Título: |
OPTIMIZATION UNDER UNCERTAINTY FOR INTEGRATED TACTICAL AND OPERATIONAL PLANNING OF THE OIL SUPPLY CHAIN
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Instituição: |
PONTIFÃCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO - PUC-RIO
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Autor(es): |
ADRIANA LEIRAS
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Colaborador(es): |
SILVIO HAMACHER - Orientador
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Data da catalogação: |
15 11:10:20.000000/06/2011 |
Tipo: |
THESIS
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Idioma(s): |
ENGLISH - UNITED STATES |
Referência [pt]: |
https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/DEI/serieConsulta.php?strSecao=resultado&nrSeq=17652@1 |
Referência [en]: |
https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/DEI/serieConsulta.php?strSecao=resultado&nrSeq=17652@2 |
Referência DOI: |
https://doi.org/10.17771/PUCRio.acad.17652
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Resumo:
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The uncertain nature and high economic incentives of the refining business
are driving forces for improvements in the refinery planning process. Decisions
made at the oil chain differ mainly in the range of activities (spatial integration)
and planning horizon (temporal integration). This thesis purpose is to address the
problem of the oil chain integration under uncertainty at different decision levels.
Tactical and operational mathematical programming models are proposed. The
tactical model maximizes the expected profit of the supply chain and allocates the
production targets to refineries taking logistics constraints into account. The
operational model maximizes the expected profit of each refinery determining the
amount of material that is processed at each process unit in a given period. Both
models are two-stage stochastic linear programs where uncertainty is incorporated
in the dominant random parameters at each level (price and demand at the tactical
level and oil supply and process capacity unit at the operational level).Spatial
integration is discussed at the tactical level (considering supply chain), whereas
the temporal integration is discussed in the interaction between the two levels.
Two temporal integration approaches are considered: hierarchical, where the flow
of information is only from the tactical to the operational model, and iterative,
where there is feedback from the tactical to the operational model. An industrial
scale study was conducted to discuss the benefits of integration in a stochastic
environment. Results are offered in the context of a study using data from the
Brazilian oil industry to demonstrate the effectiveness of the proposed approaches.
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