A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis

Autores
Mroginski, Javier Luis; Beneyto, Pablo Alejandro; Gutierrez, Guillermo J; Di Rado, Hector Ariel
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Purpose-There are many problems in civil or mechanical engineering related to structural design. In such a case, the solution techniques which lead to deterministic results are no longer valid due to the heuristic nature of design problems. The purpose of this paper is to propose a computational tool based on genetic algorithms, applied to the optimal design of cross-sections (solid tubes) of 3D truss structures. Design/methodology/approach-The main feature of this genetic algorithm approach is the introduction of a selective-smart method developed in order to improve the convergence rate of large optimization problems. This selective genetic algorithm is based on a preliminary sensitivity analysis performed over each variable, in order to reduce the search space of the evolutionary process. In order to account for the optimization of the total weight, the displacement (of a specific section) and the internal stresses distribution of the structure a multiobjective optimization function was proposed. Findings-The numerical results presented in this paper show a significant improvement in the convergence rate as well as an important reduction in the relative error, compared to the exact solution. Originality/value-The variables sensitivity analysis put forward in this approach introduces a significant improvement in the convergence rate of the genetic algorithm proposed in this paper.
Fil: Mroginski, Javier Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Botánica del Nordeste. Universidad Nacional del Nordeste. Facultad de Ciencias Agrarias. Instituto de Botánica del Nordeste; Argentina
Fil: Beneyto, Pablo Alejandro. Universidad Nacional del Nordeste; Argentina
Fil: Gutierrez, Guillermo J. Universidad Nacional del Nordeste; Argentina
Fil: Di Rado, Hector Ariel. Universidad Nacional del Nordeste; Argentina
Materia
3d Bars Structure
Finite Element Method
Genetic Algorithm
Multiobjective Optimization
Sensitivity Analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/39457
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysisMroginski, Javier LuisBeneyto, Pablo AlejandroGutierrez, Guillermo JDi Rado, Hector Ariel3d Bars StructureFinite Element MethodGenetic AlgorithmMultiobjective OptimizationSensitivity Analysishttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Purpose-There are many problems in civil or mechanical engineering related to structural design. In such a case, the solution techniques which lead to deterministic results are no longer valid due to the heuristic nature of design problems. The purpose of this paper is to propose a computational tool based on genetic algorithms, applied to the optimal design of cross-sections (solid tubes) of 3D truss structures. Design/methodology/approach-The main feature of this genetic algorithm approach is the introduction of a selective-smart method developed in order to improve the convergence rate of large optimization problems. This selective genetic algorithm is based on a preliminary sensitivity analysis performed over each variable, in order to reduce the search space of the evolutionary process. In order to account for the optimization of the total weight, the displacement (of a specific section) and the internal stresses distribution of the structure a multiobjective optimization function was proposed. Findings-The numerical results presented in this paper show a significant improvement in the convergence rate as well as an important reduction in the relative error, compared to the exact solution. Originality/value-The variables sensitivity analysis put forward in this approach introduces a significant improvement in the convergence rate of the genetic algorithm proposed in this paper.Fil: Mroginski, Javier Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Botánica del Nordeste. Universidad Nacional del Nordeste. Facultad de Ciencias Agrarias. Instituto de Botánica del Nordeste; ArgentinaFil: Beneyto, Pablo Alejandro. Universidad Nacional del Nordeste; ArgentinaFil: Gutierrez, Guillermo J. Universidad Nacional del Nordeste; ArgentinaFil: Di Rado, Hector Ariel. Universidad Nacional del Nordeste; ArgentinaEmerald2016-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/39457Mroginski, Javier Luis; Beneyto, Pablo Alejandro; Gutierrez, Guillermo J; Di Rado, Hector Ariel; A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis; Emerald; Multidiscipline Modeling in Materials and Structures; 12; 2; 1-2016; 423-4351573-6105CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1108/MMMS-08-2015-0048info:eu-repo/semantics/altIdentifier/url/https://www.emeraldinsight.com/doi/abs/10.1108/MMMS-08-2015-0048info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:37:28Zoai:ri.conicet.gov.ar:11336/39457instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:37:28.69CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis
title A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis
spellingShingle A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis
Mroginski, Javier Luis
3d Bars Structure
Finite Element Method
Genetic Algorithm
Multiobjective Optimization
Sensitivity Analysis
title_short A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis
