Multirecombinated evolutionary algorithms to solve multiobjective job shop scheduling

Autores
Esquivel, Susana Cecilia; Ferrero, Sergio W.; Gallard, Raúl Hector
Año de publicación
2000
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Multiobjective optimization, also known as vector-valued criteria or multicriteria optimization, have long been used in many application areas where a problem involves multiple objectives, often conflicting, to be met or optimized. Scheduling problems is one of such application areas whose importance lays on its economical impact and its complexity. The present paper propases CPS-MCPC, a cooperative population search method with multiple crossovers per couple. The cooperati ve search CPS is implemented with in di viduals of a single population, which are selected for recombination using alternatively each criterion. MCPC a multirecombination approach is used to exploit good features of both selected parents. To test the potentials of the novel method for building the Pareto front regular and non-regular objectives functions were chosen: the makespan and the mean absolute deviation of job completion times from a common due date (an earliness/ tardiness related problem). The set of experiments conducted, used three basic representation schemes and contrasted results of the proposed approach against conventional methods of recombination. Details of implementation and results are discussed.
I Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
evolutionary computation
job shop scheduling
multiobjective optimization
multirecombination
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:10915/23418

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spelling Multirecombinated evolutionary algorithms to solve multiobjective job shop schedulingEsquivel, Susana CeciliaFerrero, Sergio W.Gallard, Raúl HectorCiencias Informáticasevolutionary computationjob shop schedulingmultiobjective optimizationmultirecombinationMultiobjective optimization, also known as vector-valued criteria or multicriteria optimization, have long been used in many application areas where a problem involves multiple objectives, often conflicting, to be met or optimized. Scheduling problems is one of such application areas whose importance lays on its economical impact and its complexity. The present paper propases CPS-MCPC, a cooperative population search method with multiple crossovers per couple. The cooperati ve search CPS is implemented with in di viduals of a single population, which are selected for recombination using alternatively each criterion. MCPC a multirecombination approach is used to exploit good features of both selected parents. To test the potentials of the novel method for building the Pareto front regular and non-regular objectives functions were chosen: the makespan and the mean absolute deviation of job completion times from a common due date (an earliness/ tardiness related problem). The set of experiments conducted, used three basic representation schemes and contrasted results of the proposed approach against conventional methods of recombination. Details of implementation and results are discussed.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/10915/23418enginfo: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:10915/23418Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:28:17.164SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Multirecombinated evolutionary algorithms to solve multiobjective job shop scheduling
title Multirecombinated evolutionary algorithms to solve multiobjective job shop scheduling
spellingShingle Multirecombinated evolutionary algorithms to solve multiobjective job shop scheduling
Esquivel, Susana Cecilia
Ciencias Informáticas
evolutionary computation
job shop scheduling
multiobjective optimization
multirecombination
title_short Multirecombinated evolutionary algorithms to solve multiobjective job shop scheduling
title_full Multirecombinated evolutionary algorithms to solve multiobjective job shop scheduling
title_fullStr Multirecombinated evolutionary algorithms to solve multiobjective job shop scheduling
title_full_unstemmed Multirecombinated evolutionary algorithms to solve multiobjective job shop scheduling
title_sort Multirecombinated evolutionary algorithms to solve multiobjective job shop scheduling
dc.creator.none.fl_str_mv Esquivel, Susana Cecilia
Ferrero, Sergio W.
Gallard, Raúl Hector
author Esquivel, Susana Cecilia
author_facet Esquivel, Susana Cecilia
Ferrero, Sergio W.
Gallard, Raúl Hector
author_role author
author2 Ferrero, Sergio W.
Gallard, Raúl Hector
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
evolutionary computation
job shop scheduling
multiobjective optimization
multirecombination
topic Ciencias Informáticas
evolutionary computation
job shop scheduling
multiobjective optimization
multirecombination
dc.description.none.fl_txt_mv Multiobjective optimization, also known as vector-valued criteria or multicriteria optimization, have long been used in many application areas where a problem involves multiple objectives, often conflicting, to be met or optimized. Scheduling problems is one of such application areas whose importance lays on its economical impact and its complexity. The present paper propases CPS-MCPC, a cooperative population search method with multiple crossovers per couple. The cooperati ve search CPS is implemented with in di viduals of a single population, which are selected for recombination using alternatively each criterion. MCPC a multirecombination approach is used to exploit good features of both selected parents. To test the potentials of the novel method for building the Pareto front regular and non-regular objectives functions were chosen: the makespan and the mean absolute deviation of job completion times from a common due date (an earliness/ tardiness related problem). The set of experiments conducted, used three basic representation schemes and contrasted results of the proposed approach against conventional methods of recombination. Details of implementation and results are discussed.
I Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description Multiobjective optimization, also known as vector-valued criteria or multicriteria optimization, have long been used in many application areas where a problem involves multiple objectives, often conflicting, to be met or optimized. Scheduling problems is one of such application areas whose importance lays on its economical impact and its complexity. The present paper propases CPS-MCPC, a cooperative population search method with multiple crossovers per couple. The cooperati ve search CPS is implemented with in di viduals of a single population, which are selected for recombination using alternatively each criterion. MCPC a multirecombination approach is used to exploit good features of both selected parents. To test the potentials of the novel method for building the Pareto front regular and non-regular objectives functions were chosen: the makespan and the mean absolute deviation of job completion times from a common due date (an earliness/ tardiness related problem). The set of experiments conducted, used three basic representation schemes and contrasted results of the proposed approach against conventional methods of recombination. Details of implementation and results are discussed.
publishDate 2000
dc.date.none.fl_str_mv 2000-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/23418
url http://sedici.unlp.edu.ar/handle/10915/23418
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)
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