MATHEMATICAL MODELLING AND SOLUTION APPROACHES FOR PRODUCTION PLANNING IN A CHEMICAL INDUSTRY
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa operacional (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382017000200311 |
Resumo: | ABSTRACT This paper addresses a lot sizing problem in a Brazilian chemical industry where a product can be produced by more than one process, which can use different parallel machines and may even consume a wide range of raw materials. Moreover, most of the products are liquids and the inventories must be kept in a restricted number of storage tanks with a limited capacity. Hence, these two issues are barely addressed in the literature on lot sizing. The classical multi-level capacitated lot sizing problem was extended to address them and a mixed integer programming (MIP) formulation was developed to determine how many batches should be produced and in which tank products should be stored to meet the demands and minimize production costs. The results of computational experiments show that the commercial solver found poor quality solutions or could not find feasible solutions within one hour. Thus, we applied relaxand-fix and fix-and-optimize MIP based heuristics and we observed that these heuristics were able to obtain feasible solutions for more instances in shorter computational times and find better solutions than those obtained by the commercial solver to solve the proposed model. |
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MATHEMATICAL MODELLING AND SOLUTION APPROACHES FOR PRODUCTION PLANNING IN A CHEMICAL INDUSTRYLot sizing problemMixed integer programming problemChemical industryRelax-and-fixFix-and-optimizeABSTRACT This paper addresses a lot sizing problem in a Brazilian chemical industry where a product can be produced by more than one process, which can use different parallel machines and may even consume a wide range of raw materials. Moreover, most of the products are liquids and the inventories must be kept in a restricted number of storage tanks with a limited capacity. Hence, these two issues are barely addressed in the literature on lot sizing. The classical multi-level capacitated lot sizing problem was extended to address them and a mixed integer programming (MIP) formulation was developed to determine how many batches should be produced and in which tank products should be stored to meet the demands and minimize production costs. The results of computational experiments show that the commercial solver found poor quality solutions or could not find feasible solutions within one hour. Thus, we applied relaxand-fix and fix-and-optimize MIP based heuristics and we observed that these heuristics were able to obtain feasible solutions for more instances in shorter computational times and find better solutions than those obtained by the commercial solver to solve the proposed model.Sociedade Brasileira de Pesquisa Operacional2017-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382017000200311Pesquisa Operacional v.37 n.2 2017reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2017.037.02.0311info:eu-repo/semantics/openAccessCunha,Artur LovatoSantos,Maristela Oliveiraeng2017-09-22T00:00:00Zoai:scielo:S0101-74382017000200311Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2017-09-22T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false |
dc.title.none.fl_str_mv |
MATHEMATICAL MODELLING AND SOLUTION APPROACHES FOR PRODUCTION PLANNING IN A CHEMICAL INDUSTRY |
title |
MATHEMATICAL MODELLING AND SOLUTION APPROACHES FOR PRODUCTION PLANNING IN A CHEMICAL INDUSTRY |
spellingShingle |
MATHEMATICAL MODELLING AND SOLUTION APPROACHES FOR PRODUCTION PLANNING IN A CHEMICAL INDUSTRY Cunha,Artur Lovato Lot sizing problem Mixed integer programming problem Chemical industry Relax-and-fix Fix-and-optimize |
title_short |
MATHEMATICAL MODELLING AND SOLUTION APPROACHES FOR PRODUCTION PLANNING IN A CHEMICAL INDUSTRY |
title_full |
MATHEMATICAL MODELLING AND SOLUTION APPROACHES FOR PRODUCTION PLANNING IN A CHEMICAL INDUSTRY |
title_fullStr |
MATHEMATICAL MODELLING AND SOLUTION APPROACHES FOR PRODUCTION PLANNING IN A CHEMICAL INDUSTRY |
title_full_unstemmed |
MATHEMATICAL MODELLING AND SOLUTION APPROACHES FOR PRODUCTION PLANNING IN A CHEMICAL INDUSTRY |
title_sort |
MATHEMATICAL MODELLING AND SOLUTION APPROACHES FOR PRODUCTION PLANNING IN A CHEMICAL INDUSTRY |
author |
Cunha,Artur Lovato |
author_facet |
Cunha,Artur Lovato Santos,Maristela Oliveira |
author_role |
author |
author2 |
Santos,Maristela Oliveira |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Cunha,Artur Lovato Santos,Maristela Oliveira |
dc.subject.por.fl_str_mv |
Lot sizing problem Mixed integer programming problem Chemical industry Relax-and-fix Fix-and-optimize |
topic |
Lot sizing problem Mixed integer programming problem Chemical industry Relax-and-fix Fix-and-optimize |
description |
ABSTRACT This paper addresses a lot sizing problem in a Brazilian chemical industry where a product can be produced by more than one process, which can use different parallel machines and may even consume a wide range of raw materials. Moreover, most of the products are liquids and the inventories must be kept in a restricted number of storage tanks with a limited capacity. Hence, these two issues are barely addressed in the literature on lot sizing. The classical multi-level capacitated lot sizing problem was extended to address them and a mixed integer programming (MIP) formulation was developed to determine how many batches should be produced and in which tank products should be stored to meet the demands and minimize production costs. The results of computational experiments show that the commercial solver found poor quality solutions or could not find feasible solutions within one hour. Thus, we applied relaxand-fix and fix-and-optimize MIP based heuristics and we observed that these heuristics were able to obtain feasible solutions for more instances in shorter computational times and find better solutions than those obtained by the commercial solver to solve the proposed model. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-08-01 |
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=S0101-74382017000200311 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382017000200311 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0101-7438.2017.037.02.0311 |
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 |
Sociedade Brasileira de Pesquisa Operacional |
publisher.none.fl_str_mv |
Sociedade Brasileira de Pesquisa Operacional |
dc.source.none.fl_str_mv |
Pesquisa Operacional v.37 n.2 2017 reponame:Pesquisa operacional (Online) instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) instacron:SOBRAPO |
instname_str |
Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) |
instacron_str |
SOBRAPO |
institution |
SOBRAPO |
reponame_str |
Pesquisa operacional (Online) |
collection |
Pesquisa operacional (Online) |
repository.name.fl_str_mv |
Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO) |
repository.mail.fl_str_mv |
||sobrapo@sobrapo.org.br |
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1750318018159706112 |