Genetic algorithm for vehicle routing problem with heterogeneous fleet and separate collection and delivery: a case in the Secretariat of Labor and Social Development of the State of CearÃ

Detalhes bibliográficos
Autor(a) principal: CÃsar Augusto Chaves e Sousa Filho
Data de Publicação: 2014
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações da UFC
Texto Completo: http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=13744
Resumo: A concern of logistics management is the correct and efficient use of the available fleet. The central focus of fleet management is determining the routes that will be used in customer service and the efficient allocation of available resources (vehicles). The correct fleet management can generate a competitive advantage. There is a problem in the Operations Research dedicated to working this type of situation, the Vehicle Routing Problem (VRP). The VRP tries to generate the most economical route to efficient use of the available fleet. The case study discussed in this work was a particular situation VRP where there is a heterogeneous fleet and where the collections and deliveries of passengers are carried at separate times. To solve this problem we designed a Genetic Algorithm. Additionally, three different crossover operators were tested in the search for better results. At the end of the study, the Genetic Algorithm was capable of solving the problem in a short time and finding the most economical way to generate routes, using efficiently the fleet and fulfilling all requests.
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spelling info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisGenetic algorithm for vehicle routing problem with heterogeneous fleet and separate collection and delivery: a case in the Secretariat of Labor and Social Development of the State of CearÃAlgoritmo genÃtico para o problema de roteirizaÃÃo de veÃculos com frota heterogÃnea e coleta e entrega separadas: estudo de caso na Secretaria do Trabalho e Desenvolvimento Social do Estado do CearÃ2014-07-31Josà Lassance de Castro Silva23574445334SÃlvia Maria de Freitas32429959372http://buscatextual.cnpq.br/buscatextual/visualizacv.jsp?id=K4727554D8Michael Ferreira de Souza0907168272202795995360CÃsar Augusto Chaves e Sousa FilhoUniversidade Federal do CearÃPrograma de PÃs-GraduaÃÃo em LogÃstica e Pesquisa OperacionalUFCBRProblema de roteamento de veÃculos Algoritmo genÃtico Frota heterogÃneaVehicle Routing Problem, Heterogeneous Fleet, Pickup and Delivery Separated, Genetic Algorithm, Logistics Operational ResearchPESQUISA OPERACIONALA concern of logistics management is the correct and efficient use of the available fleet. The central focus of fleet management is determining the routes that will be used in customer service and the efficient allocation of available resources (vehicles). The correct fleet management can generate a competitive advantage. There is a problem in the Operations Research dedicated to working this type of situation, the Vehicle Routing Problem (VRP). The VRP tries to generate the most economical route to efficient use of the available fleet. The case study discussed in this work was a particular situation VRP where there is a heterogeneous fleet and where the collections and deliveries of passengers are carried at separate times. To solve this problem we designed a Genetic Algorithm. Additionally, three different crossover operators were tested in the search for better results. At the end of the study, the Genetic Algorithm was capable of solving the problem in a short time and finding the most economical way to generate routes, using efficiently the fleet and fulfilling all requests.Uma das preocupaÃÃes da gestÃo logÃstica à a correta e eficiente utilizaÃÃo da frota disponÃvel. O foco central da gestÃo da frota està em determinar as rotas que serÃo utilizadas no atendimento aos clientes e a alocaÃÃo eficiente dos recursos (veÃculos) disponÃveis. A gestÃo correta da frota pode gerar um diferencial competitivo. Existe na Pesquisa Operacional um problema dedicado a trabalhar este tipo de situaÃÃo, denominado Problema de Roteamento de VeÃculos (PRV). O PRV procura gerar a rota mais econÃmica com utilizaÃÃo eficiente da frota disponÃvel. No estudo de caso, realizado neste trabalho, foi abordada uma situaÃÃo particular do PRV onde hà uma frota heterogÃnea e as coletas e entregas de passageiros sÃo realizadas em momentos separados. Para a resoluÃÃo deste problema foi desenvolvido e implementado um Algoritmo GenÃtico (AG). Adicionalmente, trÃs operadores de cruzamento diferentes foram testados na busca dos melhores resultados encontrados pelo AG. Ao final, o Algoritmo GenÃtico conseguiu se mostrar capaz de resolver o problema em tempo hÃbil e de maneira a gerar rotas mais econÃmicas, utilizando eficientemente a frota e atendendo todas as solicitaÃÃes.http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=13744application/pdfinfo:eu-repo/semantics/openAccessporreponame:Biblioteca Digital de Teses e Dissertações da UFCinstname:Universidade Federal do Cearáinstacron:UFC2019-01-21T11:27:05Zmail@mail.com -
