Problemas de roteamento de veículos com dependência temporal e espacial entre rotas de equipes de campo
Ano de defesa: | 2016 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | , , , |
Tipo de documento: | Tese |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Santa Maria
|
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia Elétrica
|
Departamento: |
Engenharia Elétrica
|
País: |
BR
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://repositorio.ufsm.br/handle/1/3700 |
Resumo: | This thesis presents two new routing problems, both with objective functions focused on relative positioning of teams during the routing horizon. The relative positioning results in temporal and spatial dependencies among routes and is quantified with a nonlinear dispersion metric, designed to evaluate the instantaneous distances among teams over a time interval. This metric allows the design of objective functions to approximate teams during routes execution, when minimized, or disperse them, when maximized. Both approximation and dispersion are important routing characteristics in some practical applications, and two new optimization problems are proposed with these opposite objectives. The first one is a variation of the Multiple Traveling Salesman Problem, and its goal is to find a set of tours where the salesmen travel close to each other, minimizing dispersion. A Local Search Genetic Algorithm is proposed to solve the problem. It includes specialized genetic operators and neighborhoods. A new set of benchmark instances is proposed, adapted for the new problem from literature instances. Computational results show that the proposed approach provides solutions with the desired characteristics of minimal dispersion. The second problem is a bi-objective arc routing problem in which routes must be constructed in order to maximize collected profit and dispersion of teams. The maximization of the dispersion metric fosters the scattering of the teams during routing procedure. Usually, profit and dispersion objectives are conflicting, and by using a bi-objective approach the decision maker is able to choose a trade-off between collecting profits and scattering teams. Two solution methods are proposed, a Multi-objective Genetic Algorithm and a Multi-objective Genetic Local Search Algorithm, both specialized in order to exploit the characteristics of the problem. It is demonstrated, by means of computational experiments on a new set of benchmark instances, that the proposed approach provides approximation sets with the desired characteristics. |
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2017-05-252017-05-252016-08-26DHEIN, Guilherme. Vehicle routing problems with temporal and spatial dependencies among routes. 2016. 151 f. Tese (Doutorado em Engenharia Elétrica) - Universidade Federal de Santa Maria, Santa Maria, 2016.http://repositorio.ufsm.br/handle/1/3700This thesis presents two new routing problems, both with objective functions focused on relative positioning of teams during the routing horizon. The relative positioning results in temporal and spatial dependencies among routes and is quantified with a nonlinear dispersion metric, designed to evaluate the instantaneous distances among teams over a time interval. This metric allows the design of objective functions to approximate teams during routes execution, when minimized, or disperse them, when maximized. Both approximation and dispersion are important routing characteristics in some practical applications, and two new optimization problems are proposed with these opposite objectives. The first one is a variation of the Multiple Traveling Salesman Problem, and its goal is to find a set of tours where the salesmen travel close to each other, minimizing dispersion. A Local Search Genetic Algorithm is proposed to solve the problem. It includes specialized genetic operators and neighborhoods. A new set of benchmark instances is proposed, adapted for the new problem from literature instances. Computational results show that the proposed approach provides solutions with the desired characteristics of minimal dispersion. The second problem is a bi-objective arc routing problem in which routes must be constructed in order to maximize collected profit and dispersion of teams. The maximization of the dispersion metric fosters the scattering of the teams during routing procedure. Usually, profit and dispersion objectives are conflicting, and by using a bi-objective approach the decision maker is able to choose a trade-off between collecting profits and scattering teams. Two solution methods are proposed, a Multi-objective Genetic Algorithm and a Multi-objective Genetic Local Search Algorithm, both specialized in order to exploit the characteristics of the problem. It is demonstrated, by means of computational experiments on a new set of benchmark instances, that the proposed approach provides approximation sets with the desired characteristics.Esta tese apresenta dois novos problemas de roteamento, ambos com funções objetivo voltadas para o posicionamento relativo das equipes durante o horizonte de roteamento. O posicionamento relativo resulta em uma dependência temporal e espacial entre rotas e é quantificado com uma métrica de dispersão não-linear, projetada para avaliar as distâncias instantâneas entre as equipes ao longo de um intervalo de tempo. Esta métrica