Modeling and optimization of multi-layer aggregate production planning

Detalhes bibliográficos
Autor(a) principal: Aziz, Ridwan Al
Data de Publicação: 2018
Outros Autores: Paul, Himangshu Kumar, Karim, Touseef Mashrurul, Ahmed, Imtiaz, Azeem, Abdullahil
Tipo de documento: Artigo
Idioma: eng
Título da fonte: JOSCM. Journal of Operations and Supply Chain Management
Texto Completo: https://periodicos.fgv.br/joscm/article/view/67615
Resumo: Aggregate production planning has attracted the attention of researchers for quite a long time now; and the continued researches depict the significance and scope for improvement in this arena. Here, a multi-product, multi-level and multi-period model has been formulated to identify the required aggregate plan for meeting the forecast demand, by regulating production rates, inventory, workforce, various production costs, and other controllable variables. Several new contributing factors, such as costs related to material handling, raw material inventory and worker training have been included in the objective function and constraint equations to make the model more realistic. A case study has been presented for a cosmetics and toiletries manufacturer in Bangladesh. Eventually, the problem has been solved using Genetic Algorithm and Particle Swarm Optimization approach. The solution illustrates that the model can be applied in a real world scenario to enhance productivity and profitability.
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spelling Modeling and optimization of multi-layer aggregate production planningAggregate production planninginventory optimizationmulti-period modelinggenetic algorithmparticle swarm optimizationAggregate production planning has attracted the attention of researchers for quite a long time now; and the continued researches depict the significance and scope for improvement in this arena. Here, a multi-product, multi-level and multi-period model has been formulated to identify the required aggregate plan for meeting the forecast demand, by regulating production rates, inventory, workforce, various production costs, and other controllable variables. Several new contributing factors, such as costs related to material handling, raw material inventory and worker training have been included in the objective function and constraint equations to make the model more realistic. A case study has been presented for a cosmetics and toiletries manufacturer in Bangladesh. Eventually, the problem has been solved using Genetic Algorithm and Particle Swarm Optimization approach. The solution illustrates that the model can be applied in a real world scenario to enhance productivity and profitability.FGV EAESP2018-11-17info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.fgv.br/joscm/article/view/6761510.12660/joscmv11n2p1-15Journal of Operations and Supply Chain Management; Vol. 11 No. 2 (2018): July-December; 1-15Journal of Operations and Supply Chain Management; v. 11 n. 2 (2018): July-December; 1-151984-3046reponame:JOSCM. Journal of Operations and Supply Chain Managementinstname:Fundação Getulio Vargas (FGV)instacron:FGVenghttps://periodicos.fgv.br/joscm/article/view/67615/pdf_55Copyright (c) 2018 Journal of Operations and Supply Chain Managementinfo:eu-repo/semantics/openAccessAziz, Ridwan AlPaul, Himangshu KumarKarim, Touseef MashrurulAhmed, ImtiazAzeem, Abdullahil2019-02-15T18:21:48Zoai:ojs.periodicos.fgv.br:article/67615Revistahttp://bibliotecadigital.fgv.br/ojs/index.php/joscmPRIhttp://bibliotecadigital.fgv.br/ojs/index.php/joscm/oai||joscm@fgv.br1984-30461984-3046opendoar:2019-02-15T18:21:48JOSCM. Journal of Operations and Supply Chain Management - Fundação Getulio Vargas (FGV)false
dc.title.none.fl_str_mv Modeling and optimization of multi-layer aggregate production planning
title Modeling and optimization of multi-layer aggregate production planning
spellingShingle Modeling and optimization of multi-layer aggregate production planning
Aziz, Ridwan Al
Aggregate production planning
inventory optimization
multi-period modeling
genetic algorithm
particle swarm optimization
title_short Modeling and optimization of multi-layer aggregate production planning
title_full Modeling and optimization of multi-layer aggregate production planning
title_fullStr Modeling and optimization of multi-layer aggregate production planning
title_full_unstemmed Modeling and optimization of multi-layer aggregate production planning
title_sort Modeling and optimization of multi-layer aggregate production planning
author Aziz, Ridwan Al
author_facet Aziz, Ridwan Al
Paul, Himangshu Kumar
Karim, Touseef Mashrurul
Ahmed, Imtiaz
Azeem, Abdullahil
author_role author
author2 Paul, Himangshu Kumar
Karim, Touseef Mashrurul
Ahmed, Imtiaz
Azeem, Abdullahil
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Aziz, Ridwan Al
Paul, Himangshu Kumar
Karim, Touseef Mashrurul
Ahmed, Imtiaz
Azeem, Abdullahil
dc.subject.por.fl_str_mv Aggregate production planning
inventory optimization
multi-period modeling
genetic algorithm
particle swarm optimization
topic Aggregate production planning
inventory optimization
multi-period modeling
genetic algorithm
particle swarm optimization
description Aggregate production planning has attracted the attention of researchers for quite a long time now; and the continued researches depict the significance and scope for improvement in this arena. Here, a multi-product, multi-level and multi-period model has been formulated to identify the required aggregate plan for meeting the forecast demand, by regulating production rates, inventory, workforce, various production costs, and other controllable variables. Several new contributing factors, such as costs related to material handling, raw material inventory and worker training have been included in the objective function and constraint equations to make the model more realistic. A case study has been presented for a cosmetics and toiletries manufacturer in Bangladesh. Eventually, the problem has been solved using Genetic Algorithm and Particle Swarm Optimization approach. The solution illustrates that the model can be applied in a real world scenario to enhance productivity and profitability.
publishDate 2018
dc.date.none.fl_str_mv 2018-11-17
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.fgv.br/joscm/article/view/67615
10.12660/joscmv11n2p1-15
url https://periodicos.fgv.br/joscm/article/view/67615
identifier_str_mv 10.12660/joscmv11n2p1-15
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.fgv.br/joscm/article/view/67615/pdf_55
dc.rights.driver.fl_str_mv Copyright (c) 2018 Journal of Operations and Supply Chain Management
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2018 Journal of Operations and Supply Chain Management
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv FGV EAESP
publisher.none.fl_str_mv FGV EAESP
dc.source.none.fl_str_mv Journal of Operations and Supply Chain Management; Vol. 11 No. 2 (2018): July-December; 1-15
Journal of Operations and Supply Chain Management; v. 11 n. 2 (2018): July-December; 1-15
1984-3046
reponame:JOSCM. Journal of Operations and Supply Chain Management
instname:Fundação Getulio Vargas (FGV)
instacron:FGV
instname_str Fundação Getulio Vargas (FGV)
instacron_str FGV
institution FGV
reponame_str JOSCM. Journal of Operations and Supply Chain Management
collection JOSCM. Journal of Operations and Supply Chain Management
repository.name.fl_str_mv JOSCM. Journal of Operations and Supply Chain Management - Fundação Getulio Vargas (FGV)
repository.mail.fl_str_mv ||joscm@fgv.br
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