A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS

Detalhes bibliográficos
Autor(a) principal: Araujo, Silvio Alexandre De
Data de Publicação: 2014
Outros Autores: Poldi, Kelly Cristina, Smith, Jim
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNIFESP
Texto Completo: http://repositorio.unifesp.br/handle/11600/8367
http://dx.doi.org/10.1590/0101-7438.2014.034.02.0165
Resumo: This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the problem. This heuristic is empirically analyzed by solving randomly generated instances and also practical instances from a chemical-fiber company. The computational results show that the method is efficient and obtains positive results when compared to other methods from the literature.
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spelling Araujo, Silvio Alexandre DePoldi, Kelly CristinaSmith, JimUniversidade Estadual Paulista (UNESP)Universidade Federal de São Paulo (UNIFESP)University of the West of England Faculty of Environment and Technology2015-06-14T13:47:05Z2015-06-14T13:47:05Z2014-05-01Pesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 34, n. 2, p. 165-187, 2014.0101-7438http://repositorio.unifesp.br/handle/11600/8367http://dx.doi.org/10.1590/0101-7438.2014.034.02.0165S0101-74382014000200165.pdfS0101-7438201400020016510.1590/0101-7438.2014.034.02.0165This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the problem. This heuristic is empirically analyzed by solving randomly generated instances and also practical instances from a chemical-fiber company. The computational results show that the method is efficient and obtains positive results when compared to other methods from the literature.Universidade Estadual Paulista Departamento de Matemática AplicadaUniversidade Federal de São Paulo (UNIFESP) Instituto de Ciência e TecnologiaUniversity of the West of England Faculty of Environment and TechnologyUNIFESP, Instituto de Ciência e TecnologiaSciELO165-187engSociedade Brasileira de Pesquisa OperacionalPesquisa Operacionalinteger optimizationcutting stock problem with setupsgenetic algorithmA GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPSinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UNIFESPinstname:Universidade Federal de São Paulo (UNIFESP)instacron:UNIFESPORIGINALS0101-74382014000200165.pdfapplication/pdf371129${dspace.ui.url}/bitstream/11600/8367/1/S0101-74382014000200165.pdf56c750c9e1f0457b9ba79e7617fc35bfMD51open accessTEXTS0101-74382014000200165.pdf.txtS0101-74382014000200165.pdf.txtExtracted texttext/plain67721${dspace.ui.url}/bitstream/11600/8367/9/S0101-74382014000200165.pdf.txtdb2550f048e123e4c0a13e0c93552d9cMD59open accessTHUMBNAILS0101-74382014000200165.pdf.jpgS0101-74382014000200165.pdf.jpgIM Thumbnailimage/jpeg4601${dspace.ui.url}/bitstream/11600/8367/11/S0101-74382014000200165.pdf.jpgd0a6bea5919c5e4e3c75a8be231e79b7MD511open access11600/83672023-06-05 19:07:00.738open accessoai:repositorio.unifesp.br:11600/8367Repositório InstitucionalPUBhttp://www.repositorio.unifesp.br/oai/requestopendoar:34652023-06-05T22:07Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)false
dc.title.en.fl_str_mv A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS
title A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS
spellingShingle A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS
Araujo, Silvio Alexandre De
integer optimization
cutting stock problem with setups
genetic algorithm
title_short A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS
title_full A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS
title_fullStr A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS
title_full_unstemmed A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS
title_sort A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH SETUPS
author Araujo, Silvio Alexandre De
author_facet Araujo, Silvio Alexandre De
Poldi, Kelly Cristina
Smith, Jim
author_role author
author2 Poldi, Kelly Cristina
Smith, Jim
author2_role author
author
dc.contributor.institution.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Universidade Federal de São Paulo (UNIFESP)
University of the West of England Faculty of Environment and Technology
dc.contributor.author.fl_str_mv Araujo, Silvio Alexandre De
Poldi, Kelly Cristina
Smith, Jim
dc.subject.eng.fl_str_mv integer optimization
cutting stock problem with setups
genetic algorithm
topic integer optimization
cutting stock problem with setups
genetic algorithm
description This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the problem. This heuristic is empirically analyzed by solving randomly generated instances and also practical instances from a chemical-fiber company. The computational results show that the method is efficient and obtains positive results when compared to other methods from the literature.
publishDate 2014
dc.date.issued.fl_str_mv 2014-05-01
dc.date.accessioned.fl_str_mv 2015-06-14T13:47:05Z
dc.date.available.fl_str_mv 2015-06-14T13:47:05Z
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.citation.fl_str_mv Pesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 34, n. 2, p. 165-187, 2014.
dc.identifier.uri.fl_str_mv http://repositorio.unifesp.br/handle/11600/8367
http://dx.doi.org/10.1590/0101-7438.2014.034.02.0165
dc.identifier.issn.none.fl_str_mv 0101-7438
dc.identifier.file.none.fl_str_mv S0101-74382014000200165.pdf
dc.identifier.scielo.none.fl_str_mv S0101-74382014000200165
dc.identifier.doi.none.fl_str_mv 10.1590/0101-7438.2014.034.02.0165
identifier_str_mv Pesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 34, n. 2, p. 165-187, 2014.
0101-7438
S0101-74382014000200165.pdf
S0101-74382014000200165
10.1590/0101-7438.2014.034.02.0165
url http://repositorio.unifesp.br/handle/11600/8367
http://dx.doi.org/10.1590/0101-7438.2014.034.02.0165
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv Pesquisa Operacional
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 165-187
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 reponame:Repositório Institucional da UNIFESP
instname:Universidade Federal de São Paulo (UNIFESP)
instacron:UNIFESP
instname_str Universidade Federal de São Paulo (UNIFESP)
instacron_str UNIFESP
institution UNIFESP
reponame_str Repositório Institucional da UNIFESP
collection Repositório Institucional da UNIFESP
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