Operation Skipping Flow Shop Scheduling and Industry 4.0

Autores
Rossit, Daniel Alejandro; Toncovich, Adrián Andrés; Rossit, Diego Gabriel; Nesmachnow, Sergio
Año de publicación
2020
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Industry 4.0 is a modern approach where the connectivity between different stages of the production process and the consumers is enhanced. In this paper a relevant problem for both Industry 4.0 and flow shop literature is addressed: an operation skipping flow shop scheduling problem. A solution method to optimize total tardiness, which is novel to the related literature, is presented. The solution approach consists of two stages. In the first stage, a genetic algorithm is applied to obtain an efficient solution in a permutation fashion. In the second stage, the solution obtained in the previous stage is improved with a simulated annealing algorithm considering a non-permutation strategy. Results show that NPFS solutions outperform PFS solutions for this problem. Furthermore, if the percentage of skipping operations increases the impact of the NPFS approach increases too.
Fil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Toncovich, Adrián Andrés. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Nesmachnow, Sergio. Universidad de la República; Uruguay
International Conference of Production Research-Americas (ICPR-Americas)
Bahía Blanca
Argentina
Universidad Nacional del Sur
Materia
INDUSTRY 4.0
NON-PERMUTATION FLOW SHOP
SKIPPING OPERATIONS
CYBER-PHYSICAL SYSTEM
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/147139
Acceder
id CONICETDig_d4783af251736d58fc09c120b00d8b3a
oai_identifier_str oai:ri.conicet.gov.ar:11336/147139
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Operation Skipping Flow Shop Scheduling and Industry 4.0Rossit, Daniel AlejandroToncovich, Adrián AndrésRossit, Diego GabrielNesmachnow, SergioINDUSTRY 4.0NON-PERMUTATION FLOW SHOPSKIPPING OPERATIONSCYBER-PHYSICAL SYSTEMhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2Industry 4.0 is a modern approach where the connectivity between different stages of the production process and the consumers is enhanced. In this paper a relevant problem for both Industry 4.0 and flow shop literature is addressed: an operation skipping flow shop scheduling problem. A solution method to optimize total tardiness, which is novel to the related literature, is presented. The solution approach consists of two stages. In the first stage, a genetic algorithm is applied to obtain an efficient solution in a permutation fashion. In the second stage, the solution obtained in the previous stage is improved with a simulated annealing algorithm considering a non-permutation strategy. Results show that NPFS solutions outperform PFS solutions for this problem. Furthermore, if the percentage of skipping operations increases the impact of the NPFS approach increases too.Fil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Toncovich, Adrián Andrés. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Nesmachnow, Sergio. Universidad de la República; UruguayInternational Conference of Production Research-Americas (ICPR-Americas)Bahía BlancaArgentinaUniversidad Nacional del SurUniversidad Nacional del Sur2020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectConferenciaJournalhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/147139Operation Skipping Flow Shop Scheduling and Industry 4.0; International Conference of Production Research-Americas (ICPR-Americas); Bahía Blanca; Argentina; 2020; 1212-12212619-1865CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.matematica.uns.edu.ar/ipcra/pdf/icpr_americas_2020_proceedings.pdfInternacionalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:11:50Zoai:ri.conicet.gov.ar:11336/147139instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:11:51.088CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Operation Skipping Flow Shop Scheduling and Industry 4.0
title Operation Skipping Flow Shop Scheduling and Industry 4.0
spellingShingle Operation Skipping Flow Shop Scheduling and Industry 4.0
Rossit, Daniel Alejandro
INDUSTRY 4.0
NON-PERMUTATION FLOW SHOP
SKIPPING OPERATIONS
CYBER-PHYSICAL SYSTEM
title_short Operation Skipping Flow Shop Scheduling and Industry 4.0
title_full Operation Skipping Flow Shop Scheduling and Industry 4.0
title_fullStr Operation Skipping Flow Shop Scheduling and Industry 4.0
title_full_unstemmed Operation Skipping Flow Shop Scheduling and Industry 4.0
title_sort Operation Skipping Flow Shop Scheduling and Industry 4.0
dc.creator.none.fl_str_mv Rossit, Daniel Alejandro
Toncovich, Adrián Andrés
Rossit, Diego Gabriel
Nesmachnow, Sergio
author Rossit, Daniel Alejandro
author_facet Rossit, Daniel Alejandro
Toncovich, Adrián Andrés
Rossit, Diego Gabriel
Nesmachnow, Sergio
author_role author
author2 Toncovich, Adrián Andrés
Rossit, Diego Gabriel
Nesmachnow, Sergio
author2_role author
author
author
dc.subject.none.fl_str_mv INDUSTRY 4.0
NON-PERMUTATION FLOW SHOP
SKIPPING OPERATIONS
CYBER-PHYSICAL SYSTEM
topic INDUSTRY 4.0
NON-PERMUTATION FLOW SHOP
SKIPPING OPERATIONS
CYBER-PHYSICAL SYSTEM
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Industry 4.0 is a modern approach where the connectivity between different stages of the production process and the consumers is enhanced. In this paper a relevant problem for both Industry 4.0 and flow shop literature is addressed: an operation skipping flow shop scheduling problem. A solution method to optimize total tardiness, which is novel to the related literature, is presented. The solution approach consists of two stages. In the first stage, a genetic algorithm is applied to obtain an efficient solution in a permutation fashion. In the second stage, the solution obtained in the previous stage is improved with a simulated annealing algorithm considering a non-permutation strategy. Results show that NPFS solutions outperform PFS solutions for this problem. Furthermore, if the percentage of skipping operations increases the impact of the NPFS approach increases too.
Fil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Toncovich, Adrián Andrés. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Nesmachnow, Sergio. Universidad de la República; Uruguay
International Conference of Production Research-Americas (ICPR-Americas)
Bahía Blanca
Argentina
Universidad Nacional del Sur
description Industry 4.0 is a modern approach where the connectivity between different stages of the production process and the consumers is enhanced. In this paper a relevant problem for both Industry 4.0 and flow shop literature is addressed: an operation skipping flow shop scheduling problem. A solution method to optimize total tardiness, which is novel to the related literature, is presented. The solution approach consists of two stages. In the first stage, a genetic algorithm is applied to obtain an efficient solution in a permutation fashion. In the second stage, the solution obtained in the previous stage is improved with a simulated annealing algorithm considering a non-permutation strategy. Results show that NPFS solutions outperform PFS solutions for this problem. Furthermore, if the percentage of skipping operations increases the impact of the NPFS approach increases too.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
Conferencia
Journal
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
status_str publishedVersion
format conferenceObject
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/147139
Operation Skipping Flow Shop Scheduling and Industry 4.0; International Conference of Production Research-Americas (ICPR-Americas); Bahía Blanca; Argentina; 2020; 1212-1221
2619-1865
CONICET Digital
CONICET
url http://hdl.handle.net/11336/147139
identifier_str_mv Operation Skipping Flow Shop Scheduling and Industry 4.0; International Conference of Production Research-Americas (ICPR-Americas); Bahía Blanca; Argentina; 2020; 1212-1221
2619-1865
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.matematica.uns.edu.ar/ipcra/pdf/icpr_americas_2020_proceedings.pdf
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.coverage.none.fl_str_mv Internacional
dc.publisher.none.fl_str_mv Universidad Nacional del Sur
publisher.none.fl_str_mv Universidad Nacional del Sur
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842270172899966976
score 13.13397

Publicaciones similares