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ETDs @PUC-Rio
Estatística
Título: CONTAINERS ROAD TRANSPORTATION OPTIMIZATION: EXACT AND HEURISTICS METHODS
Autor: SAULO BORGES PINHEIRO
Colaborador(es): SILVIO HAMACHER - Orientador
Catalogação: 03/SET/2018 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=34991&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=34991&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.34991
Resumo:
Despite the Brazilian continental scale, the magnitude of its coastline and the proximity between the coast and the large urban centers, the transport of cargo in containers using cabotage is still very limited in Brazil. In this scenario, the Brazilian cabotage ship-owners seek to provide door-to-door services, achieving economies of scale in procurement for suppliers that perform road ends, thus increasing the competitiveness of cabotage with its main competitor, the transportation by trucks. This work presents two models that aim to minimize the total cost of hiring road suppliers to a list of demands that must be performed. The first is a mathematical model based on integer linear programming, the second is an algorithm that uses a greedy heuristic. The models were developed and tested in real scenarios, experienced by a Brazilian cabotage ship-owner for a period of time. The results of the two models, which are compared among each other and with the manually solutions performed by the company’s employees, show that the solutions of optimization models are much better than the manual solutions. The results also show that the greedy algorithm achieves very close results to the exact method, proving to be very useful given the ease of its implementation.
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