The scheduling algorithms for two-stage grid models
This paper deals with the scheduling of parallel works in a two-stage hierarchical grid. In this configuration, one of the great challenges is to assign the tasks in order to allow an efficient use of resources, while satisfying other criteria. In general, the optimization criteria are often in conf...
- Autores:
-
amelec, viloria
Pineda Lezama, Omar Bonerge
Martínez, Karol
Mercado Caruso, Nohora
- Tipo de recurso:
- http://purl.org/coar/resource_type/c_816b
- Fecha de publicación:
- 2021
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/8300
- Acceso en línea:
- https://hdl.handle.net/11323/8300
https://repositorio.cuc.edu.co/
- Palabra clave:
- Algorithms
Programming
Genetic algorithm
- Rights
- openAccess
- License
- CC0 1.0 Universal
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| dc.title.eng.fl_str_mv |
The scheduling algorithms for two-stage grid models |
| title |
The scheduling algorithms for two-stage grid models |
| spellingShingle |
The scheduling algorithms for two-stage grid models Algorithms Programming Genetic algorithm |
| title_short |
The scheduling algorithms for two-stage grid models |
| title_full |
The scheduling algorithms for two-stage grid models |
| title_fullStr |
The scheduling algorithms for two-stage grid models |
| title_full_unstemmed |
The scheduling algorithms for two-stage grid models |
| title_sort |
The scheduling algorithms for two-stage grid models |
| dc.creator.fl_str_mv |
amelec, viloria Pineda Lezama, Omar Bonerge Martínez, Karol Mercado Caruso, Nohora |
| dc.contributor.author.spa.fl_str_mv |
amelec, viloria Pineda Lezama, Omar Bonerge Martínez, Karol Mercado Caruso, Nohora |
| dc.subject.eng.fl_str_mv |
Algorithms Programming Genetic algorithm |
| topic |
Algorithms Programming Genetic algorithm |
| description |
This paper deals with the scheduling of parallel works in a two-stage hierarchical grid. In this configuration, one of the great challenges is to assign the tasks in order to allow an efficient use of resources, while satisfying other criteria. In general, the optimization criteria are often in conflict. For solving this problem, a bi-objective genetic algorithm is proposed presenting an experimental study of six cross operators, and three mutation operators. The most influential parameters are determined through a statistical analysis of multifactorial variance which compares the proposal with five allocation strategies found in the literature. |
| publishDate |
2021 |
| dc.date.accessioned.none.fl_str_mv |
2021-05-31T16:03:41Z |
| dc.date.available.none.fl_str_mv |
2021-05-31T16:03:41Z |
| dc.date.issued.none.fl_str_mv |
2021 |
| dc.type.spa.fl_str_mv |
Pre-Publicación |
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http://purl.org/coar/resource_type/c_816b |
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Text |
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info:eu-repo/semantics/preprint |
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http://purl.org/redcol/resource_type/ARTOTR |
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info:eu-repo/semantics/acceptedVersion |
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http://purl.org/coar/resource_type/c_816b |
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acceptedVersion |
| dc.identifier.issn.spa.fl_str_mv |
1876-1100 1876-1119 |
| dc.identifier.uri.spa.fl_str_mv |
https://hdl.handle.net/11323/8300 |
| dc.identifier.doi.spa.fl_str_mv |
DOI:10.1007/978-981-15-9019-1_40 |
| dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
| dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
| identifier_str_mv |
1876-1100 1876-1119 DOI:10.1007/978-981-15-9019-1_40 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
| url |
https://hdl.handle.net/11323/8300 https://repositorio.cuc.edu.co/ |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.rights.spa.fl_str_mv |
CC0 1.0 Universal |
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http://creativecommons.org/publicdomain/zero/1.0/ |
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info:eu-repo/semantics/openAccess |
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CC0 1.0 Universal http://creativecommons.org/publicdomain/zero/1.0/ http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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application/pdf |
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Corporación Universidad de la Costa |
| dc.source.spa.fl_str_mv |
Lecture Notes in Electrical Engineering |
| institution |
Corporación Universidad de la Costa |
| dc.source.url.spa.fl_str_mv |
https://www.springerprofessional.de/en/the-scheduling-algorithms-for-two-stage-grid-models/18909628 |
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amelec, viloriaPineda Lezama, Omar BonergeMartínez, KarolMercado Caruso, Nohora2021-05-31T16:03:41Z2021-05-31T16:03:41Z20211876-11001876-1119https://hdl.handle.net/11323/8300DOI:10.1007/978-981-15-9019-1_40Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/This paper deals with the scheduling of parallel works in a two-stage hierarchical grid. In this configuration, one of the great challenges is to assign the tasks in order to allow an efficient use of resources, while satisfying other criteria. In general, the optimization criteria are often in conflict. For solving this problem, a bi-objective genetic algorithm is proposed presenting an experimental study of six cross operators, and three mutation operators. The most influential parameters are determined through a statistical analysis of multifactorial variance which compares the proposal with five allocation strategies found in the literature.amelec, viloria-will be generated-orcid-0000-0003-2673-6350-600Pineda Lezama, Omar BonergeMartínez, KarolMercado Caruso, Nohora-will be generated-orcid-0000-0001-9261-8331-600application/pdfengCorporación Universidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Lecture Notes in Electrical Engineeringhttps://www.springerprofessional.de/en/the-scheduling-algorithms-for-two-stage-grid-models/18909628AlgorithmsProgrammingGenetic algorithmThe scheduling algorithms for two-stage grid modelsPre-Publicaciónhttp://purl.org/coar/resource_type/c_816bTextinfo:eu-repo/semantics/preprinthttp://purl.org/redcol/resource_type/ARTOTRinfo:eu-repo/semantics/acceptedVersionPublicationORIGINALThe Scheduling Algorithms 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