Defesa de Tese de Doutorado – Leonardo Salsano de Assis – 28/5/2020
Defesa de Tese de Doutorado | |
Aluno | Leonardo Salsano de Assis |
Orientador | Prof. Eduardo Camponogara, Dr. – DAS/UFSC |
Coorientador | Prof. Ignacio Grossmann, Dr. – Carnegie Mellon University (EUA) |
Data
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28/5/2020 (quinta-feira) – 8h30
Videoconferência (https://us02web.zoom.us/j/84669789227) |
Banca |
Prof. Eduardo Camponogara, Dr. – DAS/UFSC (presidente);
Prof. Leandro Magatão, Dr. – DAMEC/UTFPR; Prof. Erlon Finardi, Dr. – DELT/UFSC; Prof. Werner Kraus Junior, Dr. – DAS/UFSC; Prof. Laio Oriel Seman, Dr. – UNIVALI. |
Título | Operational Management of Crude Oil Supply: models and solution strategies |
Abstract: The supply of crude oil from offshore platforms to refineries is an important problem faced by vertically integrated oil companies which control production, transportation, storage and refining. In deep-water offshore oilfields, Floating, Production, Storage and Offloading units (FPSOs) produce and store crude oil which is transferred to an oil terminal by a fleet of shuttle tankers. Upon arrival at the terminal, a shuttle tanker unloads crude oil through a pipeline into Storage Tanks (STs). The crude oil is then pumped through a pipeline from the storage tanks to Charging Tanks (CTs), and subsequently sent to Crude Distillation Units (CDUs) at the refinery. This dissertation advances the state of the art on the management of crude oil supply by proposing models and algorithms to consider elements of the operational decision level in an integrated fashion, which leads to the Operational Management of Crude Oil Supply (OMCOS). OMCOS comprises both the upstream (i.e., platforms, vessels and terminal) and the midstream (i.e., CDUs at the refinery) segments. In relation to the technical literature, OMCOS combines elements of Maritime Inventory Routing (MIR) with Crude Oil Scheduling (COS) by considering decisions at the operational level (i.e., scheduling and crude oil blending) and tactical level (i.e., inventory control and resource allocation). Such an integration leads to non-convex Mixed Integer Non-Linear Programming (MINLP) models that are addressed in this dissertation. The main contributions are the following:
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