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Multiobjective optimization of polymer extrusion: decision making and robustness

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Resumo:A Multi-Objective Evolutionary Algorithm (MOEA) is used to optimize polymer single screw extrusion. In this approach, the MOEA is linked to a modelling routine that quantifies the objectives as a function of the decision variables (i.e., operating conditions and/or screw geometry). Due to the conflicting nature of some objectives, the optimization algorithm uses a set of possible solutions to the problem that evolves during suc-cessive generations to a set of optimal solutions denoted as Pareto set. Since practical process optimization should yield a single solution, it is convenient to implement also a Decision Making (DM) strategy. Two methodologies were followed. In one case, the solutions were selected based on the preferences of a decision maker. Alternatively, the sensitivity of the solutions to small changes in the design variables was taken into account through a robustness analysis. The analysis of various case studies and the comparison with experi-mental data validated the method and demonstrates its potential.
Autores principais:Gaspar-Cunha, A.
Outros Autores:Covas, J. A.; Denysiuk, Roman; Recio, Gustavo
Assunto:Optimization Extrusion
Ano:2016
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
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author Gaspar-Cunha, A.
author2 Covas, J. A.
Denysiuk, Roman
Recio, Gustavo
author2_role author
author
author
author_facet Gaspar-Cunha, A.
Covas, J. A.
Denysiuk, Roman
Recio, Gustavo
author_role author
contributor_name_str_mv Universidade do Minho
country_str PT
creators_json_txt [{\"Person.name\":\"Gaspar-Cunha, A.\"},{\"Person.name\":\"Covas, J. A.\"},{\"Person.name\":\"Denysiuk, Roman\"},{\"Person.name\":\"Recio, Gustavo\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Universidade do Minho
datacite.creators.creator.creatorName.fl_str_mv Gaspar-Cunha, A.
Covas, J. A.
Denysiuk, Roman
Recio, Gustavo
datacite.date.Accepted.fl_str_mv 2016-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2018-03-27T08:37:50Z
datacite.date.embargoed.fl_str_mv 2018-03-27T08:37:50Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Optimization
Extrusion
datacite.titles.title.fl_str_mv Multiobjective optimization of polymer extrusion: decision making and robustness
dc.contributor.none.fl_str_mv Universidade do Minho
dc.creator.none.fl_str_mv Gaspar-Cunha, A.
Covas, J. A.
Denysiuk, Roman
Recio, Gustavo
dc.date.Accepted.fl_str_mv 2016-01-01T00:00:00Z
dc.date.available.fl_str_mv 2018-03-27T08:37:50Z
dc.date.embargoed.fl_str_mv 2018-03-27T08:37:50Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://hdl.handle.net/1822/53522
dc.language.none.fl_str_mv eng
dc.rights.cclincense.fl_str_mv http://creativecommons.org/licenses/by/4.0/
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.rights.copyright.fl_str_mv openAccess
dc.subject.none.fl_str_mv Optimization
Extrusion
dc.title.fl_str_mv Multiobjective optimization of polymer extrusion: decision making and robustness
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_5794
description A Multi-Objective Evolutionary Algorithm (MOEA) is used to optimize polymer single screw extrusion. In this approach, the MOEA is linked to a modelling routine that quantifies the objectives as a function of the decision variables (i.e., operating conditions and/or screw geometry). Due to the conflicting nature of some objectives, the optimization algorithm uses a set of possible solutions to the problem that evolves during suc-cessive generations to a set of optimal solutions denoted as Pareto set. Since practical process optimization should yield a single solution, it is convenient to implement also a Decision Making (DM) strategy. Two methodologies were followed. In one case, the solutions were selected based on the preferences of a decision maker. Alternatively, the sensitivity of the solutions to small changes in the design variables was taken into account through a robustness analysis. The analysis of various case studies and the comparison with experi-mental data validated the method and demonstrates its potential.
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eu_rights_str_mv openAccess
format conferencePaper
fulltext.url.fl_str_mv https://prod-dspace.uminho.pt/bitstreams/df9bf816-7f28-4d38-9ddc-8ff528f97185/download
id rum_7ca4e0c571f04410091c37a9999c8dad
identifier.url.fl_str_mv https://hdl.handle.net/1822/53522
instacron_str repositorium
institution Universidade do Minho
instname_str Universidade do Minho
language eng
network_acronym_str rum
network_name_str RepositóriUM - Universidade do Minho
oai_identifier_str oai:repositorium.uminho.pt:1822/53522
organization_str_mv urn:organizationAcronym:repositorium
person_str_mv Gaspar-Cunha, A.
Covas, J. A.
Denysiuk, Roman
Recio, Gustavo
publishDate 2016
reponame_str RepositóriUM - Universidade do Minho
repository_id_str urn:repositoryAcronym:rum
service_str_mv urn:repositoryAcronym:rum
spelling engporA Multi-Objective Evolutionary Algorithm (MOEA) is used to optimize polymer single screw extrusion. In this approach, the MOEA is linked to a modelling routine that quantifies the objectives as a function of the decision variables (i.e., operating conditions and/or screw geometry). Due to the conflicting nature of some objectives, the optimization algorithm uses a set of possible solutions to the problem that evolves during suc-cessive generations to a set of optimal solutions denoted as Pareto set. Since practical process optimization should yield a single solution, it is convenient to implement also a Decision Making (DM) strategy. Two methodologies were followed. In one case, the solutions were selected based on the preferences of a decision maker. Alternatively, the sensitivity of the solutions to small changes in the design variables was taken into account through a robustness analysis. The analysis of various case studies and the comparison with experi-mental data validated the method and demonstrates its potential.application/pdfporMultiobjective optimization of polymer extrusion: decision making and robustnessGaspar-Cunha, A.Covas, J. A.Denysiuk, RomanRecio, GustavoHostingInstitutionOrganizationalUniversidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.pt2018-03-27T08:37:50Z20162016-01-01T00:00:00ZHandlehttps://hdl.handle.net/1822/53522http://purl.org/coar/access_right/c_abf2open accessOptimizationExtrusion562836 bytesother research producthttp://purl.org/coar/resource_type/c_5794conference paper2016http://creativecommons.org/licenses/by/4.0/openAccesshttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://prod-dspace.uminho.pt/bitstreams/df9bf816-7f28-4d38-9ddc-8ff528f97185/download
spellingShingle Multiobjective optimization of polymer extrusion: decision making and robustness
Gaspar-Cunha, A.
Optimization
Extrusion
status SINGLETON
subject.fl_str_mv Optimization
Extrusion
title Multiobjective optimization of polymer extrusion: decision making and robustness
title_full Multiobjective optimization of polymer extrusion: decision making and robustness
title_fullStr Multiobjective optimization of polymer extrusion: decision making and robustness
title_full_unstemmed Multiobjective optimization of polymer extrusion: decision making and robustness
title_short Multiobjective optimization of polymer extrusion: decision making and robustness
title_sort Multiobjective optimization of polymer extrusion: decision making and robustness
topic Optimization
Extrusion
topic_facet Optimization
Extrusion
url https://hdl.handle.net/1822/53522
visible 1