A genetic approach using direct representation of solution for the parallel task scheduling problem

Autores
Esquivel, Susana Cecilia; Gatica, Claudia R.; Gallard, Raúl Hector
Año de publicación
2001
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In scheduling, a set of machines in parallel is a setting that is important, from both the theoretical and practical points of view. From the theoretical viewpoint, it is a generalization of the single machine scheduling problem. From the practical point of view the occurrence of resources in parallel is common in real-world. When machines are computers, a parallel program can be conceived as a set of parallel components (tasks) which can be executed according to some precedence relationship. In this case efficient scheduling of tasks permits to take full advantage of the computational power provided by a multiprocessor or a multicomputer system. This kind of planning involves the assignment of partially ordered tasks onto the system architecture processing components. This paper shows the problem of allocating a number of non-identical tasks in a multiprocessor or multicomputer system. The model assumes that the system consists of a number of identical processors and only one task may execute on a processor at a time. All schedules and tasks are non-preemptive. The well-known Graham’s list scheduling algorithm (LSA) is contrasted with an evolutionary approach using a direct representation of solutions.
Eje: Computación evolutiva
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Task scheduling
evolutionary algorithms
direct representation
List Scheduling Algorithm
Evolución
Scheduling
Algorithms
Parallel
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:10915/23543

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network_name_str SEDICI (UNLP)
spelling A genetic approach using direct representation of solution for the parallel task scheduling problemEsquivel, Susana CeciliaGatica, Claudia R.Gallard, Raúl HectorCiencias InformáticasTask schedulingevolutionary algorithmsdirect representationList Scheduling AlgorithmEvoluciónSchedulingAlgorithmsParallelIn scheduling, a set of machines in parallel is a setting that is important, from both the theoretical and practical points of view. From the theoretical viewpoint, it is a generalization of the single machine scheduling problem. From the practical point of view the occurrence of resources in parallel is common in real-world. When machines are computers, a parallel program can be conceived as a set of parallel components (tasks) which can be executed according to some precedence relationship. In this case efficient scheduling of tasks permits to take full advantage of the computational power provided by a multiprocessor or a multicomputer system. This kind of planning involves the assignment of partially ordered tasks onto the system architecture processing components. This paper shows the problem of allocating a number of non-identical tasks in a multiprocessor or multicomputer system. The model assumes that the system consists of a number of identical processors and only one task may execute on a processor at a time. All schedules and tasks are non-preemptive. The well-known Graham’s list scheduling algorithm (LSA) is contrasted with an evolutionary approach using a direct representation of solutions.Eje: Computación evolutivaRed de Universidades con Carreras en Informática (RedUNCI)2001-10info: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/10915/23543enginfo: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:UNLP2025-09-03T10:28:18Zoai:sedici.unlp.edu.ar:10915/23543Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:28:19.116SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A genetic approach using direct representation of solution for the parallel task scheduling problem
title A genetic approach using direct representation of solution for the parallel task scheduling problem
spellingShingle A genetic approach using direct representation of solution for the parallel task scheduling problem
Esquivel, Susana Cecilia
Ciencias Informáticas
Task scheduling
evolutionary algorithms
direct representation
List Scheduling Algorithm
Evolución
Scheduling
Algorithms
Parallel
title_short A genetic approach using direct representation of solution for the parallel task scheduling problem
title_full A genetic approach using direct representation of solution for the parallel task scheduling problem
title_fullStr A genetic approach using direct representation of solution for the parallel task scheduling problem
title_full_unstemmed A genetic approach using direct representation of solution for the parallel task scheduling problem
title_sort A genetic approach using direct representation of solution for the parallel task scheduling problem
dc.creator.none.fl_str_mv Esquivel, Susana Cecilia
Gatica, Claudia R.
Gallard, Raúl Hector
author Esquivel, Susana Cecilia
author_facet Esquivel, Susana Cecilia
Gatica, Claudia R.
Gallard, Raúl Hector
author_role author
author2 Gatica, Claudia R.
Gallard, Raúl Hector
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Task scheduling
evolutionary algorithms
direct representation
List Scheduling Algorithm
Evolución
Scheduling
Algorithms
Parallel
topic Ciencias Informáticas
Task scheduling
evolutionary algorithms
direct representation
List Scheduling Algorithm
Evolución
Scheduling
Algorithms
Parallel
dc.description.none.fl_txt_mv In scheduling, a set of machines in parallel is a setting that is important, from both the theoretical and practical points of view. From the theoretical viewpoint, it is a generalization of the single machine scheduling problem. From the practical point of view the occurrence of resources in parallel is common in real-world. When machines are computers, a parallel program can be conceived as a set of parallel components (tasks) which can be executed according to some precedence relationship. In this case efficient scheduling of tasks permits to take full advantage of the computational power provided by a multiprocessor or a multicomputer system. This kind of planning involves the assignment of partially ordered tasks onto the system architecture processing components. This paper shows the problem of allocating a number of non-identical tasks in a multiprocessor or multicomputer system. The model assumes that the system consists of a number of identical processors and only one task may execute on a processor at a time. All schedules and tasks are non-preemptive. The well-known Graham’s list scheduling algorithm (LSA) is contrasted with an evolutionary approach using a direct representation of solutions.
Eje: Computación evolutiva
Red de Universidades con Carreras en Informática (RedUNCI)
description In scheduling, a set of machines in parallel is a setting that is important, from both the theoretical and practical points of view. From the theoretical viewpoint, it is a generalization of the single machine scheduling problem. From the practical point of view the occurrence of resources in parallel is common in real-world. When machines are computers, a parallel program can be conceived as a set of parallel components (tasks) which can be executed according to some precedence relationship. In this case efficient scheduling of tasks permits to take full advantage of the computational power provided by a multiprocessor or a multicomputer system. This kind of planning involves the assignment of partially ordered tasks onto the system architecture processing components. This paper shows the problem of allocating a number of non-identical tasks in a multiprocessor or multicomputer system. The model assumes that the system consists of a number of identical processors and only one task may execute on a processor at a time. All schedules and tasks are non-preemptive. The well-known Graham’s list scheduling algorithm (LSA) is contrasted with an evolutionary approach using a direct representation of solutions.
publishDate 2001
dc.date.none.fl_str_mv 2001-10
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/10915/23543
url http://sedici.unlp.edu.ar/handle/10915/23543
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
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instname:Universidad Nacional de La Plata
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reponame_str SEDICI (UNLP)
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instname_str Universidad Nacional de La Plata
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institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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