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Estatística
Título: STOCHASTIC OPTIMIZATION MODEL TO THE BIODIESEL SUPPLY CHAIN STRATEGIC PLANNING
Autor: PEDRO SENNA VIEIRA
Colaborador(es): SILVIO HAMACHER - Orientador
FABRICIO CARLOS PINHEIRO OLIVEIRA - Coorientador
Catalogação: 14/FEV/2017 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=29136&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=29136&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.29136
Resumo:
The Brazilian Program for Biodiesel Use and Production highlights the production of biodiesel from castor seeds, as a non-polluting energy source and as a job generation in poor regions. However, an obstacle to biodiesel production comes from the castor seeds poor production conditions and lack of infrastructure and logistics. This work aims to present a contribution to solve this problem, performing a strategic planning optimization of this biodiesel supply chain. The main objective is to minimize total storage costs and grains transportation to the crushing plant. An important peculiarity of this problem is the production uncertainty, which affects the supply chain design. Thus, we propose a stochastic Mixed Integer Linear Programming (MILP) model with two stage and multi-stage formulations. This model was tested on a real case in the Brazilian s semi-arid region. As a result, in order to obtain the minimum total cost, we present the logistics network flow design and warehouses assignments for both formulations. Lastly, we present a comparison between these formulations highlighting that the flexibility gain provided by the multi-stage model results in a lower total logistic cost.
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