CAPACITATED LOT SIZING AND SCHEDULING WITH ORDER ACCEPTANCE AND DELIVERY TIME WINDOWS: MATHEMATICAL MODEL AND A MIP-BASED HEURISTIC
Autor(a) principal: | |
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Data de Publicação: | 2019 |
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=S0101-74382019000300471 |
Resumo: | ABSTRACT This research addresses a lot sizing and scheduling problem inspired by a real-world production environment where the customers make advanced orders and the industry need to decide which orders will be accepted with the aim of maximizing the profit respecting the production capacity constraints. Orders are composed of different types of items which must be delivered within a given time interval and, moreover, such orders cannot be split. A mixed integer programming (MIP) model is proposed to represent the problem and a MIP-based heuristic is also proposed to deliver good solutions at an acceptable computational time. The heuristic is composed of three phases (construction, deterministic improvement and stochastic improvement phases) and combines relax-and-fix, fix-and-optimize, and iterative MIP based neighborhood search procedures. Computational tests are presented in order to study the efficiency of the proposed approaches. |
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CAPACITATED LOT SIZING AND SCHEDULING WITH ORDER ACCEPTANCE AND DELIVERY TIME WINDOWS: MATHEMATICAL MODEL AND A MIP-BASED HEURISTICLot sizing and schedulingorder acceptanceMIP-based heuristicsABSTRACT This research addresses a lot sizing and scheduling problem inspired by a real-world production environment where the customers make advanced orders and the industry need to decide which orders will be accepted with the aim of maximizing the profit respecting the production capacity constraints. Orders are composed of different types of items which must be delivered within a given time interval and, moreover, such orders cannot be split. A mixed integer programming (MIP) model is proposed to represent the problem and a MIP-based heuristic is also proposed to deliver good solutions at an acceptable computational time. The heuristic is composed of three phases (construction, deterministic improvement and stochastic improvement phases) and combines relax-and-fix, fix-and-optimize, and iterative MIP based neighborhood search procedures. Computational tests are presented in order to study the efficiency of the proposed approaches.Sociedade Brasileira de Pesquisa Operacional2019-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382019000300471Pesquisa Operacional v.39 n.3 2019reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2019.039.03.0471info:eu-repo/semantics/openAccessSoler,Willy A. de OliveiraPoldi,Kelly C.Santos,Maristela O.eng2019-11-29T00:00:00Zoai:scielo:S0101-74382019000300471Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2019-11-29T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false |
dc.title.none.fl_str_mv |
CAPACITATED LOT SIZING AND SCHEDULING WITH ORDER ACCEPTANCE AND DELIVERY TIME WINDOWS: MATHEMATICAL MODEL AND A MIP-BASED HEURISTIC |
title |
CAPACITATED LOT SIZING AND SCHEDULING WITH ORDER ACCEPTANCE AND DELIVERY TIME WINDOWS: MATHEMATICAL MODEL AND A MIP-BASED HEURISTIC |
spellingShingle |
CAPACITATED LOT SIZING AND SCHEDULING WITH ORDER ACCEPTANCE AND DELIVERY TIME WINDOWS: MATHEMATICAL MODEL AND A MIP-BASED HEURISTIC Soler,Willy A. de Oliveira Lot sizing and scheduling order acceptance MIP-based heuristics |
title_short |
CAPACITATED LOT SIZING AND SCHEDULING WITH ORDER ACCEPTANCE AND DELIVERY TIME WINDOWS: MATHEMATICAL MODEL AND A MIP-BASED HEURISTIC |
title_full |
CAPACITATED LOT SIZING AND SCHEDULING WITH ORDER ACCEPTANCE AND DELIVERY TIME WINDOWS: MATHEMATICAL MODEL AND A MIP-BASED HEURISTIC |
title_fullStr |
CAPACITATED LOT SIZING AND SCHEDULING WITH ORDER ACCEPTANCE AND DELIVERY TIME WINDOWS: MATHEMATICAL MODEL AND A MIP-BASED HEURISTIC |
title_full_unstemmed |
CAPACITATED LOT SIZING AND SCHEDULING WITH ORDER ACCEPTANCE AND DELIVERY TIME WINDOWS: MATHEMATICAL MODEL AND A MIP-BASED HEURISTIC |
title_sort |
CAPACITATED LOT SIZING AND SCHEDULING WITH ORDER ACCEPTANCE AND DELIVERY TIME WINDOWS: MATHEMATICAL MODEL AND A MIP-BASED HEURISTIC |
author |
Soler,Willy A. de Oliveira |
author_facet |
Soler,Willy A. de Oliveira Poldi,Kelly C. Santos,Maristela O. |
author_role |
author |
author2 |
Poldi,Kelly C. Santos,Maristela O. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Soler,Willy A. de Oliveira Poldi,Kelly C. Santos,Maristela O. |
dc.subject.por.fl_str_mv |
Lot sizing and scheduling order acceptance MIP-based heuristics |
topic |
Lot sizing and scheduling order acceptance MIP-based heuristics |
description |
ABSTRACT This research addresses a lot sizing and scheduling problem inspired by a real-world production environment where the customers make advanced orders and the industry need to decide which orders will be accepted with the aim of maximizing the profit respecting the production capacity constraints. Orders are composed of different types of items which must be delivered within a given time interval and, moreover, such orders cannot be split. A mixed integer programming (MIP) model is proposed to represent the problem and a MIP-based heuristic is also proposed to deliver good solutions at an acceptable computational time. The heuristic is composed of three phases (construction, deterministic improvement and stochastic improvement phases) and combines relax-and-fix, fix-and-optimize, and iterative MIP based neighborhood search procedures. Computational tests are presented in order to study the efficiency of the proposed approaches. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-01 |
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=S0101-74382019000300471 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382019000300471 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0101-7438.2019.039.03.0471 |
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.39 n.3 2019 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 |
_version_ |
1750318018275049472 |