Sistema multiagente para controle de veículos autônomos
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFSCAR |
Texto Completo: | https://repositorio.ufscar.br/handle/ufscar/570 |
Resumo: | Vehicle fleets are an important component in several applications, moving materials and people. Examples include material handling in warehouses, factories and port terminals, people transportation as in taxi fleets and emergency services, such as medical assistance, fire-fighters and police. Fleet operation is crucial for these applications: it can mean loss of money and commercial partners in case of industry, os loss of lives in case of emergency services. Controlling the fleet to achieve efficient levels of performance is a difficult problem, though, and becomes even harder as the fleet grows. Research in the area has been linking vehicle fleet operation to Multi-Agent Systems, because vehicle fleets are naturally distributed and Multi-agent System is a convenient abstraction to cope with distributed Artificial Intelligence problems. Therefore, it is proposed a Multi-Agent System to control vehicle fleets, focusing on material handling application in warehouses. The proposed system has three types of agents: Vehicle Agent, Loading Point Agent and Storage Point Agent. Agents interact amongst themselves through messages, trying to efficiently realize the material handling in a warehouse. System implementation is done through a simulation of a warehouse operation, built on top of MASON multi-agent system simulation platform. Task assignment strategies is also an important problem, therefore four strategies are shown and tested using the simulation: CNET, Fuzzy, DynCNET and FiTA. To enable comparison among these strategies, a Genetic Algorithm is employed to systematically search good parameters for each strategy. The proposed system, as well as the simulation, are offered as a framework for development of other vehicle fleets controlling multi-agent systems and/or task assignment strategies. |
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Branisso, Lucas BinhardiKato, Edilson Reis Rodrigueshttp://lattes.cnpq.br/8517698122676145http://lattes.cnpq.br/2989288919102233634a423a-72ed-4be2-bbce-a362d6c64ef72016-06-02T19:06:14Z2014-09-252016-06-02T19:06:14Z2014-06-10BRANISSO, Lucas Binhardi. Sistema multiagente para controle de veículos autônomos. 2014. 130 f. Dissertação (Mestrado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2014.https://repositorio.ufscar.br/handle/ufscar/570Vehicle fleets are an important component in several applications, moving materials and people. Examples include material handling in warehouses, factories and port terminals, people transportation as in taxi fleets and emergency services, such as medical assistance, fire-fighters and police. Fleet operation is crucial for these applications: it can mean loss of money and commercial partners in case of industry, os loss of lives in case of emergency services. Controlling the fleet to achieve efficient levels of performance is a difficult problem, though, and becomes even harder as the fleet grows. Research in the area has been linking vehicle fleet operation to Multi-Agent Systems, because vehicle fleets are naturally distributed and Multi-agent System is a convenient abstraction to cope with distributed Artificial Intelligence problems. Therefore, it is proposed a Multi-Agent System to control vehicle fleets, focusing on material handling application in warehouses. The proposed system has three types of agents: Vehicle Agent, Loading Point Agent and Storage Point Agent. Agents interact amongst themselves through messages, trying to efficiently realize the material handling in a warehouse. System implementation is done through a simulation of a warehouse operation, built on top of MASON multi-agent system simulation platform. Task assignment strategies is also an important problem, therefore four strategies are shown and tested using the simulation: CNET, Fuzzy, DynCNET and FiTA. To enable comparison among these strategies, a Genetic Algorithm is employed to systematically search good parameters for each strategy. The proposed system, as well as the simulation, are offered as a framework for development of other vehicle fleets controlling multi-agent systems and/or task assignment strategies.Em várias aplicações, frotas de veículos são um componente importante, transportando materiais e pessoas. Exemplos incluem o manejo de materiais em depósitos, fabricas e terminais portuários, o transporte de pessoas como em frotas de taxis e serviços de emergência, como socorro medico, bombeiros e polícia. A operacao da frota e crucial para essas aplicações: pode significar perda de dinheiro e parceiros comerciais no caso dos exemplos na indústria, ou perda de vidas, no caso de serviços de emergência. Porem, controlar a frota de modo que ela opere eficientemente e um problema difícil, que se torna ainda mais custoso com o aumento da frota. Pesquisas na área tem ligado a operação de frotas de veículos a Sistema Multiagente, notando os fatos de que frotas de veículos são naturalmente distribuídas e que o conceito de Agentes (e, consequentemente, Sistemas Multiagentes) e uma abstração conveniente para lidar com problemas de Inteligencia Artificial de forma distribuída. Com base nisto, e proposto um Sistema Multiagente para controle de frotas de veículos, focando a aplicação dessa frota no manejo de materiais em um depósito. O sistema proposto possui três tipos agentes: Agente de Veículo, Agente de Ponto de Carga e Agente de Ponto de Armazenamento. Os agentes interagem entre si, trocando mensagens a fim de realizar o manejo dos materiais no deposito de forma eficiente. O sistema e implementado na forma de uma simulação de operação de um deposito, construída na plataforma de simulação de sistemas multiagentes MASON. Como a estrategia de associação de tarefas também e um problema importante, quatro estratégias são mostradas e testadas através da simulação: CNET, Fuzzy, DynCNET e FiTA. Para possibilitar comparações entre as estrategias, um Algoritmo Genetico foi utilizado para sistematicamente encontrar bons parâmetros para as quatro estrategias. O sistema proposto, bem como a simulação, são oferecidos como framework para construção de outros sistemas multiagentes para frotas de veículos e/ou estrategias de