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

dc.creatorMoretti, Antonio Carlos
dc.creatorSalles Neto, Luiz Leduíno de
dc.date2008-01-01
dc.date2014-07-18T20:03:54Z
dc.date2015-11-26T11:39:46Z
dc.date2014-07-18T20:03:54Z
dc.date2015-11-26T11:39:46Z
dc.date.accessioned2018-03-28T20:43:10Z
dc.date.available2018-03-28T20:43:10Z
dc.identifierComputational & Applied Mathematics. Sociedade Brasileira de Matemática Aplicada e Computacional, v. 27, n. 1, p. 61-78, 2008.
dc.identifier1807-0302
dc.identifierS1807-03022008000100004
dc.identifierhttp://www.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022008000100004
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/38625
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/38625
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1234297
dc.descriptionIn 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.
dc.description61
dc.description78
dc.languageen
dc.publisherSociedade Brasileira de Matemática Aplicada e Computacional
dc.relationComputational & Applied Mathematics
dc.rightsaberto
dc.sourceSciELO
dc.subjectcutting problem
dc.subjectnonlinear programming
dc.subjectcolumn generation
dc.titleNonlinear cutting stock problem model to minimize the number of different patterns and objects
dc.typeArtículos de revistas


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