Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Production |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132018000100217 |
Resumo: | Abstract Paper aims We propose a modified Sequential Heuristic Procedure (MSHP) to reduce the cutting waste and number of setups for the One-Dimensional Cutting Stock Problem with Setup Cost. Originality This heuristic modifies Haessler’s sequential heuristic procedure (1975) by adapting the Integer Bounded Knapsack Problem to generate cutting patterns, instead of the original lexicographic search employed. The solution strategy is to generate different cutting plans using MSHP, and then to use an integer programming model to seek even better results. Research method It is a axiomatic research, ordinary in studies of Operational Research. Main findings In the computational experiments, we demonstrate the effectiveness of the algorithm with two sets of benchmark instances by comparing it with other approaches, and obtaining better solutions for some scenarios. Implications for theory and practice The approach is suitable for practitioners from different industrial settings due to its easily coding and possible adaptation for problem extensions. |
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Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup costCutting stockProblemSetup costsHeuristicsAbstract Paper aims We propose a modified Sequential Heuristic Procedure (MSHP) to reduce the cutting waste and number of setups for the One-Dimensional Cutting Stock Problem with Setup Cost. Originality This heuristic modifies Haessler’s sequential heuristic procedure (1975) by adapting the Integer Bounded Knapsack Problem to generate cutting patterns, instead of the original lexicographic search employed. The solution strategy is to generate different cutting plans using MSHP, and then to use an integer programming model to seek even better results. Research method It is a axiomatic research, ordinary in studies of Operational Research. Main findings In the computational experiments, we demonstrate the effectiveness of the algorithm with two sets of benchmark instances by comparing it with other approaches, and obtaining better solutions for some scenarios. Implications for theory and practice The approach is suitable for practitioners from different industrial settings due to its easily coding and possible adaptation for problem extensions.Associação Brasileira de Engenharia de Produção2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132018000100217Production v.28 2018reponame:Productioninstname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPRO10.1590/0103-6513.20170105info:eu-repo/semantics/openAccessMartin,MateusMoretti,AntonioGomes-Ruggiero,MarciaSalles Neto,Luizeng2018-10-11T00:00:00Zoai:scielo:S0103-65132018000100217Revistahttps://www.scielo.br/j/prod/https://old.scielo.br/oai/scielo-oai.php||production@editoracubo.com.br1980-54110103-6513opendoar:2018-10-11T00:00Production - Associação Brasileira de Engenharia de Produção (ABEPRO)false |
dc.title.none.fl_str_mv |
Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost |
title |
Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost |
spellingShingle |
Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost Martin,Mateus Cutting stock Problem Setup costs Heuristics |
title_short |
Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost |
title_full |
Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost |
title_fullStr |
Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost |
title_full_unstemmed |
Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost |
title_sort |
Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost |
author |
Martin,Mateus |
author_facet |
Martin,Mateus Moretti,Antonio Gomes-Ruggiero,Marcia Salles Neto,Luiz |
author_role |
author |
author2 |
Moretti,Antonio Gomes-Ruggiero,Marcia Salles Neto,Luiz |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Martin,Mateus Moretti,Antonio Gomes-Ruggiero,Marcia Salles Neto,Luiz |
dc.subject.por.fl_str_mv |
Cutting stock Problem Setup costs Heuristics |
topic |
Cutting stock Problem Setup costs Heuristics |
description |
Abstract Paper aims We propose a modified Sequential Heuristic Procedure (MSHP) to reduce the cutting waste and number of setups for the One-Dimensional Cutting Stock Problem with Setup Cost. Originality This heuristic modifies Haessler’s sequential heuristic procedure (1975) by adapting the Integer Bounded Knapsack Problem to generate cutting patterns, instead of the original lexicographic search employed. The solution strategy is to generate different cutting plans using MSHP, and then to use an integer programming model to seek even better results. Research method It is a axiomatic research, ordinary in studies of Operational Research. Main findings In the computational experiments, we demonstrate the effectiveness of the algorithm with two sets of benchmark instances by comparing it with other approaches, and obtaining better solutions for some scenarios. Implications for theory and practice The approach is suitable for practitioners from different industrial settings due to its easily coding and possible adaptation for problem extensions. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-01-01 |
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=S0103-65132018000100217 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132018000100217 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0103-6513.20170105 |
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 |
Associação Brasileira de Engenharia de Produção |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia de Produção |
dc.source.none.fl_str_mv |
Production v.28 2018 reponame:Production instname:Associação Brasileira de Engenharia de Produção (ABEPRO) instacron:ABEPRO |
instname_str |
Associação Brasileira de Engenharia de Produção (ABEPRO) |
instacron_str |
ABEPRO |
institution |
ABEPRO |
reponame_str |
Production |
collection |
Production |
repository.name.fl_str_mv |
Production - Associação Brasileira de Engenharia de Produção (ABEPRO) |
repository.mail.fl_str_mv |
||production@editoracubo.com.br |
_version_ |
1754213154453192704 |