Facing the job shop scheduling problem wih hybrid evolutionary algorithms

Autores
Salto, Carolina; Fernandez, Natalia; Alfonso, Hugo; Gallard, Raúl Hector
Año de publicación
2001
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Evolutionary algorithms (EAs) offer a robust approach to problem solving. EAs are extremely flexible and can be extended by incorporating alternative approaches to favour he search process. One way is to hybridize an evolutionary algorithm with standard local search procedures [10,11], such as hill climbing [12], simulated annealing [15] and tabu search [4]. Individual solutions can be improved using local techniques and then placed back in competition with other members of the population. The hybrid approach complements the properties of evolutionary algorithm and local search heuristic methods. An evolutionary algorithm is used to perform global search to escape from local optima, while local search is used to conduct fine-tuning.
Eje: Inteligencia Computacional - Metaheurísticas
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Facing the job shop scheduling problem
hybrid evolutionary algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
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:10915/21660
Acceder
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network_name_str SEDICI (UNLP)
spelling Facing the job shop scheduling problem wih hybrid evolutionary algorithmsSalto, CarolinaFernandez, NataliaAlfonso, HugoGallard, Raúl HectorCiencias InformáticasFacing the job shop scheduling problemhybrid evolutionary algorithmsSchedulingARTIFICIAL INTELLIGENCEAlgorithmsEvolutionary algorithms (EAs) offer a robust approach to problem solving. EAs are extremely flexible and can be extended by incorporating alternative approaches to favour he search process. One way is to hybridize an evolutionary algorithm with standard local search procedures [10,11], such as hill climbing [12], simulated annealing [15] and tabu search [4]. Individual solutions can be improved using local techniques and then placed back in competition with other members of the population. The hybrid approach complements the properties of evolutionary algorithm and local search heuristic methods. An evolutionary algorithm is used to perform global search to escape from local optima, while local search is used to conduct fine-tuning.Eje: Inteligencia Computacional - MetaheurísticasRed de Universidades con Carreras en Informática (RedUNCI)2001-05info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/21660enginfo: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:UNLP2025-09-10T11:58:07Zoai:sedici.unlp.edu.ar:10915/21660Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-10 11:58:07.573SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Facing the job shop scheduling problem wih hybrid evolutionary algorithms
title Facing the job shop scheduling problem wih hybrid evolutionary algorithms
spellingShingle Facing the job shop scheduling problem wih hybrid evolutionary algorithms
Salto, Carolina
Ciencias Informáticas
Facing the job shop scheduling problem
hybrid evolutionary algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
Algorithms
title_short Facing the job shop scheduling problem wih hybrid evolutionary algorithms
title_full Facing the job shop scheduling problem wih hybrid evolutionary algorithms
title_fullStr Facing the job shop scheduling problem wih hybrid evolutionary algorithms
title_full_unstemmed Facing the job shop scheduling problem wih hybrid evolutionary algorithms
title_sort Facing the job shop scheduling problem wih hybrid evolutionary algorithms
dc.creator.none.fl_str_mv Salto, Carolina
Fernandez, Natalia
Alfonso, Hugo
Gallard, Raúl Hector
author Salto, Carolina
author_facet Salto, Carolina
Fernandez, Natalia
Alfonso, Hugo
Gallard, Raúl Hector
author_role author
author2 Fernandez, Natalia
Alfonso, Hugo
Gallard, Raúl Hector
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Facing the job shop scheduling problem
hybrid evolutionary algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
Algorithms
topic Ciencias Informáticas
Facing the job shop scheduling problem
hybrid evolutionary algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
Algorithms
dc.description.none.fl_txt_mv Evolutionary algorithms (EAs) offer a robust approach to problem solving. EAs are extremely flexible and can be extended by incorporating alternative approaches to favour he search process. One way is to hybridize an evolutionary algorithm with standard local search procedures [10,11], such as hill climbing [12], simulated annealing [15] and tabu search [4]. Individual solutions can be improved using local techniques and then placed back in competition with other members of the population. The hybrid approach complements the properties of evolutionary algorithm and local search heuristic methods. An evolutionary algorithm is used to perform global search to escape from local optima, while local search is used to conduct fine-tuning.
Eje: Inteligencia Computacional - Metaheurísticas
Red de Universidades con Carreras en Informática (RedUNCI)
description Evolutionary algorithms (EAs) offer a robust approach to problem solving. EAs are extremely flexible and can be extended by incorporating alternative approaches to favour he search process. One way is to hybridize an evolutionary algorithm with standard local search procedures [10,11], such as hill climbing [12], simulated annealing [15] and tabu search [4]. Individual solutions can be improved using local techniques and then placed back in competition with other members of the population. The hybrid approach complements the properties of evolutionary algorithm and local search heuristic methods. An evolutionary algorithm is used to perform global search to escape from local optima, while local search is used to conduct fine-tuning.
publishDate 2001
dc.date.none.fl_str_mv 2001-05
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/10915/21660
url http://sedici.unlp.edu.ar/handle/10915/21660
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
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
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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score 12.993085

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