An evolutionary metaheuristic for forming teams in the classroom with constraints

[EN] Team formation is essential for developing teamwork-related skills in educational settings. The problem of team formation in the classroom consists of partitioning a classroom into non-overlapping teams of students, including every single student. Several algorithms have been proposed to automa...

Descripción completa

Detalles Bibliográficos
Autores: Candel, Gonzalo, Sanchez-Anguix, Víctor|||0000-0003-4851-0037, Alberola Oltra, Juan Miguel|||0000-0002-5486-5638, Julian, Vicente|||0000-0002-2743-6037, Botti V.|||0000-0002-6507-2756
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/232274
Acceso en línea:https://riunet.upv.es/handle/10251/232274
Access Level:acceso abierto
Palabra clave:Team formation
Artificial intelligence
Metaheuristics
Evolutionary algorithm
Teamwork
Classroom
id ES_7f87d7eda39236a48c8e931e240f0f57
oai_identifier_str oai:riunet.upv.es:10251/232274
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv An evolutionary metaheuristic for forming teams in the classroom with constraints
title An evolutionary metaheuristic for forming teams in the classroom with constraints
spellingShingle An evolutionary metaheuristic for forming teams in the classroom with constraints
Candel, Gonzalo
Team formation
Artificial intelligence
Metaheuristics
Evolutionary algorithm
Teamwork
Classroom
title_short An evolutionary metaheuristic for forming teams in the classroom with constraints
title_full An evolutionary metaheuristic for forming teams in the classroom with constraints
title_fullStr An evolutionary metaheuristic for forming teams in the classroom with constraints
title_full_unstemmed An evolutionary metaheuristic for forming teams in the classroom with constraints
title_sort An evolutionary metaheuristic for forming teams in the classroom with constraints
dc.creator.none.fl_str_mv Candel, Gonzalo
Sanchez-Anguix, Víctor|||0000-0003-4851-0037
Alberola Oltra, Juan Miguel|||0000-0002-5486-5638
Julian, Vicente|||0000-0002-2743-6037
Botti V.|||0000-0002-6507-2756
author Candel, Gonzalo
author_facet Candel, Gonzalo
Sanchez-Anguix, Víctor|||0000-0003-4851-0037
Alberola Oltra, Juan Miguel|||0000-0002-5486-5638
Julian, Vicente|||0000-0002-2743-6037
Botti V.|||0000-0002-6507-2756
author_role author
author2 Sanchez-Anguix, Víctor|||0000-0003-4851-0037
Alberola Oltra, Juan Miguel|||0000-0002-5486-5638
Julian, Vicente|||0000-0002-2743-6037
Botti V.|||0000-0002-6507-2756
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Instituto Universitario Mixto de Tecnología de Informática
Departamento de Sistemas Informáticos y Computación
Departamento de Estadística e Investigación Operativa Aplicadas y Calidad
Escuela Politécnica Superior de Gandia
Escuela Técnica Superior de Ingeniería Informática
Instituto Universitario Valenciano de Investigación en Inteligencia Artificial
European Commission
AGENCIA ESTATAL DE INVESTIGACION
• Agència Valenciana de la Innovació
Universitat Politècnica de València
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Team formation
Artificial intelligence
Metaheuristics
Evolutionary algorithm
Teamwork
Classroom
topic Team formation
Artificial intelligence
Metaheuristics
Evolutionary algorithm
Teamwork
Classroom
description [EN] Team formation is essential for developing teamwork-related skills in educational settings. The problem of team formation in the classroom consists of partitioning a classroom into non-overlapping teams of students, including every single student. Several algorithms have been proposed to automate the formation of teams, each employing different criteria for guiding the team formation process. Traditionally, metaheuristics have been a common approach due to the combinatorial complexity of the problem. This paper introduces a novel and general evolutionary algorithm for team formation in the classroom guided by mutation, the general concept of synergy between team members, and local search. Our algorithm allows for flexible team size constraints and the inclusion of compulsory and forbidden student combinations, which are not considered in existing methods but are important for capturing human relationships in the classroom. In addition, our algorithm is independent of the specific objective function employed to evaluate the teams formed. We present experiments comparing our proposal with other state-of-the-art algorithms, demonstrating robust performance across different objective functions employed in the team formation literature, superior scalability as the problem size increases, and remarkable performance in settings with or without the aforementioned constraints.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-07-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/232274
url https://riunet.upv.es/handle/10251/232274
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 RTI2018-095390-B-C31 HACIA UNA MOVILIDAD INTELIGENTE Y SOSTENIBLE SOPORTADA POR SISTEMAS MULTI-AGENTES Y EDGE COMPUTING
