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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23411
Ver los metadatos del registro completo
id |
SEDICI_b6f5de2ff71b39075377b320952fddd1 |
---|---|
oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/23411 |
network_acronym_str |
SEDICI |
repository_id_str |
1329 |
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 info:ar-repo/semantics/documentoDeConferencia |
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 |
dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
reponame_str |
SEDICI (UNLP) |
collection |
SEDICI (UNLP) |
instname_str |
Universidad Nacional de La Plata |
instacron_str |
UNLP |
institution |
UNLP |
repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
_version_ |
1842260121128796160 |
score |
13.13397 |