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Frederico Gadelha Guimarãeshttp://lattes.cnpq.br/2472681535872194Pauline Catriona HaddowRasul EnayatifarGilberto Reynoso MezaPuca Huachi Vaz PennaRoberto Gomes RibeiroLucas de Souza Batistahttp://lattes.cnpq.br/7528357026621505Babak Rezaei2023-10-26T18:48:42Z2023-10-26T18:48:42Z2023-08-30http://hdl.handle.net/1843/60098The Vehicle Routing Problem (VRP) is one of the most significant problems in operational research today. VRP has a vast range of application fields such as transportation, logistics, manufacturing, relief systems and communication. To suit the needs of different real-world VRP scenarios, many models of VRP have been developed - CVRP (Capacitated VRP) being the classical form. In this study, at first a hybrid algorithm (ICAHGS) for solving CVRP is proposed, combining a refined ICA (Imperialist Competitive Algorithm) as the primary evolutionary and multi-population method, and a Hybrid Genetic Search (HGSCVRP) algorithm as an enhanced local search and population management strategy within the ICA framework. ICAHGS has been compared to several state-of-the-art algorithms from literature. The results of this comparison, which include both classical benchmark instances and real-world applications, demonstrate the competitive performance of the proposed algorithm. Afterwards, Dynamic Population Island GA and HGS (DPIGA-HGS) is introduced, which is a novel hybrid metaheuristic model. DPIGA-HGS integrates a specialized island model (DPIGA) and a refined HGS as its local search engine within each island. The primary objective of DPIGA-HGS is to contribute to the advancement of the field by proposing a new variant of Island GA and simultaneously achieving improved optimization results in comparison to ICAHGS. The results of the comparative analyses revealed the superior performance of DPIGA-HGS when pitted against other state-of-the art algorithms, including ICAHGS. Across multiple benchmark datasets, DPIGA-HGS showcased its prowess by achieving a significant number of BKS (Best Known Solution), outperforming its competitors in various instances.O Problema de Roteamento de Veículos (VRP) é um dos problemas mais significativos na pesquisa operacional atualmente. O VRP tem uma ampla gama de campos de aplicação, como transporte, logística, manufatura, sistemas de auxílio e comunicação. Para atender às necessidades de diferentes cenários do VRP no mundo real, muitos modelos de VRP foram desenvolvidos - sendo o CVRP (VRP capacitado) a forma clássica. Neste estudo, é proposto inicialmente um algoritmo híbrido (ICAHGS) para resolver o CVRP, combinando um ICA (Algoritmo Competitivo Imperialista) refinado como o método evolucionário primário e de múltiplas populações, e um algoritmo de Busca Genética Híbrida (HGS-CVRP) como uma estratégia aprimorada de busca local e gerenciamento de população dentro do framework do ICA. O ICAHGS foi comparado com diversos algoritmos de ponta da literatura. Os resultados dessa comparação, que incluem tanto instâncias de referência clássicas quanto aplicações do mundo real, demonstram o desempenho competitivo do algoritmo proposto. Posteriormente, é introduzido o Algoritmo Genético de Ilhas com População Dinâmica e HGS (DPIGA-HGS), que é um novo modelo híbrido de metaheurística. O DPIGA-HGS integra um modelo de ilhas especializado (DPIGA) e um HGS refinado como seu mecanismo de busca local dentro de cada ilha. O objetivo principal do DPIGA-HGS é contribuir para o avanço do campo, propondo uma nova variante do Algoritmo Genético de Ilhas e, simultaneamente, alcançando resultados de otimização aprimorados em comparação com o ICAHGS. Os resultados das análises comparativas revelaram o desempenho superior do DPIGA-HGS quando comparado a outros algoritmos de ponta, incluindo o ICAHGS. Através de múltiplos conjuntos de dados de referência, o DPIGA-HGS demonstrou sua habilidade ao alcançar um número significativo de solução mais conhecida (BKS), superando seus concorrentes em várias instâncias.engUniversidade Federal de Minas GeraisPrograma de Pós-Graduação em Engenharia ElétricaUFMGBrasilENG - DEPARTAMENTO DE ENGENHARIA ELÉTRICAEngenharia elétricaVeículosAlgoritmos genéticosGenéticaAlgoritmosInteligência artificialCiência da computaçãoCálculos numéricosVehicle routing problemEvolutionary computationImperialist competitive algorithmHybrid genetic searchIsland genetic algorithmMulti-population genetic algorithmCombining genetic local search into multi-population evolutionary algorithms for the capacitated vehicle routing probleminfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSElicense.txtlicense.txttext/plain; charset=utf-82118https://repositorio.ufmg.br/bitstream/1843/60098/2/license.txtcda590c95a0b51b4d15f60c9642ca272MD52ORIGINALFinal Thesis - Babak Rezaei.pdfFinal Thesis - Babak Rezaei.pdfapplication/pdf8704422https://repositorio.ufmg.br/bitstream/1843/60098/1/Final%20Thesis%20-%20Babak%20Rezaei.pdf4fc3c49b2ce108a33ae32b0695f1a171MD511843/600982023-10-26 15:48:43.254oai:repositorio.ufmg.br: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ório InstitucionalPUBhttps://repositorio.ufmg.br/oaiopendoar:2023-10-26T18:48:43Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
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