An agent-based simulation model using decoupled learning rules to (re)schedule multiple projects

Autores
Tosselli, Laura; Bogado, Verónica; Martínez, Ernesto
Año de publicación
2017
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Competitive pressures and business globalization have led many organizations, mainly technology-based and innovation-oriented companies, to adopt project-based organizational structures. In a multi-project context within enterprise networks, reaching feasible solutions to the multi-project (re)scheduling problem represents a major challenge, where autonomy and decentralization of the environment favor agent-based simulation This work presents and validates a simulation-based multi-agent model using the fractal company concept to solve the complex multi-project (re)scheduling problem in enterprise networks. The proposed agent-based model is tested trough a set of project instances that vary in project structure, project parameters, number of resources shared, unplanned events that affect them, etc. Results obtained are assessed through different scheduling goals, such project total duration, project total cost, leveling resource usage, among others to show that decoupled learning rules allows finding a solution which can be understood as a Nash equilibrium for the interacting agents and it is far better compared to the ones obtained with existing approaches.
Eje: XVIII Workshop de Agentes y Sistemas Inteligentes (WASI).
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
multi-project (re)scheduling
project-oriented fractal organization
multi-agent simulation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/63483
Acceder
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network_name_str SEDICI (UNLP)
spelling An agent-based simulation model using decoupled learning rules to (re)schedule multiple projectsTosselli, LauraBogado, VerónicaMartínez, ErnestoCiencias Informáticasmulti-project (re)schedulingproject-oriented fractal organizationmulti-agent simulationCompetitive pressures and business globalization have led many organizations, mainly technology-based and innovation-oriented companies, to adopt project-based organizational structures. In a multi-project context within enterprise networks, reaching feasible solutions to the multi-project (re)scheduling problem represents a major challenge, where autonomy and decentralization of the environment favor agent-based simulation This work presents and validates a simulation-based multi-agent model using the fractal company concept to solve the complex multi-project (re)scheduling problem in enterprise networks. The proposed agent-based model is tested trough a set of project instances that vary in project structure, project parameters, number of resources shared, unplanned events that affect them, etc. Results obtained are assessed through different scheduling goals, such project total duration, project total cost, leveling resource usage, among others to show that decoupled learning rules allows finding a solution which can be understood as a Nash equilibrium for the interacting agents and it is far better compared to the ones obtained with existing approaches.Eje: XVIII Workshop de Agentes y Sistemas Inteligentes (WASI).Red de Universidades con Carreras en Informática (RedUNCI)2017-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf33-42http://sedici.unlp.edu.ar/handle/10915/63483enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-34-1539-9info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:08:24Zoai:sedici.unlp.edu.ar:10915/63483Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:08:25.002SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv An agent-based simulation model using decoupled learning rules to (re)schedule multiple projects
title An agent-based simulation model using decoupled learning rules to (re)schedule multiple projects
spellingShingle An agent-based simulation model using decoupled learning rules to (re)schedule multiple projects
Tosselli, Laura
Ciencias Informáticas
multi-project (re)scheduling
project-oriented fractal organization
multi-agent simulation
title_short An agent-based simulation model using decoupled learning rules to (re)schedule multiple projects
title_full An agent-based simulation model using decoupled learning rules to (re)schedule multiple projects
title_fullStr An agent-based simulation model using decoupled learning rules to (re)schedule multiple projects
title_full_unstemmed An agent-based simulation model using decoupled learning rules to (re)schedule multiple projects
title_sort An agent-based simulation model using decoupled learning rules to (re)schedule multiple projects
dc.creator.none.fl_str_mv Tosselli, Laura
Bogado, Verónica
Martínez, Ernesto
author Tosselli, Laura
author_facet Tosselli, Laura
Bogado, Verónica
Martínez, Ernesto
author_role author
author2 Bogado, Verónica
Martínez, Ernesto
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
multi-project (re)scheduling
project-oriented fractal organization
multi-agent simulation
topic Ciencias Informáticas
multi-project (re)scheduling
project-oriented fractal organization
multi-agent simulation
dc.description.none.fl_txt_mv Competitive pressures and business globalization have led many organizations, mainly technology-based and innovation-oriented companies, to adopt project-based organizational structures. In a multi-project context within enterprise networks, reaching feasible solutions to the multi-project (re)scheduling problem represents a major challenge, where autonomy and decentralization of the environment favor agent-based simulation This work presents and validates a simulation-based multi-agent model using the fractal company concept to solve the complex multi-project (re)scheduling problem in enterprise networks. The proposed agent-based model is tested trough a set of project instances that vary in project structure, project parameters, number of resources shared, unplanned events that affect them, etc. Results obtained are assessed through different scheduling goals, such project total duration, project total cost, leveling resource usage, among others to show that decoupled learning rules allows finding a solution which can be understood as a Nash equilibrium for the interacting agents and it is far better compared to the ones obtained with existing approaches.
Eje: XVIII Workshop de Agentes y Sistemas Inteligentes (WASI).
Red de Universidades con Carreras en Informática (RedUNCI)
description Competitive pressures and business globalization have led many organizations, mainly technology-based and innovation-oriented companies, to adopt project-based organizational structures. In a multi-project context within enterprise networks, reaching feasible solutions to the multi-project (re)scheduling problem represents a major challenge, where autonomy and decentralization of the environment favor agent-based simulation This work presents and validates a simulation-based multi-agent model using the fractal company concept to solve the complex multi-project (re)scheduling problem in enterprise networks. The proposed agent-based model is tested trough a set of project instances that vary in project structure, project parameters, number of resources shared, unplanned events that affect them, etc. Results obtained are assessed through different scheduling goals, such project total duration, project total cost, leveling resource usage, among others to show that decoupled learning rules allows finding a solution which can be understood as a Nash equilibrium for the interacting agents and it is far better compared to the ones obtained with existing approaches.
publishDate 2017
dc.date.none.fl_str_mv 2017-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/63483
url http://sedici.unlp.edu.ar/handle/10915/63483
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-34-1539-9
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
33-42
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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