Exportação concluída — 

Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera

Detalhes bibliográficos
Ano de defesa: 2008
Autor(a) principal: Gomes, Francisco Régis Abreu
Orientador(a): Silva, José Lassance de Castro
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/16185
Resumo: In this work two problems were solved: the first is Continuous Perm utation Flowshop Scheduling Problem (CPFSP) it possesses the constraint that no j ob can wait for processing among serial machines; the second is Permutation Flowshop Scheduling Problem (PFSP), in that the previous restriction does not exist. The metaheurist ic Genetic Algorithm (GA) has been applied with success for solving the PFSP, but up to now it was not found in the literature something that shows that GA is a good method for CPFS P. The objective of this work was to develop an efficient GA for both problems, but that does not need to use an initialization efficient and/or hybridization allied with other se arch technique. The development of proposed GA took in consideration the characteristics, diversification and the intensification, that inspired the creation of three procedure s that further improved the proposed GA. Several experiments were accomplished with the ins tances of Taillard (1993), Reeves (1995) and Heller (1960). The results were compared wi th other methods found in the literature. Polynomials were built with Lagrangeana's Interpolation use to determine the time execution of proposed GA. Finally, the method wa s applied in a real problem. The results showed that proposed GA is the best method for CPFSP and that is very close of best GA found in the literature with efficie nt initialization for PFSP.
id UFC-7_30afe697e850fadce73ca565259f5b2e
oai_identifier_str oai:repositorio.ufc.br:riufc/16185
network_acronym_str UFC-7
network_name_str Repositório Institucional da Universidade Federal do Ceará (UFC)
repository_id_str
spelling Gomes, Francisco Régis AbreuSilva, José Lassance de Castro2016-04-07T16:40:50Z2016-04-07T16:40:50Z2008-02-15GOMES, F. R. A. Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera. 2008. 141 f. Dissertação (Mestrado em Logística e Pesquisa Operacional) – Pró-Reitoria de Pesquisa e Pós-Graduação, Universidade Federal do Ceará, Fortaleza, 2008.http://www.repositorio.ufc.br/handle/riufc/16185In this work two problems were solved: the first is Continuous Perm utation Flowshop Scheduling Problem (CPFSP) it possesses the constraint that no j ob can wait for processing among serial machines; the second is Permutation Flowshop Scheduling Problem (PFSP), in that the previous restriction does not exist. The metaheurist ic Genetic Algorithm (GA) has been applied with success for solving the PFSP, but up to now it was not found in the literature something that shows that GA is a good method for CPFS P. The objective of this work was to develop an efficient GA for both problems, but that does not need to use an initialization efficient and/or hybridization allied with other se arch technique. The development of proposed GA took in consideration the characteristics, diversification and the intensification, that inspired the creation of three procedure s that further improved the proposed GA. Several experiments were accomplished with the ins tances of Taillard (1993), Reeves (1995) and Heller (1960). The results were compared wi th other methods found in the literature. Polynomials were built with Lagrangeana's Interpolation use to determine the time execution of proposed GA. Finally, the method wa s applied in a real problem. The results showed that proposed GA is the best method for CPFSP and that is very close of best GA found in the literature with efficie nt initialization for PFSP.Neste trabalho foram tratados dois problemas: o primeiro é denominado Continuous Permutation Flowshop Scheduling Problem (CPFSP), que possui a restrição de que nenhuma tarefa pode esperar por processamento entre máquinas consecutivas; o segundo é denominado de Permutation Flowshop Scheduling Problem (PFSP), em que a restrição anterior não existe. A metaheurística Algoritmo Genético (AG) tem sido aplicada com sucesso ao PFSP, mas até o momento não foi encontrado na literatura algo que mostre que o AG é um bom método para o CPFSP. O objetivo deste trabalho foi desenvolver um AG eficiente paras esses dois problemas, mas que não precisa utilizar inicialização eficiente e/ou hibridização com outra técnica de busca. O desenvolvimento do AG proposto levou em consideração as características, diversificação e a intensificação, que inspiraram a criação de três procedimentos que melhoraram o desempenho do AG proposto. Foram realizados vários experimentos com as instâncias de Taillard (1993), Reeves (1995) e Heller (1960). Os resultados foram comparados com outros métodos encontrados na literatura. Foram construídos polinômios com a utilização de Interpolação Lagrangeana para determinar o tempo execução do AG proposto. Por fim, o método foi aplicado num problema real. Os resultados mostraram que o AG proposto é o melhor método para o CPFSP e que fica