Nonlinear cutting stock problem model to minimize the number of different patterns and objects

Detalhes bibliográficos
Autor(a) principal: Moretti,Antonio Carlos
Data de Publicação: 2008
Outros Autores: Salles Neto,Luiz Leduíno de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Computational & Applied Mathematics
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022008000100004
Resumo: In this article we solve a nonlinear cutting stock problem which represents a cutting stock problem that considers the minimization of, both, the number of objects used and setup. We use a linearization of the nonlinear objective function to make possible the generation of good columns with the Gilmore and Gomory procedure. Each time a new column is added to the problem, we solve the original nonlinear problem by an Augmented Lagrangian method. This process is repeated until no more profitable columns is generated by Gilmore and Gomory technique. Finally, we apply a simple heuristic to obtain an integral solution for the original nonlinear integer problem.
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spelling Nonlinear cutting stock problem model to minimize the number of different patterns and objectscutting problemnonlinear programmingcolumn generationIn this article we solve a nonlinear cutting stock problem which represents a cutting stock problem that considers the minimization of, both, the number of objects used and setup. We use a linearization of the nonlinear objective function to make possible the generation of good columns with the Gilmore and Gomory procedure. Each time a new column is added to the problem, we solve the original nonlinear problem by an Augmented Lagrangian method. This process is repeated until no more profitable columns is generated by Gilmore and Gomory technique. Finally, we apply a simple heuristic to obtain an integral solution for the original nonlinear integer problem.Sociedade Brasileira de Matemática Aplicada e Computacional2008-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022008000100004Computational & Applied Mathematics v.27 n.1 2008reponame:Computational & Applied Mathematicsinstname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)instacron:SBMACinfo:eu-repo/semantics/openAccessMoretti,Antonio CarlosSalles Neto,Luiz Leduíno deeng2008-04-02T00:00:00Zoai:scielo:S1807-03022008000100004Revistahttps://www.scielo.br/j/cam/ONGhttps://old.scielo.br/oai/scielo-oai.php||sbmac@sbmac.org.br1807-03022238-3603opendoar:2008-04-02T00:00Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)false
dc.title.none.fl_str_mv Nonlinear cutting stock problem model to minimize the number of different patterns and objects
title Nonlinear cutting stock problem model to minimize the number of different patterns and objects
spellingShingle Nonlinear cutting stock problem model to minimize the number of different patterns and objects
Moretti,Antonio Carlos
cutting problem
nonlinear programming
column generation
title_short Nonlinear cutting stock problem model to minimize the number of different patterns and objects
title_full Nonlinear cutting stock problem model to minimize the number of different patterns and objects
title_fullStr Nonlinear cutting stock problem model to minimize the number of different patterns and objects
title_full_unstemmed Nonlinear cutting stock problem model to minimize the number of different patterns and objects
title_sort Nonlinear cutting stock problem model to minimize the number of different patterns and objects
author Moretti,Antonio Carlos
author_facet Moretti,Antonio Carlos
Salles Neto,Luiz Leduíno de
author_role author
author2 Salles Neto,Luiz Leduíno de
author2_role author
dc.contributor.author.fl_str_mv Moretti,Antonio Carlos
Salles Neto,Luiz Leduíno de
dc.subject.por.fl_str_mv cutting problem
nonlinear programming
column generation
topic cutting problem
nonlinear programming
column generation
description In this article we solve a nonlinear cutting stock problem which represents a cutting stock problem that considers the minimization of, both, the number of objects used and setup. We use a linearization of the nonlinear objective function to make possible the generation of good columns with the Gilmore and Gomory procedure. Each time a new column is added to the problem, we solve the original nonlinear problem by an Augmented Lagrangian method. This process is repeated until no more profitable columns is generated by Gilmore and Gomory technique. Finally, we apply a simple heuristic to obtain an integral solution for the original nonlinear integer problem.
publishDate 2008
dc.date.none.fl_str_mv 2008-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022008000100004
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dc.language.iso.fl_str_mv eng
language eng
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 Matemática Aplicada e Computacional
publisher.none.fl_str_mv Sociedade Brasileira de Matemática Aplicada e Computacional
dc.source.none.fl_str_mv Computational & Applied Mathematics v.27 n.1 2008
reponame:Computational & Applied Mathematics
instname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
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collection Computational & Applied Mathematics
repository.name.fl_str_mv Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
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