A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines

Autores
Tupia Anticona, Manuel
Año de publicación
2006
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Industrial planning has experienced notable advancements since its beginning by the middle of the 20th century. The importance of its application within the several industries where it is used has been demonstrated, regardless of the difficulty of the design of the exact algorithms that solve the variants. Heuristic methods have been applied for planning problems due to their high complexity; especially Artificial Intelligence when developing new strategies to solve one of the most important variants called task scheduling. It is possible to define task scheduling as: .a set of N production line tasks and M machines, which can execute those tasks, where the goal is to find an execution order that minimizes the accumulated execution time, known as makespan. This paper presents a GRASP meta heuristic strategy for the problem of scheduling dependent tasks in different machines
IFIP International Conference on Artificial Intelligence in Theory and Practice - Industrial Applications of AI
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Heuristic methods
Algorithms
Scheduling
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:10915/23927
Acceder
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network_name_str SEDICI (UNLP)
spelling A GRASP algorithm to solve the problem of dependent tasks scheduling in different machinesTupia Anticona, ManuelCiencias InformáticasHeuristic methodsAlgorithmsSchedulingIndustrial planning has experienced notable advancements since its beginning by the middle of the 20th century. The importance of its application within the several industries where it is used has been demonstrated, regardless of the difficulty of the design of the exact algorithms that solve the variants. Heuristic methods have been applied for planning problems due to their high complexity; especially Artificial Intelligence when developing new strategies to solve one of the most important variants called task scheduling. It is possible to define task scheduling as: .a set of N production line tasks and M machines, which can execute those tasks, where the goal is to find an execution order that minimizes the accumulated execution time, known as makespan. This paper presents a GRASP meta heuristic strategy for the problem of scheduling dependent tasks in different machinesIFIP International Conference on Artificial Intelligence in Theory and Practice - Industrial Applications of AIRed de Universidades con Carreras en Informática (RedUNCI)2006-08info: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/10915/23927enginfo:eu-repo/semantics/altIdentifier/isbn/0-387-34654-6info: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:UNLP2025-09-29T10:55:40Zoai:sedici.unlp.edu.ar:10915/23927Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:40.53SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines
title A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines
spellingShingle A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines
Tupia Anticona, Manuel
Ciencias Informáticas
Heuristic methods
Algorithms
Scheduling
title_short A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines
title_full A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines
title_fullStr A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines
title_full_unstemmed A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines
title_sort A GRASP algorithm to solve the problem of dependent tasks scheduling in different machines
dc.creator.none.fl_str_mv Tupia Anticona, Manuel
author Tupia Anticona, Manuel
author_facet Tupia Anticona, Manuel
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Heuristic methods
Algorithms
Scheduling
topic Ciencias Informáticas
Heuristic methods
Algorithms
Scheduling
dc.description.none.fl_txt_mv Industrial planning has experienced notable advancements since its beginning by the middle of the 20th century. The importance of its application within the several industries where it is used has been demonstrated, regardless of the difficulty of the design of the exact algorithms that solve the variants. Heuristic methods have been applied for planning problems due to their high complexity; especially Artificial Intelligence when developing new strategies to solve one of the most important variants called task scheduling. It is possible to define task scheduling as: .a set of N production line tasks and M machines, which can execute those tasks, where the goal is to find an execution order that minimizes the accumulated execution time, known as makespan. This paper presents a GRASP meta heuristic strategy for the problem of scheduling dependent tasks in different machines
IFIP International Conference on Artificial Intelligence in Theory and Practice - Industrial Applications of AI
Red de Universidades con Carreras en Informática (RedUNCI)
description Industrial planning has experienced notable advancements since its beginning by the middle of the 20th century. The importance of its application within the several industries where it is used has been demonstrated, regardless of the difficulty of the design of the exact algorithms that solve the variants. Heuristic methods have been applied for planning problems due to their high complexity; especially Artificial Intelligence when developing new strategies to solve one of the most important variants called task scheduling. It is possible to define task scheduling as: .a set of N production line tasks and M machines, which can execute those tasks, where the goal is to find an execution order that minimizes the accumulated execution time, known as makespan. This paper presents a GRASP meta heuristic strategy for the problem of scheduling dependent tasks in different machines
publishDate 2006
dc.date.none.fl_str_mv 2006-08
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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dc.language.none.fl_str_mv eng
language eng
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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