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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23543
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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) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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13.13397 |