Production sequencing in a flow shop system using optimization and heuristic algorithms
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Gestão & Produção |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2021000100208 |
Resumo: | abstract: The purpose of the research was to determine the sequencing of the production of n jobs in m operations in a small footwear company in an environment of flow shop machine characteristics, which optimizes the total time of completion of the job in the production system (Makespan). We used heuristic algorithms that were applied through Lekin and WinQSB softwares, and for the optimization algorithm we designed a mathematical model that was solved by Juliabox software. Results show that the integer linear programming and local search minimize the makespan with 3807 minutes, and different production sequences for each algorithm, which consider permutation, which improves the traditional way of programming the production in 97 minutes, however, the optimization presents better results in the performance measures of average waiting time, average time of flow, and average job in process. Application of heuristic algorithms proves to be simple and fast, but the mathematical model of optimization designed and encoded in the software is a flexible and valuable tool for decision making in production programming, which could be applied in other footwear companies, and in other productive sectors whose companies have the same characteristics of the case study, reducing costs and improving delivery times. |
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Gestão & Produção |
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Production sequencing in a flow shop system using optimization and heuristic algorithmsFlow shopHeuristicsOperations researchOptimizationInteger linear programmingProduction sequencingabstract: The purpose of the research was to determine the sequencing of the production of n jobs in m operations in a small footwear company in an environment of flow shop machine characteristics, which optimizes the total time of completion of the job in the production system (Makespan). We used heuristic algorithms that were applied through Lekin and WinQSB softwares, and for the optimization algorithm we designed a mathematical model that was solved by Juliabox software. Results show that the integer linear programming and local search minimize the makespan with 3807 minutes, and different production sequences for each algorithm, which consider permutation, which improves the traditional way of programming the production in 97 minutes, however, the optimization presents better results in the performance measures of average waiting time, average time of flow, and average job in process. Application of heuristic algorithms proves to be simple and fast, but the mathematical model of optimization designed and encoded in the software is a flexible and valuable tool for decision making in production programming, which could be applied in other footwear companies, and in other productive sectors whose companies have the same characteristics of the case study, reducing costs and improving delivery times.Universidade Federal de São Carlos2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2021000100208Gestão & Produção v.28 n.1 2021reponame:Gestão & Produçãoinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCAR10.1590/1806-9649.2020v28e3886info:eu-repo/semantics/openAccessCaicedo-Rolón Junior,ÁlvaroLlanos,John Wilmer Parraeng2021-03-29T00:00:00Zoai:scielo:S0104-530X2021000100208Revistahttps://www.gestaoeproducao.com/PUBhttps://old.scielo.br/oai/scielo-oai.phpgp@dep.ufscar.br||revistagestaoemanalise@unichristus.edu.br1806-96490104-530Xopendoar:2021-03-29T00:00Gestão & Produção - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.none.fl_str_mv |
Production sequencing in a flow shop system using optimization and heuristic algorithms |
title |
Production sequencing in a flow shop system using optimization and heuristic algorithms |
spellingShingle |
Production sequencing in a flow shop system using optimization and heuristic algorithms Caicedo-Rolón Junior,Álvaro Flow shop Heuristics Operations research Optimization Integer linear programming Production sequencing |
title_short |
Production sequencing in a flow shop system using optimization and heuristic algorithms |
title_full |
Production sequencing in a flow shop system using optimization and heuristic algorithms |
title_fullStr |
Production sequencing in a flow shop system using optimization and heuristic algorithms |
title_full_unstemmed |
Production sequencing in a flow shop system using optimization and heuristic algorithms |
title_sort |
Production sequencing in a flow shop system using optimization and heuristic algorithms |
author |
Caicedo-Rolón Junior,Álvaro |
author_facet |
Caicedo-Rolón Junior,Álvaro Llanos,John Wilmer Parra |
author_role |
author |
author2 |
Llanos,John Wilmer Parra |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Caicedo-Rolón Junior,Álvaro Llanos,John Wilmer Parra |
dc.subject.por.fl_str_mv |
Flow shop Heuristics Operations research Optimization Integer linear programming Production sequencing |
topic |
Flow shop Heuristics Operations research Optimization Integer linear programming Production sequencing |
description |
abstract: The purpose of the research was to determine the sequencing of the production of n jobs in m operations in a small footwear company in an environment of flow shop machine characteristics, which optimizes the total time of completion of the job in the production system (Makespan). We used heuristic algorithms that were applied through Lekin and WinQSB softwares, and for the optimization algorithm we designed a mathematical model that was solved by Juliabox software. Results show that the integer linear programming and local search minimize the makespan with 3807 minutes, and different production sequences for each algorithm, which consider permutation, which improves the traditional way of programming the production in 97 minutes, however, the optimization presents better results in the performance measures of average waiting time, average time of flow, and average job in process. Application of heuristic algorithms proves to be simple and fast, but the mathematical model of optimization designed and encoded in the software is a flexible and valuable tool for decision making in production programming, which could be applied in other footwear companies, and in other productive sectors whose companies have the same characteristics of the case study, reducing costs and improving delivery times. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2021000100208 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2021000100208 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1806-9649.2020v28e3886 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Universidade Federal de São Carlos |
publisher.none.fl_str_mv |
Universidade Federal de São Carlos |
dc.source.none.fl_str_mv |
Gestão & Produção v.28 n.1 2021 reponame:Gestão & Produção instname:Universidade Federal de São Carlos (UFSCAR) instacron:UFSCAR |
instname_str |
Universidade Federal de São Carlos (UFSCAR) |
instacron_str |
UFSCAR |
institution |
UFSCAR |
reponame_str |
Gestão & Produção |
collection |
Gestão & Produção |
repository.name.fl_str_mv |
Gestão & Produção - Universidade Federal de São Carlos (UFSCAR) |
repository.mail.fl_str_mv |
gp@dep.ufscar.br||revistagestaoemanalise@unichristus.edu.br |
_version_ |
1750118207890391040 |