Production sequencing in a flow shop system using optimization and heuristic algorithms

Detalhes bibliográficos
Autor(a) principal: Caicedo-Rolón Junior,Álvaro
Data de Publicação: 2021
Outros Autores: Llanos,John Wilmer Parra
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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spelling 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
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