Solving the flow shop scheduling problem under evolutionary approaches
- Autores
- Vilanova, Gabriela; Pandolfi, Daniel; San Pedro, María Eugenia de; Villagra, Andrea; Bain, María Elena; Gallard, Raúl Hector
- Año de publicación
- 2001
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- The flow shop scheduling problem (FSSP) [12], has held the attention of many researchers. In a simplest usual situation, a set of jobs must follow the same route to be executed on a set of machines (resources) and the main objective is to optimize some performance variable (makespan, tardiness, lateness, etc.). In the case of the makespan, it have been proved that when the number of machines is greater than or equal to three, the problem is NP-hard.
Eje: Inteligencia Computacional - Metaheurísticas
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
Solving the flow shop scheduling problem
evolutionary approaches
Scheduling
ARTIFICIAL INTELLIGENCE - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/21670
Ver los metadatos del registro completo
| id |
SEDICI_fe8b1d6671ce94db94e3127614b66d46 |
|---|---|
| oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/21670 |
| network_acronym_str |
SEDICI |
| repository_id_str |
1329 |
| network_name_str |
SEDICI (UNLP) |
| spelling |
Solving the flow shop scheduling problem under evolutionary approachesVilanova, GabrielaPandolfi, DanielSan Pedro, María Eugenia deVillagra, AndreaBain, María ElenaGallard, Raúl HectorCiencias InformáticasSolving the flow shop scheduling problemevolutionary approachesSchedulingARTIFICIAL INTELLIGENCEThe flow shop scheduling problem (FSSP) [12], has held the attention of many researchers. In a simplest usual situation, a set of jobs must follow the same route to be executed on a set of machines (resources) and the main objective is to optimize some performance variable (makespan, tardiness, lateness, etc.). In the case of the makespan, it have been proved that when the number of machines is greater than or equal to three, the problem is NP-hard.Eje: Inteligencia Computacional - MetaheurísticasRed de Universidades con Carreras en Informática (RedUNCI)2001-05info: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/10915/21670enginfo: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:UNLP2025-09-29T10:54:43Zoai:sedici.unlp.edu.ar:10915/21670Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:54:43.351SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Solving the flow shop scheduling problem under evolutionary approaches |
| title |
Solving the flow shop scheduling problem under evolutionary approaches |
| spellingShingle |
Solving the flow shop scheduling problem under evolutionary approaches Vilanova, Gabriela Ciencias Informáticas Solving the flow shop scheduling problem evolutionary approaches Scheduling ARTIFICIAL INTELLIGENCE |
| title_short |
Solving the flow shop scheduling problem under evolutionary approaches |
| title_full |
Solving the flow shop scheduling problem under evolutionary approaches |
| title_fullStr |
Solving the flow shop scheduling problem under evolutionary approaches |
| title_full_unstemmed |
Solving the flow shop scheduling problem under evolutionary approaches |
| title_sort |
Solving the flow shop scheduling problem under evolutionary approaches |
| dc.creator.none.fl_str_mv |
Vilanova, Gabriela Pandolfi, Daniel San Pedro, María Eugenia de Villagra, Andrea Bain, María Elena Gallard, Raúl Hector |
| author |
Vilanova, Gabriela |
| author_facet |
Vilanova, Gabriela Pandolfi, Daniel San Pedro, María Eugenia de Villagra, Andrea Bain, María Elena Gallard, Raúl Hector |
| author_role |
author |
| author2 |
Pandolfi, Daniel San Pedro, María Eugenia de Villagra, Andrea Bain, María Elena Gallard, Raúl Hector |
| author2_role |
author author author author author |
| dc.subject.none.fl_str_mv |
Ciencias Informáticas Solving the flow shop scheduling problem evolutionary approaches Scheduling ARTIFICIAL INTELLIGENCE |
| topic |
Ciencias Informáticas Solving the flow shop scheduling problem evolutionary approaches Scheduling ARTIFICIAL INTELLIGENCE |
| dc.description.none.fl_txt_mv |
The flow shop scheduling problem (FSSP) [12], has held the attention of many researchers. In a simplest usual situation, a set of jobs must follow the same route to be executed on a set of machines (resources) and the main objective is to optimize some performance variable (makespan, tardiness, lateness, etc.). In the case of the makespan, it have been proved that when the number of machines is greater than or equal to three, the problem is NP-hard. Eje: Inteligencia Computacional - Metaheurísticas Red de Universidades con Carreras en Informática (RedUNCI) |
| description |
The flow shop scheduling problem (FSSP) [12], has held the attention of many researchers. In a simplest usual situation, a set of jobs must follow the same route to be executed on a set of machines (resources) and the main objective is to optimize some performance variable (makespan, tardiness, lateness, etc.). In the case of the makespan, it have been proved that when the number of machines is greater than or equal to three, the problem is NP-hard. |
| publishDate |
2001 |
| dc.date.none.fl_str_mv |
2001-05 |
| 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/10915/21670 |
| url |
http://sedici.unlp.edu.ar/handle/10915/21670 |
| 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_ |
1844615805474439168 |
| score |
13.070432 |