A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problem

Autores
Salto, Carolina; Minetti, Gabriela F.; Alfonso, Hugo; Gallard, Raúl Hector
Año de publicación
2000
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
A variety of optimization problems in fields such as production operations in manufacturing industry, parallel and distributed systems, logistics and traffic can be summarized within the general class of scheduling problems. A common feature of this problems is that they belong to the class of NP-complete problems, which means that no deterministic algorithm is known yet for solving them in polynomial time. The major advantage of evolutionary techniques resides in their ability of providing good solutions to extremely complex problems in reasonable time. This work introduces MCMP-PRB to face the Job Shop Scheduling Problem (JSSP). Enhancements include a multiplicity feature (MCMP) and a further hybridization with a conventional heuristic know as the priority dispatching rule.
I Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
evolutionary algorithms
chromosome representation
multiplicity
Scheduling
Optimization
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:10915/23430
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/23430
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problemSalto, CarolinaMinetti, Gabriela F.Alfonso, HugoGallard, Raúl HectorCiencias Informáticasevolutionary algorithmschromosome representationmultiplicitySchedulingOptimizationA variety of optimization problems in fields such as production operations in manufacturing industry, parallel and distributed systems, logistics and traffic can be summarized within the general class of scheduling problems. A common feature of this problems is that they belong to the class of NP-complete problems, which means that no deterministic algorithm is known yet for solving them in polynomial time. The major advantage of evolutionary techniques resides in their ability of providing good solutions to extremely complex problems in reasonable time. This work introduces MCMP-PRB to face the Job Shop Scheduling Problem (JSSP). Enhancements include a multiplicity feature (MCMP) and a further hybridization with a conventional heuristic know as the priority dispatching rule.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/10915/23430enginfo: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:UNLP2025-10-15T10:48:01Zoai:sedici.unlp.edu.ar:10915/23430Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 10:48:02.031SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problem
title A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problem
spellingShingle A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problem
Salto, Carolina
Ciencias Informáticas
evolutionary algorithms
chromosome representation
multiplicity
Scheduling
Optimization
title_short A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problem
title_full A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problem
title_fullStr A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problem
title_full_unstemmed A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problem
title_sort A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problem
dc.creator.none.fl_str_mv Salto, Carolina
Minetti, Gabriela F.
Alfonso, Hugo
Gallard, Raúl Hector
author Salto, Carolina
author_facet Salto, Carolina
Minetti, Gabriela F.
Alfonso, Hugo
Gallard, Raúl Hector
author_role author
author2 Minetti, Gabriela F.
Alfonso, Hugo
Gallard, Raúl Hector
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
evolutionary algorithms
chromosome representation
multiplicity
Scheduling
Optimization
topic Ciencias Informáticas
evolutionary algorithms
chromosome representation
multiplicity
Scheduling
Optimization
dc.description.none.fl_txt_mv A variety of optimization problems in fields such as production operations in manufacturing industry, parallel and distributed systems, logistics and traffic can be summarized within the general class of scheduling problems. A common feature of this problems is that they belong to the class of NP-complete problems, which means that no deterministic algorithm is known yet for solving them in polynomial time. The major advantage of evolutionary techniques resides in their ability of providing good solutions to extremely complex problems in reasonable time. This work introduces MCMP-PRB to face the Job Shop Scheduling Problem (JSSP). Enhancements include a multiplicity feature (MCMP) and a further hybridization with a conventional heuristic know as the priority dispatching rule.
I Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description A variety of optimization problems in fields such as production operations in manufacturing industry, parallel and distributed systems, logistics and traffic can be summarized within the general class of scheduling problems. A common feature of this problems is that they belong to the class of NP-complete problems, which means that no deterministic algorithm is known yet for solving them in polynomial time. The major advantage of evolutionary techniques resides in their ability of providing good solutions to extremely complex problems in reasonable time. This work introduces MCMP-PRB to face the Job Shop Scheduling Problem (JSSP). Enhancements include a multiplicity feature (MCMP) and a further hybridization with a conventional heuristic know as the priority dispatching rule.
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/10915/23430
url http://sedici.unlp.edu.ar/handle/10915/23430
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
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score 13.22299

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