Repair algorithms and penalty functions to handling constraints in an evolutionary scheduling

Autores
Villagra, Andrea; Pandolfi, Daniel; Rasjido, José; Montenegro, Cristian; Serón, Natalia; Leguizamón, Mario Guillermo
Año de publicación
2010
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Ecosystems are directly and negatively affected by many industrial risky activities such as the oil transportation and exploitation. It is therefore important that oil companies carry out a correct maintenance of their oil fields. In this work we implement in our previously proposed evolutionary optimization tool (called PAE) a set of constraint-handling techniques to solve a constrained version of the maintenance problem. The results and comparisons demonstrated that the proposed repair algorithm required less computational effort (evaluations) with the same quality of solutions for the set of instances used.
Presentado en XI Workshop Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Ecosistema
Constraints
Algorithms
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/18808
Acceder
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network_name_str SEDICI (UNLP)
spelling Repair algorithms and penalty functions to handling constraints in an evolutionary schedulingVillagra, AndreaPandolfi, DanielRasjido, JoséMontenegro, CristianSerón, NataliaLeguizamón, Mario GuillermoCiencias InformáticasEcosistemaConstraintsAlgorithmsEcosystems are directly and negatively affected by many industrial risky activities such as the oil transportation and exploitation. It is therefore important that oil companies carry out a correct maintenance of their oil fields. In this work we implement in our previously proposed evolutionary optimization tool (called PAE) a set of constraint-handling techniques to solve a constrained version of the maintenance problem. The results and comparisons demonstrated that the proposed repair algorithm required less computational effort (evaluations) with the same quality of solutions for the set of instances used.Presentado en XI Workshop Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2010-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf41-51http://sedici.unlp.edu.ar/handle/10915/18808enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-9474-49-9info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:35:13Zoai:sedici.unlp.edu.ar:10915/18808Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:35:13.428SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Repair algorithms and penalty functions to handling constraints in an evolutionary scheduling
title Repair algorithms and penalty functions to handling constraints in an evolutionary scheduling
spellingShingle Repair algorithms and penalty functions to handling constraints in an evolutionary scheduling
Villagra, Andrea
Ciencias Informáticas
Ecosistema
Constraints
Algorithms
title_short Repair algorithms and penalty functions to handling constraints in an evolutionary scheduling
title_full Repair algorithms and penalty functions to handling constraints in an evolutionary scheduling
title_fullStr Repair algorithms and penalty functions to handling constraints in an evolutionary scheduling
title_full_unstemmed Repair algorithms and penalty functions to handling constraints in an evolutionary scheduling
title_sort Repair algorithms and penalty functions to handling constraints in an evolutionary scheduling
dc.creator.none.fl_str_mv Villagra, Andrea
Pandolfi, Daniel
Rasjido, José
Montenegro, Cristian
Serón, Natalia
Leguizamón, Mario Guillermo
author Villagra, Andrea
author_facet Villagra, Andrea
Pandolfi, Daniel
Rasjido, José
Montenegro, Cristian
Serón, Natalia
Leguizamón, Mario Guillermo
author_role author
author2 Pandolfi, Daniel
Rasjido, José
Montenegro, Cristian
Serón, Natalia
Leguizamón, Mario Guillermo
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Ecosistema
Constraints
Algorithms
topic Ciencias Informáticas
Ecosistema
Constraints
Algorithms
dc.description.none.fl_txt_mv Ecosystems are directly and negatively affected by many industrial risky activities such as the oil transportation and exploitation. It is therefore important that oil companies carry out a correct maintenance of their oil fields. In this work we implement in our previously proposed evolutionary optimization tool (called PAE) a set of constraint-handling techniques to solve a constrained version of the maintenance problem. The results and comparisons demonstrated that the proposed repair algorithm required less computational effort (evaluations) with the same quality of solutions for the set of instances used.
Presentado en XI Workshop Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description Ecosystems are directly and negatively affected by many industrial risky activities such as the oil transportation and exploitation. It is therefore important that oil companies carry out a correct maintenance of their oil fields. In this work we implement in our previously proposed evolutionary optimization tool (called PAE) a set of constraint-handling techniques to solve a constrained version of the maintenance problem. The results and comparisons demonstrated that the proposed repair algorithm required less computational effort (evaluations) with the same quality of solutions for the set of instances used.
publishDate 2010
dc.date.none.fl_str_mv 2010-10
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
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/18808
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-9474-49-9
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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