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

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 parall...

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Detalles Bibliográficos
Autores principales: Esquivel, Susana Cecilia, Gatica, Claudia R., Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2001
Materias:
Ciencias Informáticas
Task scheduling
evolutionary algorithms
direct representation
List Scheduling Algorithm
Evolución
Scheduling
Algorithms
Parallel
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23543
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-23543
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Task scheduling
evolutionary algorithms
direct representation
List Scheduling Algorithm
Evolución
Scheduling
Algorithms
Parallel
spellingShingle Ciencias Informáticas
Task scheduling
evolutionary algorithms
direct representation
List Scheduling Algorithm
Evolución
Scheduling
Algorithms
Parallel
Esquivel, Susana Cecilia
Gatica, Claudia R.
Gallard, Raúl Hector
A genetic approach using direct representation of solution for the parallel task scheduling problem
topic_facet Ciencias Informáticas
Task scheduling
evolutionary algorithms
direct representation
List Scheduling Algorithm
Evolución
Scheduling
Algorithms
Parallel
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.
format Objeto de conferencia
Objeto de conferencia
author Esquivel, Susana Cecilia
Gatica, Claudia R.
Gallard, Raúl Hector
author_facet Esquivel, Susana Cecilia
Gatica, Claudia R.
Gallard, Raúl Hector
author_sort Esquivel, Susana Cecilia
title A genetic approach using direct representation of solution for the parallel task scheduling problem
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 genetic approach using direct representation of solution for the parallel task scheduling problem
publishDate 2001
url http://sedici.unlp.edu.ar/handle/10915/23543
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AT gaticaclaudiar geneticapproachusingdirectrepresentationofsolutionfortheparalleltaskschedulingproblem
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bdutipo_str Repositorios
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