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 In such a case, the solution techniques which lead to deterministic results are no longer valid due to the heuristic nature of design problems.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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/39457
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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 Técnicas2025-09-03T09:46:21Zoai: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:34982025-09-03 09:46:21.711CONICET 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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1842268789491630080 |
score |
13.13397 |