title_full A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis
title_fullStr A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis
title_full_unstemmed A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis
title_sort A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis
dc.creator.none.fl_str_mv Mroginski, Javier Luis
Beneyto, Pablo Alejandro
Gutierrez, Guillermo J
Di Rado, Hector Ariel
author Mroginski, Javier Luis
author_facet Mroginski, Javier Luis
Beneyto, Pablo Alejandro
Gutierrez, Guillermo J
Di Rado, Hector Ariel
author_role author
author2 Beneyto, Pablo Alejandro
Gutierrez, Guillermo J
Di Rado, Hector Ariel
author2_role author
author
author
dc.subject.none.fl_str_mv 3d Bars Structure
Finite Element Method
Genetic Algorithm
Multiobjective Optimization
Sensitivity Analysis
topic 3d Bars Structure
Finite Element Method
Genetic Algorithm
Multiobjective Optimization
Sensitivity Analysis
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Purpose-There are many problems in civil or mechanical engineering related to structural design. In such a case, the solution techniques which lead to deterministic results are no longer valid due to the heuristic nature of design problems. The purpose of this paper is to propose a computational tool based on genetic algorithms, applied to the optimal design of cross-sections (solid tubes) of 3D truss structures. Design/methodology/approach-The main feature of this genetic algorithm approach is the introduction of a selective-smart method developed in order to improve the convergence rate of large optimization problems. This selective genetic algorithm is based on a preliminary sensitivity analysis performed over each variable, in order to reduce the search space of the evolutionary process. In order to account for the optimization of the total weight, the displacement (of a specific section) and the internal stresses distribution of the structure a multiobjective optimization function was proposed. Findings-The numerical results presented in this paper show a significant improvement in the convergence rate as well as an important reduction in the relative error, compared to the exact solution. Originality/value-The variables sensitivity analysis put forward in this approach introduces a significant improvement in the convergence rate of the genetic algorithm proposed in this paper.
Fil: Mroginski, Javier Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Botánica del Nordeste. Universidad Nacional del Nordeste. Facultad de Ciencias Agrarias. Instituto de Botánica del Nordeste; Argentina
Fil: Beneyto, Pablo Alejandro. Universidad Nacional del Nordeste; Argentina
Fil: Gutierrez, Guillermo J. Universidad Nacional del Nordeste; Argentina
Fil: Di Rado, Hector Ariel. Universidad Nacional del Nordeste; Argentina
description Purpose-There are many problems in civil or mechanical engineering related to structural design. In such a case, the solution techniques which lead to deterministic results are no longer valid due to the heuristic nature of design problems. The purpose of this paper is to propose a computational tool based on genetic algorithms, applied to the optimal design of cross-sections (solid tubes) of 3D truss structures. Design/methodology/approach-The main feature of this genetic algorithm approach is the introduction of a selective-smart method developed in order to improve the convergence rate of large optimization problems. This selective genetic algorithm is based on a preliminary sensitivity analysis performed over each variable, in order to reduce the search space of the evolutionary process. In order to account for the optimization of the total weight, the displacement (of a specific section) and the internal stresses distribution of the structure a multiobjective optimization function was proposed. Findings-The numerical results presented in this paper show a significant improvement in the convergence rate as well as an important reduction in the relative error, compared to the exact solution. Originality/value-The variables sensitivity analysis put forward in this approach introduces a significant improvement in the convergence rate of the genetic algorithm proposed in this paper.
publishDate 2016
dc.date.none.fl_str_mv 2016-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/39457
Mroginski, Javier Luis; Beneyto, Pablo Alejandro; Gutierrez, Guillermo J; Di Rado, Hector Ariel; A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis; Emerald; Multidiscipline Modeling in Materials and Structures; 12; 2; 1-2016; 423-435
1573-6105
CONICET Digital
CONICET
url http://hdl.handle.net/11336/39457
identifier_str_mv Mroginski, Javier Luis; Beneyto, Pablo Alejandro; Gutierrez, Guillermo J; Di Rado, Hector Ariel; A selective genetic algorithm for multiobjective optimization of cross sections in 3D trussed structures based on a spatial sensitivity analysis; Emerald; Multidiscipline Modeling in Materials and Structures; 12; 2; 1-2016; 423-435
1573-6105
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1108/MMMS-08-2015-0048
info:eu-repo/semantics/altIdentifier/url/https://www.emeraldinsight.com/doi/abs/10.1108/MMMS-08-2015-0048
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Emerald
publisher.none.fl_str_mv Emerald
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.069144

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