muito próximo do melhor AG encontrado na literatura com inicialização eficiente para o PFSPLogísticaAlgoritmo genéticoDiversificação e intensificaçãoAlgoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de esperaGenetic algorithm applied to the permutational flowshop scheduling problem without and with wait restrictioninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccessLICENSElicense.txtlicense.txttext/plain; charset=utf-81786http://repositorio.ufc.br/bitstream/riufc/16185/2/license.txt8c4401d3d14722a7ca2d07c782a1aab3MD52ORIGINAL2008_dis_fragomes.pdf2008_dis_fragomes.pdfapplication/pdf992202http://repositorio.ufc.br/bitstream/riufc/16185/1/2008_dis_fragomes.pdf0d83127d1323f9051e069ab4fe04f2ceMD51riufc/161852022-09-21 14:11:39.687oai:repositorio.ufc.br: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Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2022-09-21T17:11:39Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.pt_BR.fl_str_mv Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera
dc.title.en.pt_BR.fl_str_mv Genetic algorithm applied to the permutational flowshop scheduling problem without and with wait restriction
title Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera
spellingShingle Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera
Gomes, Francisco Régis Abreu
Logística
Algoritmo genético
Diversificação e intensificação
title_short Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera
title_full Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera
title_fullStr Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera
title_full_unstemmed Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera
title_sort Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera
author Gomes, Francisco Régis Abreu
author_facet Gomes, Francisco Régis Abreu
author_role author
dc.contributor.author.fl_str_mv Gomes, Francisco Régis Abreu
dc.contributor.advisor1.fl_str_mv Silva, José Lassance de Castro
contributor_str_mv Silva, José Lassance de Castro
dc.subject.por.fl_str_mv Logística
Algoritmo genético
Diversificação e intensificação
topic Logística
Algoritmo genético
Diversificação e intensificação
description In this work two problems were solved: the first is Continuous Perm utation Flowshop Scheduling Problem (CPFSP) it possesses the constraint that no j ob can wait for processing among serial machines; the second is Permutation Flowshop Scheduling Problem (PFSP), in that the previous restriction does not exist. The metaheurist ic Genetic Algorithm (GA) has been applied with success for solving the PFSP, but up to now it was not found in the literature something that shows that GA is a good method for CPFS P. The objective of this work was to develop an efficient GA for both problems, but that does not need to use an initialization efficient and/or hybridization allied with other se arch technique. The development of proposed GA took in consideration the characteristics, diversification and the intensification, that inspired the creation of three procedure s that further improved the proposed GA. Several experiments were accomplished with the ins tances of Taillard (1993), Reeves (1995) and Heller (1960). The results were compared wi th other methods found in the literature. Polynomials were built with Lagrangeana's Interpolation use to determine the time execution of proposed GA. Finally, the method wa s applied in a real problem. The results showed that proposed GA is the best method for CPFSP and that is very close of best GA found in the literature with efficie nt initialization for PFSP.
publishDate 2008
dc.date.issued.fl_str_mv 2008-02-15
dc.date.accessioned.fl_str_mv 2016-04-07T16:40:50Z
dc.date.available.fl_str_mv 2016-04-07T16:40:50Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv GOMES, F. R. A. Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera. 2008. 141 f. Dissertação (Mestrado em Logística e Pesquisa Operacional) – Pró-Reitoria de Pesquisa e Pós-Graduação, Universidade Federal do Ceará, Fortaleza, 2008.
dc.identifier.uri.fl_str_mv http://www.repositorio.ufc.br/handle/riufc/16185
identifier_str_mv GOMES, F. R. A. Algoritimo genético aplicado aos problema de seqüenciamento permutacional flowshop sem e com restrição de espera. 2008. 141 f. Dissertação (Mestrado em Logística e Pesquisa Operacional) – Pró-Reitoria de Pesquisa e Pós-Graduação, Universidade Federal do Ceará, Fortaleza, 2008.
url http://www.repositorio.ufc.br/handle/riufc/16185
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal do Ceará (UFC)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Repositório Institucional da Universidade Federal do Ceará (UFC)
collection Repositório Institucional da Universidade Federal do Ceará (UFC)
bitstream.url.fl_str_mv http://repositorio.ufc.br/bitstream/riufc/16185/2/license.txt
http://repositorio.ufc.br/bitstream/riufc/16185/1/2008_dis_fragomes.pdf
bitstream.checksum.fl_str_mv 8c4401d3d14722a7ca2d07c782a1aab3
0d83127d1323f9051e069ab4fe04f2ce
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv bu@ufc.br || repositorio@ufc.br
_version_ 1847793129575415808