Algorithms to solve the dynamic weighted tardiness problem
- Autores
- Lasso, Marta Graciela; Pandolfi, Daniel; San Pedro, María Eugenia de; Villagra, Andrea; Vilanova, Gabriela; Gallard, Raúl Hector
- Año de publicación
- 2002
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- In static scheduling problems it is assumed that jobs are ready at zero time or before processing begins. In dynamic scheduling problems a job arrival can be given at any instant in the time interval between zero and a limit established by its processing time, ensuring to accomplish it before the due date deadline. In the cases where the arrivals are near to zero the problem comes closer to the static problem, otherwise the problem becomes more restrictive. This paper proposes two approaches for resolution of the dynamic problem of Total Weighted Tardiness for a single machine environment. The first approach uses, as a list of dispatching priorities a schedule, which an evolutionary algorithm found as the best for a similar static problem: same job features, processing time, due dates and weights. The second approach uses as a dispatching priority a schedule created by a robust non-evolutionary heuristic. The details of implementation of the proposed algorithms and results for a group of selected instances are discussed in this work.
Eje: Sistemas inteligentes
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
dynamic weighted
Algorithms
Scheduling
Algorithms to solve
tardiness problem
ARTIFICIAL INTELLIGENCE - 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:10915/23133
Ver los metadatos del registro completo
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Algorithms to solve the dynamic weighted tardiness problemLasso, Marta GracielaPandolfi, DanielSan Pedro, María Eugenia deVillagra, AndreaVilanova, GabrielaGallard, Raúl HectorCiencias Informáticasdynamic weightedAlgorithmsSchedulingAlgorithms to solvetardiness problemARTIFICIAL INTELLIGENCEIn static scheduling problems it is assumed that jobs are ready at zero time or before processing begins. In dynamic scheduling problems a job arrival can be given at any instant in the time interval between zero and a limit established by its processing time, ensuring to accomplish it before the due date deadline. In the cases where the arrivals are near to zero the problem comes closer to the static problem, otherwise the problem becomes more restrictive. This paper proposes two approaches for resolution of the dynamic problem of Total Weighted Tardiness for a single machine environment. The first approach uses, as a list of dispatching priorities a schedule, which an evolutionary algorithm found as the best for a similar static problem: same job features, processing time, due dates and weights. The second approach uses as a dispatching priority a schedule created by a robust non-evolutionary heuristic. The details of implementation of the proposed algorithms and results for a group of selected instances are discussed in this work.Eje: Sistemas inteligentesRed de Universidades con Carreras en Informática (RedUNCI)2002-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf609-616http://sedici.unlp.edu.ar/handle/10915/23133enginfo: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:UNLP2025-09-29T10:55:20Zoai:sedici.unlp.edu.ar:10915/23133Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:21.064SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Algorithms to solve the dynamic weighted tardiness problem |
title |
Algorithms to solve the dynamic weighted tardiness problem |
spellingShingle |
Algorithms to solve the dynamic weighted tardiness problem Lasso, Marta Graciela Ciencias Informáticas dynamic weighted Algorithms Scheduling Algorithms to solve tardiness problem ARTIFICIAL INTELLIGENCE |
title_short |
Algorithms to solve the dynamic weighted tardiness problem |
title_full |
Algorithms to solve the dynamic weighted tardiness problem |
title_fullStr |
Algorithms to solve the dynamic weighted tardiness problem |
title_full_unstemmed |
Algorithms to solve the dynamic weighted tardiness problem |
title_sort |
Algorithms to solve the dynamic weighted tardiness problem |
dc.creator.none.fl_str_mv |
Lasso, Marta Graciela Pandolfi, Daniel San Pedro, María Eugenia de Villagra, Andrea Vilanova, Gabriela Gallard, Raúl Hector |
author |
Lasso, Marta Graciela |
author_facet |
Lasso, Marta Graciela Pandolfi, Daniel San Pedro, María Eugenia de Villagra, Andrea Vilanova, Gabriela Gallard, Raúl Hector |
author_role |
author |
author2 |
Pandolfi, Daniel San Pedro, María Eugenia de Villagra, Andrea Vilanova, Gabriela Gallard, Raúl Hector |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas dynamic weighted Algorithms Scheduling Algorithms to solve tardiness problem ARTIFICIAL INTELLIGENCE |
topic |
Ciencias Informáticas dynamic weighted Algorithms Scheduling Algorithms to solve tardiness problem ARTIFICIAL INTELLIGENCE |
dc.description.none.fl_txt_mv |
In static scheduling problems it is assumed that jobs are ready at zero time or before processing begins. In dynamic scheduling problems a job arrival can be given at any instant in the time interval between zero and a limit established by its processing time, ensuring to accomplish it before the due date deadline. In the cases where the arrivals are near to zero the problem comes closer to the static problem, otherwise the problem becomes more restrictive. This paper proposes two approaches for resolution of the dynamic problem of Total Weighted Tardiness for a single machine environment. The first approach uses, as a list of dispatching priorities a schedule, which an evolutionary algorithm found as the best for a similar static problem: same job features, processing time, due dates and weights. The second approach uses as a dispatching priority a schedule created by a robust non-evolutionary heuristic. The details of implementation of the proposed algorithms and results for a group of selected instances are discussed in this work. Eje: Sistemas inteligentes Red de Universidades con Carreras en Informática (RedUNCI) |
description |
In static scheduling problems it is assumed that jobs are ready at zero time or before processing begins. In dynamic scheduling problems a job arrival can be given at any instant in the time interval between zero and a limit established by its processing time, ensuring to accomplish it before the due date deadline. In the cases where the arrivals are near to zero the problem comes closer to the static problem, otherwise the problem becomes more restrictive. This paper proposes two approaches for resolution of the dynamic problem of Total Weighted Tardiness for a single machine environment. The first approach uses, as a list of dispatching priorities a schedule, which an evolutionary algorithm found as the best for a similar static problem: same job features, processing time, due dates and weights. The second approach uses as a dispatching priority a schedule created by a robust non-evolutionary heuristic. The details of implementation of the proposed algorithms and results for a group of selected instances are discussed in this work. |
publishDate |
2002 |
dc.date.none.fl_str_mv |
2002-10 |
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 |
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http://sedici.unlp.edu.ar/handle/10915/23133 |
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http://sedici.unlp.edu.ar/handle/10915/23133 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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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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