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Estatística
Título: MAINTENANCE LOGISTICS OPTIMIZATION BASED ON MATERIALS DISTRIBUTION PLANNING IN A RAILWAY
Autor: HUGO COSTA CAMPBEL
Colaborador(es): RAFAEL MARTINELLI PINTO - Orientador
EDUARDO PESTANA DE AGUIAR - Coorientador
Catalogação: 20/ABR/2021 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=52313&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=52313&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.52313
Resumo:
The use of optimization tools highlights a relevant differential to companies in terms of improving processes, systems and performance. In this context, the search for simple and effective programming models for problem solving contributes to the adaptation of existing models to attend this increasing demand. Currently, the railway transport seeks to optimize its processes in order to increase its competitiveness and efficiency when compared to road transport. This study, focused on improving processes in the railway, aims to realize the distribution planning of maintenance materials in a railway network with the lowest feasible operating cost. For this, the problem is modeled as a mixedinteger programming problem and it aims to make the process more efficient, with waste reduction and resource optimization. The obtained results were compared to the current distribution process in order to measure gains in process and in reducing costs and resources. The model proved to be efficient in both time and solution quality when compared to the current one, presenting a reduction of 20 percent to 26 percent in the distribution costs, depending on the analyzed warehouses. In addition, the study has also indicated a reduction in the distribution costs in all tested locations and the distance among those locations and their warehouses leads to a greater reduction in the logistic costs.
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