permite a concepção de funções objetivo para aproximar as equipes durante a execução das rotas, quando minimizada, ou para dispersá-las, quando maximizada. Tanto a aproximação quanto a dispersão são características importantes de roteamento em algumas aplicações práticas, e dois novos problemas de otimização são propostos com esses objetivos opostos. O primeiro é uma variação do Problema de Múltiplos Caixeiros Viajantes, e seu objetivo é encontrar um conjunto de rotas em que os caixeiros viajam próximos uns dos outros, minimizando a dispersão. Um Algoritmo Genético com Busca Local é proposto para resolver o problema. Ele inclui operadores genéticos e vizinhanças especializados. Um novo conjunto de instâncias é proposto, adaptado para o novo problema de instâncias da literatura. Resultados computacionais mostram que a abordagem proposta proporciona soluções com as características desejadas de dispersão mínima. O segundo problema é um problema de roteamento de arcos biobjetivo em que as rotas devem ser construídas de modo a maximizar o lucro recolhido e o distanciamento entre as equipes. A maximização da métrica promove a dispersão das equipes durante a execução das rotas. Normalmente, os objetivos de lucro e dispersão são conflitantes, e com uma abordagem biobjetivo o tomador de decisão é capaz de avaliar a troca entre a coleta de lucros e a dispersão de equipes. Dois métodos de solução são propostos, um Algoritmo Genético Multiobjetivo e um Algoritmo Genético Multiobjetivo com Busca Local, ambos especializados para explorar as características do problema. É demonstrado, por meio de experimentos computacionais sobre um novo conjunto de instâncias, que a abordagem proposta fornece conjuntos de aproximação com as características desejadas.application/pdfporUniversidade Federal de Santa MariaPrograma de Pós-Graduação em Engenharia ElétricaUFSMBREngenharia ElétricaAlgoritmo genéticoAlgoritmo genético com busca local multiobjetivoRotas sincronizadasMultiple traveling salesman problemArc routingDispersion metricDispersion minimizationDispersion maximizationProfit collectionGenetic algorithmMultiobjective genetic local search algorithmSynchronized routesCNPQ::ENGENHARIAS::ENGENHARIA ELETRICAProblemas de roteamento de veículos com dependência temporal e espacial entre rotas de equipes de campoVehicle routing problems with temporal and spatial dependencies among routesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisCardoso Junior, Ghendyhttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4770600A7Buriol, Luciana Saletehttp://lattes.cnpq.br/8337454058604654Lyra Filho, Christianohttp://lattes.cnpq.br/4217731655224539Santos, José Vicente Canto doshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4728269Y8Müller, Felipe Martinshttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4723058U1http://lattes.cnpq.br/9654070459416361Dhein, Guilherme300400000007400300300300300300300eed4f55e-1a74-47ce-afc0-4daa8655d8a371217d64-5f3e-4e22-b7f4-b4a2a03c6f27570a09aa-4e05-4999-9101-aeb1271a4104977c3911-6a48-4c76-af8c-72ef96ff189ca9530854-555a-4743-831e-76d18d8b80eee0fdea98-55da-42d1-a36a-e2c272902d52info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações do UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDHEIN, GUILHERME.pdfapplication/pdf5152546http://repositorio.ufsm.br/bitstream/1/3700/1/DHEIN%2c%20GUILHERME.pdfc53c460fc52121e2fd199f62ae9f13c2MD51TEXTDHEIN, GUILHERME.pdf.txtDHEIN, GUILHERME.pdf.txtExtracted texttext/plain305762http://repositorio.ufsm.br/bitstream/1/3700/2/DHEIN%2c%20GUILHERME.pdf.txt15bc37d70671043516379252dd5139bfMD52THUMBNAILDHEIN, GUILHERME.pdf.jpgDHEIN, GUILHERME.pdf.jpgIM Thumbnailimage/jpeg4357http://repositorio.ufsm.br/bitstream/1/3700/3/DHEIN%2c%20GUILHERME.pdf.jpg099904c660b8806fb490662a0cf1ba79MD531/37002017-07-25 10:58:28.491oai:repositorio.ufsm.br:1/3700Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2017-07-25T13:58:28Biblioteca Digital de Teses e Dissertações do UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Problemas de roteamento de veículos com dependência temporal e espacial entre rotas de equipes de campo |
dc.title.alternative.eng.fl_str_mv |
Vehicle routing problems with temporal and spatial dependencies among routes |
title |
Problemas de roteamento de veículos com dependência temporal e espacial entre rotas de equipes de campo |
spellingShingle |
Problemas de roteamento de veículos com dependência temporal e espacial entre rotas de equipes de campo Dhein, Guilherme Algoritmo genético Algoritmo genético com busca local multiobjetivo Rotas sincronizadas Multiple traveling salesman problem Arc routing Dispersion metric Dispersion minimization Dispersion maximization Profit collection Genetic algorithm Multiobjective genetic local search algorithm Synchronized routes CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
title_short |
Problemas de roteamento de veículos com dependência temporal e espacial entre rotas de equipes de campo |
title_full |
Problemas de roteamento de veículos com dependência temporal e espacial entre rotas de equipes de campo |
title_fullStr |
Problemas de roteamento de veículos com dependência temporal e espacial entre rotas de equipes de campo |
title_full_unstemmed |
Problemas de roteamento de veículos com dependência temporal e espacial entre rotas de equipes de campo |
title_sort |
