Ana Maria A. C.
dc.subject.por.fl_str_mv Derivative-free optimization
MCSFilter
Multistart
α-Pinene isomerization model
Science & Technology
topic Derivative-free optimization
MCSFilter
Multistart
α-Pinene isomerization model
Science & Technology
description This paper aims to illustrate the application of a derivative-free multistart algorithm with coordinate search filter, designated as the MCSFilter algorithm. The problem used in this study is the parameter estimation problem of the kinetic α -pinene isomerization model. This is a well known nonlinear optimization problem (NLP) that has been investigated as a case study for performance testing of most derivative based methods proposed in the literature. Since the MCSFilter algorithm features a stochastic component, it was run ten times to solve the NLP problem. The optimization problem was successfully solved in all the runs and the optimal solution demonstrates that the MCSFilter provides a good quality solution.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/57913
url http://hdl.handle.net/1822/57913
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 9783319951645
0302-9743
10.1007/978-3-319-95165-2_44
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 Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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