Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem

Autores
Casanova Pietroboni, Carlos Antonio; Schab, Esteban Alejandro; Prado, Lucas Martín; Rottoli, Giovani Daian
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
When solving multi-objective combinatorial optimization problems using a search algorithm without a priori information, the result is a Pareto front. Selecting a solution from it is a laborious task if the number of solutions to be analyzed is large. This task would benefit from a systematic approach that facilitates the analysis, comparison and selection of a solution or a group of solutions based on the preferences of the decision makers. In the last decade, the research and development of algorithms for solving multi-objective combinatorial optimization problems has been growing steadily. In contrast, efforts in the a posteriori exploration of non-dominated solutions are still scarce.
Fil: Casanova Pietroboni, Carlos Antonio. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.
Fil: Schab, Esteban Alejandro. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.
Fil: Prado, Lucas Martín. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.
Fil: Rottoli, Giovanni Daián. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.
Fuente
Frontiers in Computer Science, Sci. 5:1179059, 1-18. (2023)
Materia
Search-based software engineering
Preference-based algorithms
Aposteriori approach
Hierarchical clustering
Multiobjective optimization
Pareto front
Nivel de accesibilidad
acceso abierto
Condiciones de uso
Attribution-NonCommercial-NoDerivatives 4.0 International
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/12046
Acceder
id RIAUTN_20214971836c015b4ca2d008c5f178d2
oai_identifier_str oai:ria.utn.edu.ar:20.500.12272/12046
network_acronym_str RIAUTN
repository_id_str a
network_name_str Repositorio Institucional Abierto (UTN)
spelling Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problemCasanova Pietroboni, Carlos AntonioSchab, Esteban AlejandroPrado, Lucas MartínRottoli, Giovani DaianSearch-based software engineeringPreference-based algorithmsAposteriori approachHierarchical clusteringMultiobjective optimizationPareto frontWhen solving multi-objective combinatorial optimization problems using a search algorithm without a priori information, the result is a Pareto front. Selecting a solution from it is a laborious task if the number of solutions to be analyzed is large. This task would benefit from a systematic approach that facilitates the analysis, comparison and selection of a solution or a group of solutions based on the preferences of the decision makers. In the last decade, the research and development of algorithms for solving multi-objective combinatorial optimization problems has been growing steadily. In contrast, efforts in the a posteriori exploration of non-dominated solutions are still scarce.Fil: Casanova Pietroboni, Carlos Antonio. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.Fil: Schab, Esteban Alejandro. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.Fil: Prado, Lucas Martín. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.Fil: Rottoli, Giovanni Daián. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.Hector Florez, Universidad Distrital Francisco Jose de Caldas, Colombia.2024-12-27T14:10:44Z2023-05-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulopdfapplication/pdfFrontiers in computer sciencehttp://hdl.handle.net/20.500.12272/12046https://doi.org/10.3389/fcomp.2023.1179059Frontiers in Computer Science, Sci. 5:1179059, 1-18. (2023)reponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacionalenginfo:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Casanova Pietroboni, Carlos Antonio ; Schab, Esteban Alejandro ; Prado, Lucas Martín ; Rottoli, Giovanni Daián.No comercial con fines académicos. Licencia Creative Commons CC BY.2026-10-01T11:58:27Zoai:ria.utn.edu.ar:20.500.12272/12046instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-10-01 11:58:27.843Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
dc.title.none.fl_str_mv Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem
title Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem
spellingShingle Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem
Casanova Pietroboni, Carlos Antonio
Search-based software engineering
Preference-based algorithms
Aposteriori approach
Hierarchical clustering
Multiobjective optimization
Pareto front
title_short Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem
title_full Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem
title_fullStr Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem
title_full_unstemmed Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem
title_sort Hierarchical clustering-based framework for a posteriori exploration of pareto fronts : application on the bi-objective next release problem
dc.creator.none.fl_str_mv Casanova Pietroboni, Carlos Antonio
Schab, Esteban Alejandro
Prado, Lucas Martín
Rottoli, Giovani Daian
author Casanova Pietroboni, Carlos Antonio
author_facet Casanova Pietroboni, Carlos Antonio
Schab, Esteban Alejandro
Prado, Lucas Martín
Rottoli, Giovani Daian
author_role author
author2 Schab, Esteban Alejandro
Prado, Lucas Martín
Rottoli, Giovani Daian
author2_role author
author
author
dc.subject.none.fl_str_mv Search-based software engineering
Preference-based algorithms
Aposteriori approach
Hierarchical clustering
Multiobjective optimization
Pareto front
topic Search-based software engineering
Preference-based algorithms
Aposteriori approach
Hierarchical clustering
Multiobjective optimization
Pareto front
dc.description.none.fl_txt_mv When solving multi-objective combinatorial optimization problems using a search algorithm without a priori information, the result is a Pareto front. Selecting a solution from it is a laborious task if the number of solutions to be analyzed is large. This task would benefit from a systematic approach that facilitates the analysis, comparison and selection of a solution or a group of solutions based on the preferences of the decision makers. In the last decade, the research and development of algorithms for solving multi-objective combinatorial optimization problems has been growing steadily. In contrast, efforts in the a posteriori exploration of non-dominated solutions are still scarce.
Fil: Casanova Pietroboni, Carlos Antonio. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.
Fil: Schab, Esteban Alejandro. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.
Fil: Prado, Lucas Martín. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.
Fil: Rottoli, Giovanni Daián. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay. Departamento Ingeniería en Sistemas de Información. Grupo de Investigación Inteligencia Computacional e Ingeniería de Software; Argentina.
description When solving multi-objective combinatorial optimization problems using a search algorithm without a priori information, the result is a Pareto front. Selecting a solution from it is a laborious task if the number of solutions to be analyzed is large. This task would benefit from a systematic approach that facilitates the analysis, comparison and selection of a solution or a group of solutions based on the preferences of the decision makers. In the last decade, the research and development of algorithms for solving multi-objective combinatorial optimization problems has been growing steadily. In contrast, efforts in the a posteriori exploration of non-dominated solutions are still scarce.
publishDate 2023
dc.date.none.fl_str_mv 2023-05-24
2024-12-27T14:10:44Z
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 Frontiers in computer science
http://hdl.handle.net/20.500.12272/12046
https://doi.org/10.3389/fcomp.2023.1179059
identifier_str_mv Frontiers in computer science
url http://hdl.handle.net/20.500.12272/12046
https://doi.org/10.3389/fcomp.2023.1179059
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
Casanova Pietroboni, Carlos Antonio ; Schab, Esteban Alejandro ; Prado, Lucas Martín ; Rottoli, Giovanni Daián.
No comercial con fines académicos. Licencia Creative Commons CC BY.
eu_rights_str_mv openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
Casanova Pietroboni, Carlos Antonio ; Schab, Esteban Alejandro ; Prado, Lucas Martín ; Rottoli, Giovanni Daián.
No comercial con fines académicos. Licencia Creative Commons CC BY.
dc.format.none.fl_str_mv pdf
application/pdf
dc.publisher.none.fl_str_mv Hector Florez, Universidad Distrital Francisco Jose de Caldas, Colombia.
publisher.none.fl_str_mv Hector Florez, Universidad Distrital Francisco Jose de Caldas, Colombia.
dc.source.none.fl_str_mv Frontiers in Computer Science, Sci. 5:1179059, 1-18. (2023)
reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
_version_ 1877862394138460160
score 13.365483

Publicaciones similares