Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problem
Autor(a) principal: | |
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Data de Publicação: | 2016 |
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Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/s10479-015-2103-2 http://hdl.handle.net/11449/172588 |
Resumo: | The multiperiod cutting stock problem arises in the production planning and programming of many industries that have the cutting process as an important stage. Ordered items are required in different periods of a finite planning horizon. It is possible to bring forward or not the production of items. Unused inventory in a certain period becomes available for the next period, all together with new inventory which may come to be acquired in the market. Based on mixed integer optimization models from the literature, extensions are proposed to deal with the multiperiod case and a residual heuristic is used. Computational experiments showed that effective gains can be obtained when comparing multiperiod models with the lot for lot solution, which is typically used in practice. Most of the instances are solved satisfactorily with a high performance optimization package and the heuristic method is used for solving the hard instances. |
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Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problemCutting stock problemMathematical modelsMultiperiodResidual heuristicThe multiperiod cutting stock problem arises in the production planning and programming of many industries that have the cutting process as an important stage. Ordered items are required in different periods of a finite planning horizon. It is possible to bring forward or not the production of items. Unused inventory in a certain period becomes available for the next period, all together with new inventory which may come to be acquired in the market. Based on mixed integer optimization models from the literature, extensions are proposed to deal with the multiperiod case and a residual heuristic is used. Computational experiments showed that effective gains can be obtained when comparing multiperiod models with the lot for lot solution, which is typically used in practice. Most of the instances are solved satisfactorily with a high performance optimization package and the heuristic method is used for solving the hard instances.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Instituto de Matemática Estatística e Computação Científica-IMECC Universidade Estadual de Campinas-UNICAMP, Rua Sergio Buarque de Holanda, 651Departamento de Matemática Aplicada-DMAp Universidade Estadual Paulista-UNESP, Rua Cristóvão Colombo, 2265Departamento de Matemática Aplicada-DMAp Universidade Estadual Paulista-UNESP, Rua Cristóvão Colombo, 2265FAPESP: 2010/10133-0FAPESP: 2014/01203-5FAPESP: 2015/05193-7Universidade Estadual de Campinas (UNICAMP)Universidade Estadual Paulista (Unesp)Poldi, Kelly Cristinade Araujo, Silvio Alexandre [UNESP]2018-12-11T17:01:14Z2018-12-11T17:01:14Z2016-03-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article497-520application/pdfhttp://dx.doi.org/10.1007/s10479-015-2103-2Annals of Operations Research, v. 238, n. 1-2, p. 497-520, 2016.1572-93380254-5330http://hdl.handle.net/11449/17258810.1007/s10479-015-2103-22-s2.0-849591334322-s2.0-84959133432.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAnnals of Operations Research0,9430,943info:eu-repo/semantics/openAccess2024-01-22T06:25:35Zoai:repositorio.unesp.br:11449/172588Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:41:18.045880Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problem |
title |
Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problem |
spellingShingle |
Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problem Poldi, Kelly Cristina Cutting stock problem Mathematical models Multiperiod Residual heuristic |
title_short |
Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problem |
title_full |
Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problem |
title_fullStr |
Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problem |
title_full_unstemmed |
Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problem |
title_sort |
Mathematical models and a heuristic method for the multiperiod one-dimensional cutting stock problem |
author |
Poldi, Kelly Cristina |
author_facet |
Poldi, Kelly Cristina de Araujo, Silvio Alexandre [UNESP] |
author_role |
author |
author2 |
de Araujo, Silvio Alexandre [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual de Campinas (UNICAMP) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Poldi, Kelly Cristina de Araujo, Silvio Alexandre [UNESP] |
dc.subject.por.fl_str_mv |
Cutting stock problem Mathematical models Multiperiod Residual heuristic |
topic |
Cutting stock problem Mathematical models Multiperiod Residual heuristic |
description |
The multiperiod cutting stock problem arises in the production planning and programming of many industries that have the cutting process as an important stage. Ordered items are required in different periods of a finite planning horizon. It is possible to bring forward or not the production of items. Unused inventory in a certain period becomes available for the next period, all together with new inventory which may come to be acquired in the market. Based on mixed integer optimization models from the literature, extensions are proposed to deal with the multiperiod case and a residual heuristic is used. Computational experiments showed that effective gains can be obtained when comparing multiperiod models with the lot for lot solution, which is typically used in practice. Most of the instances are solved satisfactorily with a high performance optimization package and the heuristic method is used for solving the hard instances. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-03-01 2018-12-11T17:01:14Z 2018-12-11T17:01:14Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1007/s10479-015-2103-2 Annals of Operations Research, v. 238, n. 1-2, p. 497-520, 2016. 1572-9338 0254-5330 http://hdl.handle.net/11449/172588 10.1007/s10479-015-2103-2 2-s2.0-84959133432 2-s2.0-84959133432.pdf |
url |
http://dx.doi.org/10.1007/s10479-015-2103-2 http://hdl.handle.net/11449/172588 |
identifier_str_mv |
Annals of Operations Research, v. 238, n. 1-2, p. 497-520, 2016. 1572-9338 0254-5330 10.1007/s10479-015-2103-2 2-s2.0-84959133432 2-s2.0-84959133432.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Annals of Operations Research 0,943 0,943 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
497-520 application/pdf |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129543681081344 |