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2021-123673OB-C31 SERVICIOS INTELIGENTES COORDINADOS PARA AREAS INTELIGENTES ADAPTATIVAS
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2021-124975OB-I00 OPTIMIZACION REALISTA EN PROBLEMAS DE SALUD PUBLICA
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 TED2021-131295B-C32 INGENIERIA DE VALORES EN SISTEMAS DE IA: HERRAMIENTAS PARA LA TOMA DE DECISIONES BASADAS EN VALORES
AGENCIA VALENCIANA DE LA INNOVACION AGENCIA VALENCIANA DE LA INNOVACION INNVA1%2F2024%2F91 Hireves: Herramienta Interactiva de Relocalización de Vehículos de Emergencias Sanitarias
European Commission https://doi.org/10.13039/501100000780 CLOUDAI02%2FS8760000
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial (by-nc)
http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial (by-nc)
http://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869411831300227072
spelling An evolutionary metaheuristic for forming teams in the classroom with constraintsCandel, GonzaloSanchez-Anguix, Víctor|||0000-0003-4851-0037Alberola Oltra, Juan Miguel|||0000-0002-5486-5638Julian, Vicente|||0000-0002-2743-6037Botti V.|||0000-0002-6507-2756Team formationArtificial intelligenceMetaheuristicsEvolutionary algorithmTeamworkClassroom[EN] Team formation is essential for developing teamwork-related skills in educational settings. The problem of team formation in the classroom consists of partitioning a classroom into non-overlapping teams of students, including every single student. Several algorithms have been proposed to automate the formation of teams, each employing different criteria for guiding the team formation process. Traditionally, metaheuristics have been a common approach due to the combinatorial complexity of the problem. This paper introduces a novel and general evolutionary algorithm for team formation in the classroom guided by mutation, the general concept of synergy between team members, and local search. Our algorithm allows for flexible team size constraints and the inclusion of compulsory and forbidden student combinations, which are not considered in existing methods but are important for capturing human relationships in the classroom. In addition, our algorithm is independent of the specific objective function employed to evaluate the teams formed. We present experiments comparing our proposal with other state-of-the-art algorithms, demonstrating robust performance across different objective functions employed in the team formation literature, superior scalability as the problem size increases, and remarkable performance in settings with or without the aforementioned constraints.This work was partially supported by MINECO/FEDER RTI2018-095390-B-C31 project of the Spanish government, project TED2021-131295B-C32 from the State Research Agency, and DIGITAL2022 CLOUDAI02/S8760000 from the European Commission, . Some of the authors are partially supported by the Spanish Ministry of Science and Innovation under the project PID2021-123673OB-C31 COSASS and project OPRES-Realistic Optimization in Problems in Public Health (No. PID2021-124975OB-I00), partially financed with FEDER funds. Additional support is provided by project INNVA1/2024/91 funded by Agencia Valenciana de la Innovación.ElsevierInstituto Universitario Mixto de Tecnología de InformáticaDepartamento de Sistemas Informáticos y ComputaciónDepartamento de Estadística e Investigación Operativa Aplicadas y CalidadEscuela Politécnica Superior de GandiaEscuela Técnica Superior de Ingeniería InformáticaInstituto Universitario Valenciano de Investigación en Inteligencia ArtificialEuropean CommissionAGENCIA ESTATAL DE INVESTIGACION• Agència Valenciana de la InnovacióUniversitat Politècnica de ValènciaRepositorio Institucional de la Universitat Politècnica de València Riunet20252025-07-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/232274reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 RTI2018-095390-B-C31 HACIA UNA MOVILIDAD INTELIGENTE Y SOSTENIBLE SOPORTADA POR SISTEMAS MULTI-AGENTES Y EDGE COMPUTINGAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2021-123673OB-C31 SERVICIOS INTELIGENTES COORDINADOS PARA AREAS INTELIGENTES ADAPTATIVASAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2021-124975OB-I00 OPTIMIZACION REALISTA EN PROBLEMAS DE SALUD PUBLICAAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 TED2021-131295B-C32 INGENIERIA DE VALORES EN SISTEMAS DE IA: HERRAMIENTAS PARA LA TOMA DE DECISIONES BASADAS EN VALORESAGENCIA VALENCIANA DE LA INNOVACION AGENCIA VALENCIANA DE LA INNOVACION INNVA1%2F2024%2F91 Hireves: Herramienta Interactiva de Relocalización de Vehículos de Emergencias SanitariasEuropean Commission https://doi.org/10.13039/501100000780 CLOUDAI02%2FS8760000open accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial (by-nc) http://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2322742026-06-13T07:49:27Z
score 15,812429

Similares en LA Referencia