A comparison between centralized and decentralized genetic algorithms for the identical parallel machines scheduling
- Autores
- Esquivel, Susana Cecilia
- Año de publicación
- 2006
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Identical parallel machines problems (Pm) involve task assignments to the system's resources (a machine bank in parallel). The basic model consists of m machines and n tasks. The tasks are assigned according to the availability of the resources, following some allocation rule. In this work, the minimization of some objectives related to the due dates such as the maximum tardiness (Tmax) and the average tardiness (Tavg) were dealt with centralized and decentralized evolutive algorithms (EAs). In order to test our algorithms we used standard benchmarks. The main goal of this research was determinate the quality of the results obtained with a centralized GA and three decentralized GAs used to solve parallel machines scheduling problems. The results were compared using the ANOVA statistic method.
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
Scheduling
Parallel
Algorithms - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/22620
Ver los metadatos del registro completo
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A comparison between centralized and decentralized genetic algorithms for the identical parallel machines schedulingEsquivel, Susana CeciliaCiencias InformáticasSchedulingParallelAlgorithmsIdentical parallel machines problems (Pm) involve task assignments to the system's resources (a machine bank in parallel). The basic model consists of m machines and n tasks. The tasks are assigned according to the availability of the resources, following some allocation rule. In this work, the minimization of some objectives related to the due dates such as the maximum tardiness (Tmax) and the average tardiness (Tavg) were dealt with centralized and decentralized evolutive algorithms (EAs). In order to test our algorithms we used standard benchmarks. The main goal of this research was determinate the quality of the results obtained with a centralized GA and three decentralized GAs used to solve parallel machines scheduling problems. The results were compared using the ANOVA statistic method.Red de Universidades con Carreras en Informática (RedUNCI)2006-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1118-1125http://sedici.unlp.edu.ar/handle/10915/22620enginfo: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:UNLP2025-09-03T10:27:57Zoai:sedici.unlp.edu.ar:10915/22620Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:27:57.699SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
A comparison between centralized and decentralized genetic algorithms for the identical parallel machines scheduling |
title |
A comparison between centralized and decentralized genetic algorithms for the identical parallel machines scheduling |
spellingShingle |
A comparison between centralized and decentralized genetic algorithms for the identical parallel machines scheduling Esquivel, Susana Cecilia Ciencias Informáticas Scheduling Parallel Algorithms |
title_short |
A comparison between centralized and decentralized genetic algorithms for the identical parallel machines scheduling |
title_full |
A comparison between centralized and decentralized genetic algorithms for the identical parallel machines scheduling |
title_fullStr |
A comparison between centralized and decentralized genetic algorithms for the identical parallel machines scheduling |
title_full_unstemmed |
A comparison between centralized and decentralized genetic algorithms for the identical parallel machines scheduling |
title_sort |
A comparison between centralized and decentralized genetic algorithms for the identical parallel machines scheduling |
dc.creator.none.fl_str_mv |
Esquivel, Susana Cecilia |
author |
Esquivel, Susana Cecilia |
author_facet |
Esquivel, Susana Cecilia |
author_role |
author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Scheduling Parallel Algorithms |
topic |
Ciencias Informáticas Scheduling Parallel Algorithms |
dc.description.none.fl_txt_mv |
Identical parallel machines problems (Pm) involve task assignments to the system's resources (a machine bank in parallel). The basic model consists of m machines and n tasks. The tasks are assigned according to the availability of the resources, following some allocation rule. In this work, the minimization of some objectives related to the due dates such as the maximum tardiness (Tmax) and the average tardiness (Tavg) were dealt with centralized and decentralized evolutive algorithms (EAs). In order to test our algorithms we used standard benchmarks. The main goal of this research was determinate the quality of the results obtained with a centralized GA and three decentralized GAs used to solve parallel machines scheduling problems. The results were compared using the ANOVA statistic method. Red de Universidades con Carreras en Informática (RedUNCI) |
description |
Identical parallel machines problems (Pm) involve task assignments to the system's resources (a machine bank in parallel). The basic model consists of m machines and n tasks. The tasks are assigned according to the availability of the resources, following some allocation rule. In this work, the minimization of some objectives related to the due dates such as the maximum tardiness (Tmax) and the average tardiness (Tavg) were dealt with centralized and decentralized evolutive algorithms (EAs). In order to test our algorithms we used standard benchmarks. The main goal of this research was determinate the quality of the results obtained with a centralized GA and three decentralized GAs used to solve parallel machines scheduling problems. The results were compared using the ANOVA statistic method. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-10 |
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/10915/22620 |
url |
http://sedici.unlp.edu.ar/handle/10915/22620 |
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 1118-1125 |
dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
reponame_str |
SEDICI (UNLP) |
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SEDICI (UNLP) |
instname_str |
Universidad Nacional de La Plata |
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UNLP |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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