dc.title.en.fl_str_mv Genetic algorithm for vehicle routing problem with heterogeneous fleet and separate collection and delivery: a case in the Secretariat of Labor and Social Development of the State of CearÃ
dc.title.alternative.pt.fl_str_mv Algoritmo genÃtico para o problema de roteirizaÃÃo de veÃculos com frota heterogÃnea e coleta e entrega separadas: estudo de caso na Secretaria do Trabalho e Desenvolvimento Social do Estado do CearÃ
title Genetic algorithm for vehicle routing problem with heterogeneous fleet and separate collection and delivery: a case in the Secretariat of Labor and Social Development of the State of CearÃ
spellingShingle Genetic algorithm for vehicle routing problem with heterogeneous fleet and separate collection and delivery: a case in the Secretariat of Labor and Social Development of the State of CearÃ
CÃsar Augusto Chaves e Sousa Filho
Problema de roteamento de veÃculos
Algoritmo genÃtico
Frota heterogÃnea
Vehicle Routing Problem, Heterogeneous Fleet, Pickup and Delivery Separated, Genetic Algorithm, Logistics
Operational Research
PESQUISA OPERACIONAL
title_short Genetic algorithm for vehicle routing problem with heterogeneous fleet and separate collection and delivery: a case in the Secretariat of Labor and Social Development of the State of CearÃ
title_full Genetic algorithm for vehicle routing problem with heterogeneous fleet and separate collection and delivery: a case in the Secretariat of Labor and Social Development of the State of CearÃ
title_fullStr Genetic algorithm for vehicle routing problem with heterogeneous fleet and separate collection and delivery: a case in the Secretariat of Labor and Social Development of the State of CearÃ
title_full_unstemmed Genetic algorithm for vehicle routing problem with heterogeneous fleet and separate collection and delivery: a case in the Secretariat of Labor and Social Development of the State of CearÃ
title_sort Genetic algorithm for vehicle routing problem with heterogeneous fleet and separate collection and delivery: a case in the Secretariat of Labor and Social Development of the State of CearÃ
author CÃsar Augusto Chaves e Sousa Filho
author_facet CÃsar Augusto Chaves e Sousa Filho
author_role author
dc.contributor.advisor1.fl_str_mv Josà Lassance de Castro Silva
dc.contributor.advisor1ID.fl_str_mv 23574445334
dc.contributor.referee1.fl_str_mv SÃlvia Maria de Freitas
dc.contributor.referee1ID.fl_str_mv 32429959372
dc.contributor.referee1Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.jsp?id=K4727554D8
dc.contributor.referee2.fl_str_mv Michael Ferreira de Souza
dc.contributor.referee2ID.fl_str_mv 09071682722
dc.contributor.authorID.fl_str_mv 02795995360
dc.contributor.author.fl_str_mv CÃsar Augusto Chaves e Sousa Filho
contributor_str_mv Josà Lassance de Castro Silva
SÃlvia Maria de Freitas
Michael Ferreira de Souza
dc.subject.por.fl_str_mv Problema de roteamento de veÃculos
Algoritmo genÃtico
Frota heterogÃnea
topic Problema de roteamento de veÃculos
Algoritmo genÃtico
Frota heterogÃnea
Vehicle Routing Problem, Heterogeneous Fleet, Pickup and Delivery Separated, Genetic Algorithm, Logistics
Operational Research
PESQUISA OPERACIONAL
dc.subject.eng.fl_str_mv Vehicle Routing Problem, Heterogeneous Fleet, Pickup and Delivery Separated, Genetic Algorithm, Logistics
Operational Research
dc.subject.cnpq.fl_str_mv PESQUISA OPERACIONAL
dc.description.abstract.por.fl_txt_mv A concern of logistics management is the correct and efficient use of the available fleet. The central focus of fleet management is determining the routes that will be used in customer service and the efficient allocation of available resources (vehicles). The correct fleet management can generate a competitive advantage. There is a problem in the Operations Research dedicated to working this type of situation, the Vehicle Routing Problem (VRP). The VRP tries to generate the most economical route to efficient use of the available fleet. The case study discussed in this work was a particular situation VRP where there is a heterogeneous fleet and where the collections and deliveries of passengers are carried at separate times. To solve this problem we designed a Genetic Algorithm. Additionally, three different crossover operators were tested in the search for better results. At the end of the study, the Genetic Algorithm was capable of solving the problem in a short time and finding the most economical way to generate routes, using efficiently the fleet and fulfilling all requests.