Problemas de roteamento de veículos com dependência temporal e espacial entre rotas de equipes de campo |
author |
Dhein, Guilherme |
author_facet |
Dhein, Guilherme |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Cardoso Junior, Ghendy |
dc.contributor.advisor1Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4770600A7 |
dc.contributor.referee1.fl_str_mv |
Buriol, Luciana Salete |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/8337454058604654 |
dc.contributor.referee2.fl_str_mv |
Lyra Filho, Christiano |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/4217731655224539 |
dc.contributor.referee3.fl_str_mv |
Santos, José Vicente Canto dos |
dc.contributor.referee3Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4728269Y8 |
dc.contributor.referee4.fl_str_mv |
Müller, Felipe Martins |
dc.contributor.referee4Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4723058U1 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/9654070459416361 |
dc.contributor.author.fl_str_mv |
Dhein, Guilherme |
contributor_str_mv |
Cardoso Junior, Ghendy Buriol, Luciana Salete Lyra Filho, Christiano Santos, José Vicente Canto dos Müller, Felipe Martins |
dc.subject.por.fl_str_mv |
Algoritmo genético Algoritmo genético com busca local multiobjetivo Rotas sincronizadas |
topic |
Algoritmo genético Algoritmo genético com busca local multiobjetivo Rotas sincronizadas Multiple traveling salesman problem Arc routing Dispersion metric Dispersion minimization Dispersion maximization Profit collection Genetic algorithm Multiobjective genetic local search algorithm Synchronized routes CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
dc.subject.eng.fl_str_mv |
Multiple traveling salesman problem Arc routing Dispersion metric Dispersion minimization Dispersion maximization Profit collection Genetic algorithm Multiobjective genetic local search algorithm Synchronized routes |
dc.subject.cnpq.fl_str_mv |
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
description |
This thesis presents two new routing problems, both with objective functions focused on relative positioning of teams during the routing horizon. The relative positioning results in temporal and spatial dependencies among routes and is quantified with a nonlinear dispersion metric, designed to evaluate the instantaneous distances among teams over a time interval. This metric allows the design of objective functions to approximate teams during routes execution, when minimized, or disperse them, when maximized. Both approximation and dispersion are important routing characteristics in some practical applications, and two new optimization problems are proposed with these opposite objectives. The first one is a variation of the Multiple Traveling Salesman Problem, and its goal is to find a set of tours where the salesmen travel close to each other, minimizing dispersion. A Local Search Genetic Algorithm is proposed to solve the problem. It includes specialized genetic operators and neighborhoods. A new set of benchmark instances is proposed, adapted for the new problem from literature instances. Computational results show that the proposed approach provides solutions with the desired characteristics of minimal dispersion. The second problem is a bi-objective arc routing problem in which routes must be constructed in order to maximize collected profit and dispersion of teams. The maximization of the dispersion metric fosters the scattering of the teams during routing procedure. Usually, profit and dispersion objectives are conflicting, and by using a bi-objective approach the decision maker is able to choose a trade-off between collecting profits and scattering teams. Two solution methods are proposed, a Multi-objective Genetic Algorithm and a Multi-objective Genetic Local Search Algorithm, both specialized in order to exploit the characteristics of the problem. It is demonstrated, by means of computational experiments on a new set of benchmark instances, that the proposed approach provides approximation sets with the desired characteristics. |
publishDate |
2016 |
dc.date.issued.fl_str_mv |
2016-08-26 |
dc.date.accessioned.fl_str_mv |
2017-05-25 |
dc.date.available.fl_str_mv |
2017-05-25 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
DHEIN, Guilherme. Vehicle routing problems with temporal and spatial dependencies among routes. 2016. 151 f. Tese (Doutorado em Engenharia Elétrica) - Universidade Federal de Santa Maria, Santa Maria, 2016. |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/3700 |
identifier_str_mv |
DHEIN, Guilherme. Vehicle routing problems with temporal and spatial dependencies among routes. 2016. 151 f. Tese (Doutorado em Engenharia Elétrica) - Universidade Federal de Santa Maria, Santa Maria, 2016. |
url |
http://repositorio.ufsm.br/handle/1/3700 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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300400000007 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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Universidade Federal de Santa Maria |
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Programa de Pós-Graduação em Engenharia Elétrica |
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UFSM |
dc.publisher.country.fl_str_mv |
BR |
dc.publisher.department.fl_str_mv |
Engenharia Elétrica |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
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