Detalhes bibliográficos
| Ano de defesa: |
2017 |
| Autor(a) principal: |
PINHEIRO, Eggo Henrique Freire
 |
| Orientador(a): |
OLIVEIRA, Alexandre César Muniz de
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| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal do Maranhão
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| Programa de Pós-Graduação: |
PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIA DA COMPUTAÇÃO/CCET
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| Departamento: |
DEPARTAMENTO DE INFORMÁTICA/CCET
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| País: |
Brasil
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| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
https://tedebc.ufma.br/jspui/handle/tede/1986
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Resumo: |
Freight railways are the major means of transportation of bulk material, such as iron ore from the origin to the destination. Usually for heavy haul railways, the destination is a port. For the last few years there has been a fast growing demand. However, railway infrastructure capacity increasing is very expensive and require a lot of investiment budget. Therefore, an improvement of train scheduling process is needed to ensure the best and efficient use of the current railway. Nevertheless, in some situations it is overwhelmingly complex to solve, an NP-hard problem. Since all the previous work provided on the Train Timetable Problem is usually only applied locally to a single railway, this work provides a public base benchmark of test railways built by heuristcs. Moreover, this work deals with the train timetabling problem applied to mixed traffic railways with both cargo trains and passenger trains sharing the same resources with different priorities. It is proposed a new mathematical model extended from literature previous work intended to avoid infeasible solutions instead reparing or discarding on these cases. This model contains additional support for parallel multi-track for several railway’s signaling system approaches context as well as overtaking on it without deadlocks possibility. This model considers trains in current position and future departure planned. To achieve an improved train scheduling is applied the Evolutionary Clustering Search (ECS) with multi heuristics approaches and a modified mutation operator of Genetic Algorithm as component of ECS. The experiments shows ECS outperforms almost all tests scenario and the modified mutation operator strongly improve the results |
