Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost

Detalhes bibliográficos
Autor(a) principal: Martin,Mateus
Data de Publicação: 2018
Outros Autores: Moretti,Antonio, Gomes-Ruggiero,Marcia, Salles Neto,Luiz
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.
id ABEPRO-1_02e686a363b58f4427a94926f3f56ba7
oai_identifier_str oai:scielo:S0103-65132018000100217
network_acronym_str ABEPRO-1
network_name_str Production
repository_id_str
spelling 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