The role of different crossover methods when solving the open shop scheduling problem via a simple evolutionary approach

Autores
Beraudo, Vanina; Salto, Carolina; Alfonso, Hugo; Labarere, I.; Gallard, Raúl Hector
Año de publicación
2002
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The Open Shop Scheduling Problem (OSSP) is one of the most interesting, complexes and not frequently approached scheduling problems. Due to its intractability with other techniques, in this work we present an evolutionary approach to provide approximate solutions. One of the most important points in an Evolutionary Algorithm is to determine how to represent individuals of the evolving population and then to decide suitable genetic operators. In this work, we use permutations as chromosomes. Dealing with permutations requires appropriate crossover operators to ensure feasible offspring. Usual operators are partially-mapped, order, cycle and onecut- point crossover. The goal is to determine which is the most adequate for facing the OSSP with a simple evolutionary algorithm. Several known instances have been considered for testing in order to evaluate the algorithm behavior.
Eje: Sistemas inteligentes
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Scheduling
ARTIFICIAL INTELLIGENCE
Open Shop Scheduling
Evolutionary Computation
Crossover
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:10915/23018
Acceder
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network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling The role of different crossover methods when solving the open shop scheduling problem via a simple evolutionary approachBeraudo, VaninaSalto, CarolinaAlfonso, HugoLabarere, I.Gallard, Raúl HectorCiencias InformáticasSchedulingARTIFICIAL INTELLIGENCEOpen Shop SchedulingEvolutionary ComputationCrossoverThe Open Shop Scheduling Problem (OSSP) is one of the most interesting, complexes and not frequently approached scheduling problems. Due to its intractability with other techniques, in this work we present an evolutionary approach to provide approximate solutions. One of the most important points in an Evolutionary Algorithm is to determine how to represent individuals of the evolving population and then to decide suitable genetic operators. In this work, we use permutations as chromosomes. Dealing with permutations requires appropriate crossover operators to ensure feasible offspring. Usual operators are partially-mapped, order, cycle and onecut- point crossover. The goal is to determine which is the most adequate for facing the OSSP with a simple evolutionary algorithm. Several known instances have been considered for testing in order to evaluate the algorithm behavior.Eje: Sistemas inteligentesRed de Universidades con Carreras en Informática (RedUNCI)2002-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf600-608http://sedici.unlp.edu.ar/handle/10915/23018enginfo: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:UNLP2025-09-29T10:55:16Zoai:sedici.unlp.edu.ar:10915/23018Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:17.088SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv The role of different crossover methods when solving the open shop scheduling problem via a simple evolutionary approach
title The role of different crossover methods when solving the open shop scheduling problem via a simple evolutionary approach
spellingShingle The role of different crossover methods when solving the open shop scheduling problem via a simple evolutionary approach
Beraudo, Vanina
Ciencias Informáticas
Scheduling
ARTIFICIAL INTELLIGENCE
Open Shop Scheduling
Evolutionary Computation
Crossover
title_short The role of different crossover methods when solving the open shop scheduling problem via a simple evolutionary approach
title_full The role of different crossover methods when solving the open shop scheduling problem via a simple evolutionary approach
title_fullStr The role of different crossover methods when solving the open shop scheduling problem via a simple evolutionary approach
title_full_unstemmed The role of different crossover methods when solving the open shop scheduling problem via a simple evolutionary approach
title_sort The role of different crossover methods when solving the open shop scheduling problem via a simple evolutionary approach
dc.creator.none.fl_str_mv Beraudo, Vanina
Salto, Carolina
Alfonso, Hugo
Labarere, I.
Gallard, Raúl Hector
author Beraudo, Vanina
author_facet Beraudo, Vanina
Salto, Carolina
Alfonso, Hugo
Labarere, I.
Gallard, Raúl Hector
author_role author
author2 Salto, Carolina
Alfonso, Hugo
Labarere, I.
Gallard, Raúl Hector
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Scheduling
ARTIFICIAL INTELLIGENCE
Open Shop Scheduling
Evolutionary Computation
Crossover
topic Ciencias Informáticas
Scheduling
ARTIFICIAL INTELLIGENCE
Open Shop Scheduling
Evolutionary Computation
Crossover
dc.description.none.fl_txt_mv The Open Shop Scheduling Problem (OSSP) is one of the most interesting, complexes and not frequently approached scheduling problems. Due to its intractability with other techniques, in this work we present an evolutionary approach to provide approximate solutions. One of the most important points in an Evolutionary Algorithm is to determine how to represent individuals of the evolving population and then to decide suitable genetic operators. In this work, we use permutations as chromosomes. Dealing with permutations requires appropriate crossover operators to ensure feasible offspring. Usual operators are partially-mapped, order, cycle and onecut- point crossover. The goal is to determine which is the most adequate for facing the OSSP with a simple evolutionary algorithm. Several known instances have been considered for testing in order to evaluate the algorithm behavior.
Eje: Sistemas inteligentes
Red de Universidades con Carreras en Informática (RedUNCI)
description The Open Shop Scheduling Problem (OSSP) is one of the most interesting, complexes and not frequently approached scheduling problems. Due to its intractability with other techniques, in this work we present an evolutionary approach to provide approximate solutions. One of the most important points in an Evolutionary Algorithm is to determine how to represent individuals of the evolving population and then to decide suitable genetic operators. In this work, we use permutations as chromosomes. Dealing with permutations requires appropriate crossover operators to ensure feasible offspring. Usual operators are partially-mapped, order, cycle and onecut- point crossover. The goal is to determine which is the most adequate for facing the OSSP with a simple evolutionary algorithm. Several known instances have been considered for testing in order to evaluate the algorithm behavior.
publishDate 2002
dc.date.none.fl_str_mv 2002-10
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/10915/23018
url http://sedici.unlp.edu.ar/handle/10915/23018
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
600-608
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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