associação de tarefas.Financiadora de Estudos e Projetosapplication/pdfporUniversidade Federal de São CarlosPrograma de Pós-Graduação em Ciência da Computação - PPGCCUFSCarBRInteligência artificialSistemas multiagentesAssociação de tarefasVeículos a motor - frotasAlgoritmos genéticosMulti-agent systemTask assignemntVehicle fleetWarehouseGenetic algorithmCIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOSistema multiagente para controle de veículos autônomosinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis-1-11c64d62e-b035-4758-ae1e-e72824975942info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARORIGINAL6183.pdfapplication/pdf2878708https://repositorio.ufscar.br/bitstream/ufscar/570/1/6183.pdff9bc336337651cbba67af52d8acb7ec2MD51TEXT6183.pdf.txt6183.pdf.txtExtracted texttext/plain0https://repositorio.ufscar.br/bitstream/ufscar/570/4/6183.pdf.txtd41d8cd98f00b204e9800998ecf8427eMD54THUMBNAIL6183.pdf.jpg6183.pdf.jpgIM Thumbnailimage/jpeg8489https://repositorio.ufscar.br/bitstream/ufscar/570/5/6183.pdf.jpg58b60c56a19a856a906efed4c1424a94MD55ufscar/5702023-09-18 18:31:52.301oai:repositorio.ufscar.br:ufscar/570Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-09-18T18:31:52Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.por.fl_str_mv |
Sistema multiagente para controle de veículos autônomos |
title |
Sistema multiagente para controle de veículos autônomos |
spellingShingle |
Sistema multiagente para controle de veículos autônomos Branisso, Lucas Binhardi Inteligência artificial Sistemas multiagentes Associação de tarefas Veículos a motor - frotas Algoritmos genéticos Multi-agent system Task assignemnt Vehicle fleet Warehouse Genetic algorithm CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
title_short |
Sistema multiagente para controle de veículos autônomos |
title_full |
Sistema multiagente para controle de veículos autônomos |
title_fullStr |
Sistema multiagente para controle de veículos autônomos |
title_full_unstemmed |
Sistema multiagente para controle de veículos autônomos |
title_sort |
Sistema multiagente para controle de veículos autônomos |
author |
Branisso, Lucas Binhardi |
author_facet |
Branisso, Lucas Binhardi |
author_role |
author |
dc.contributor.authorlattes.por.fl_str_mv |
http://lattes.cnpq.br/2989288919102233 |
dc.contributor.author.fl_str_mv |
Branisso, Lucas Binhardi |
dc.contributor.advisor1.fl_str_mv |
Kato, Edilson Reis Rodrigues |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/8517698122676145 |
dc.contributor.authorID.fl_str_mv |
634a423a-72ed-4be2-bbce-a362d6c64ef7 |
contributor_str_mv |
Kato, Edilson Reis Rodrigues |
dc.subject.por.fl_str_mv |
Inteligência artificial Sistemas multiagentes Associação de tarefas Veículos a motor - frotas Algoritmos genéticos |
topic |
Inteligência artificial Sistemas multiagentes Associação de tarefas Veículos a motor - frotas Algoritmos genéticos Multi-agent system Task assignemnt Vehicle fleet Warehouse Genetic algorithm CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
dc.subject.eng.fl_str_mv |
Multi-agent system Task assignemnt Vehicle fleet Warehouse Genetic algorithm |
dc.subject.cnpq.fl_str_mv |
CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
description |
Vehicle fleets are an important component in several applications, moving materials and people. Examples include material handling in warehouses, factories and port terminals, people transportation as in taxi fleets and emergency services, such as medical assistance, fire-fighters and police. Fleet operation is crucial for these applications: it can mean loss of money and commercial partners in case of industry, os loss of lives in case of emergency services. Controlling the fleet to achieve efficient levels of performance is a difficult problem, though, and becomes even harder as the fleet grows. Research in the area has been linking vehicle fleet operation to Multi-Agent Systems, because vehicle fleets are naturally distributed and Multi-agent System is a convenient abstraction to cope with distributed Artificial Intelligence problems. Therefore, it is proposed a Multi-Agent System to control vehicle fleets, focusing on material handling application in warehouses. The proposed system has three types of agents: Vehicle Agent, Loading Point Agent and Storage Point Agent. Agents interact amongst themselves through messages, trying to efficiently realize the material handling in a warehouse. System implementation is done through a simulation of a warehouse operation, built on top of MASON multi-agent system simulation platform. Task assignment strategies is also an important problem, therefore four strategies are shown and tested using the simulation: CNET, Fuzzy, DynCNET and FiTA. To enable comparison among these strategies, a Genetic Algorithm is employed to systematically search good parameters for each strategy. The proposed system, as well as the simulation, are offered as a framework for development of other vehicle fleets controlling multi-agent systems and/or task assignment strategies. |
publishDate |
2014 |
dc.date.available.fl_str_mv |
2014-09-25 2016-06-02T19:06:14Z |
dc.date.issued.fl_str_mv |
2014-06-10 |
dc.date.accessioned.fl_str_mv |
2016-06-02T19:06:14Z |
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 |
BRANISSO, Lucas Binhardi. Sistema multiagente para controle de veículos autônomos. 2014. 130 f. Dissertação (Mestrado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2014. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufscar.br/handle/ufscar/570 |
identifier_str_mv |
BRANISSO, Lucas Binhardi. Sistema multiagente para controle de veículos autônomos. 2014. 130 f. Dissertação (Mestrado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2014. |
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https://repositorio.ufscar.br/handle/ufscar/570 |
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openAccess |
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Universidade Federal de São Carlos |
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Programa de Pós-Graduação em Ciência da Computação - PPGCC |
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UFSCar |
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BR |
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Universidade Federal de São Carlos |
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