Parallel and sequential evolutionary algorithms for the flow shop scheduling problem

Autores
Esquivel, Susana Cecilia; Printista, Alicia Marcela; Zuppa, Federico; Gallard, Raúl Hector
Año de publicación
2000
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Determining an optimal schedule to m1mm1ze the completion time of the last job abandoning the system (makespan) become a very difficult problem when there are more than two machines in the flow shop. Due both to its economical impact and complexity attention to solve the Flow Shop Scheduling problem (FSSP) has been paid by many researchers. Current trends involve distinct evolutionary computation approaches. Parallel implementations of Evolutionary Algorithms aim to improvements on performance. This work shows an implementation of parallel and sequential evolutionary approaches for the FSSP. The first one implements the island model on diverse number of island while the second evolves a single population. Experiments include also latest approaches using a multiplicity feature: Multiple Crossovers per Couple (MCPC) on a set of flow shop scheduling instances. A discussion on implementation details, analysis and comparisons of sequential, parallel, single and multirecombinated evolutionary approaches to the problem are shown.
I Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Multiple Crossovers per Couple (MCPC)
Flow Shop Scheduling problem (FSSP)
island model
Scheduling
Algorithms
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:10915/23411

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network_name_str SEDICI (UNLP)
spelling Parallel and sequential evolutionary algorithms for the flow shop scheduling problemEsquivel, Susana CeciliaPrintista, Alicia MarcelaZuppa, FedericoGallard, Raúl HectorCiencias InformáticasMultiple Crossovers per Couple (MCPC)Flow Shop Scheduling problem (FSSP)island modelSchedulingAlgorithmsDetermining an optimal schedule to m1mm1ze the completion time of the last job abandoning the system (makespan) become a very difficult problem when there are more than two machines in the flow shop. Due both to its economical impact and complexity attention to solve the Flow Shop Scheduling problem (FSSP) has been paid by many researchers. Current trends involve distinct evolutionary computation approaches. Parallel implementations of Evolutionary Algorithms aim to improvements on performance. This work shows an implementation of parallel and sequential evolutionary approaches for the FSSP. The first one implements the island model on diverse number of island while the second evolves a single population. Experiments include also latest approaches using a multiplicity feature: Multiple Crossovers per Couple (MCPC) on a set of flow shop scheduling instances. A discussion on implementation details, analysis and comparisons of sequential, parallel, single and multirecombinated evolutionary approaches to the problem are shown.I Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2000-10info: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/10915/23411enginfo: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:UNLP2025-09-03T10:28:16Zoai:sedici.unlp.edu.ar:10915/23411Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:28:17.148SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Parallel and sequential evolutionary algorithms for the flow shop scheduling problem
title Parallel and sequential evolutionary algorithms for the flow shop scheduling problem
spellingShingle Parallel and sequential evolutionary algorithms for the flow shop scheduling problem
Esquivel, Susana Cecilia
Ciencias Informáticas
Multiple Crossovers per Couple (MCPC)
Flow Shop Scheduling problem (FSSP)
island model
Scheduling
Algorithms
title_short Parallel and sequential evolutionary algorithms for the flow shop scheduling problem
title_full Parallel and sequential evolutionary algorithms for the flow shop scheduling problem
title_fullStr Parallel and sequential evolutionary algorithms for the flow shop scheduling problem
title_full_unstemmed Parallel and sequential evolutionary algorithms for the flow shop scheduling problem
title_sort Parallel and sequential evolutionary algorithms for the flow shop scheduling problem
dc.creator.none.fl_str_mv Esquivel, Susana Cecilia
Printista, Alicia Marcela
Zuppa, Federico
Gallard, Raúl Hector
author Esquivel, Susana Cecilia
author_facet Esquivel, Susana Cecilia
Printista, Alicia Marcela
Zuppa, Federico
Gallard, Raúl Hector
author_role author
author2 Printista, Alicia Marcela
Zuppa, Federico
Gallard, Raúl Hector
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Multiple Crossovers per Couple (MCPC)
Flow Shop Scheduling problem (FSSP)
island model
Scheduling
Algorithms
topic Ciencias Informáticas
Multiple Crossovers per Couple (MCPC)
Flow Shop Scheduling problem (FSSP)
island model
Scheduling
Algorithms
dc.description.none.fl_txt_mv Determining an optimal schedule to m1mm1ze the completion time of the last job abandoning the system (makespan) become a very difficult problem when there are more than two machines in the flow shop. Due both to its economical impact and complexity attention to solve the Flow Shop Scheduling problem (FSSP) has been paid by many researchers. Current trends involve distinct evolutionary computation approaches. Parallel implementations of Evolutionary Algorithms aim to improvements on performance. This work shows an implementation of parallel and sequential evolutionary approaches for the FSSP. The first one implements the island model on diverse number of island while the second evolves a single population. Experiments include also latest approaches using a multiplicity feature: Multiple Crossovers per Couple (MCPC) on a set of flow shop scheduling instances. A discussion on implementation details, analysis and comparisons of sequential, parallel, single and multirecombinated evolutionary approaches to the problem are shown.
I Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description Determining an optimal schedule to m1mm1ze the completion time of the last job abandoning the system (makespan) become a very difficult problem when there are more than two machines in the flow shop. Due both to its economical impact and complexity attention to solve the Flow Shop Scheduling problem (FSSP) has been paid by many researchers. Current trends involve distinct evolutionary computation approaches. Parallel implementations of Evolutionary Algorithms aim to improvements on performance. This work shows an implementation of parallel and sequential evolutionary approaches for the FSSP. The first one implements the island model on diverse number of island while the second evolves a single population. Experiments include also latest approaches using a multiplicity feature: Multiple Crossovers per Couple (MCPC) on a set of flow shop scheduling instances. A discussion on implementation details, analysis and comparisons of sequential, parallel, single and multirecombinated evolutionary approaches to the problem are shown.
publishDate 2000
dc.date.none.fl_str_mv 2000-10
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
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format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/23411
url http://sedici.unlp.edu.ar/handle/10915/23411
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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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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