Uma das preocupaÃÃes da gestÃo logÃstica à a correta e eficiente utilizaÃÃo da frota disponÃvel. O foco central da gestÃo da frota està em determinar as rotas que serÃo utilizadas no atendimento aos clientes e a alocaÃÃo eficiente dos recursos (veÃculos) disponÃveis. A gestÃo correta da frota pode gerar um diferencial competitivo. Existe na Pesquisa Operacional um problema dedicado a trabalhar este tipo de situaÃÃo, denominado Problema de Roteamento de VeÃculos (PRV). O PRV procura gerar a rota mais econÃmica com utilizaÃÃo eficiente da frota disponÃvel. No estudo de caso, realizado neste trabalho, foi abordada uma situaÃÃo particular do PRV onde hà uma frota heterogÃnea e as coletas e entregas de passageiros sÃo realizadas em momentos separados. Para a resoluÃÃo deste problema foi desenvolvido e implementado um Algoritmo GenÃtico (AG). Adicionalmente, trÃs operadores de cruzamento diferentes foram testados na busca dos melhores resultados encontrados pelo AG. Ao final, o Algoritmo GenÃtico conseguiu se mostrar capaz de resolver o problema em tempo hÃbil e de maneira a gerar rotas mais econÃmicas, utilizando eficientemente a frota e atendendo todas as solicitaÃÃes.
description A concern of logistics management is the correct and efficient use of the available fleet. The central focus of fleet management is determining the routes that will be used in customer service and the efficient allocation of available resources (vehicles). The correct fleet management can generate a competitive advantage. There is a problem in the Operations Research dedicated to working this type of situation, the Vehicle Routing Problem (VRP). The VRP tries to generate the most economical route to efficient use of the available fleet. The case study discussed in this work was a particular situation VRP where there is a heterogeneous fleet and where the collections and deliveries of passengers are carried at separate times. To solve this problem we designed a Genetic Algorithm. Additionally, three different crossover operators were tested in the search for better results. At the end of the study, the Genetic Algorithm was capable of solving the problem in a short time and finding the most economical way to generate routes, using efficiently the fleet and fulfilling all requests.
publishDate 2014
dc.date.issued.fl_str_mv 2014-07-31
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
status_str publishedVersion
format masterThesis
dc.identifier.uri.fl_str_mv http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=13744
url http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=13744
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.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do CearÃ
dc.publisher.program.fl_str_mv Programa de PÃs-GraduaÃÃo em LogÃstica e Pesquisa Operacional
dc.publisher.initials.fl_str_mv UFC
dc.publisher.country.fl_str_mv BR
publisher.none.fl_str_mv Universidade Federal do CearÃ
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações da UFC
instname:Universidade Federal do Ceará
instacron:UFC
reponame_str Biblioteca Digital de Teses e Dissertações da UFC
collection Biblioteca Digital de Teses e Dissertações da UFC
instname_str Universidade Federal do Ceará
instacron_str UFC
institution UFC
repository.name.fl_str_mv -
repository.mail.fl_str_mv mail@mail.com
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