Detalhes bibliográficos
| Ano de defesa: |
2014 |
| Autor(a) principal: |
Sousa Filho, César Augusto Chaves e |
| Orientador(a): |
Não Informado pela instituição |
| 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/11602
|
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. |
