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dc.contributor.authorKhor, Cheng Seong 13:16:03 (GMT) 13:16:03 (GMT)
dc.description.abstractIn view of the current situation of fluctuating high crude oil prices, it is now more important than ever for petroleum refineries to operate at an optimal level in the present dynamic global economy. Acknowledging the shortcomings of deterministic models, this work proposes a hybrid of stochastic programming formulations for an optimal midterm refinery planning that addresses three factors of uncertainties, namely price of crude oil and saleable products, product demand, and production yields. An explicit stochastic programming technique is utilized by employing compensating slack variables to account for violations of constraints in order to increase model tractability. Four approaches are considered to ensure both solution and model robustness: (1) the Markowitz’s mean–variance (MV) model to handle randomness in the objective coefficients of prices by minimizing variance of the expected value of the random coefficients; (2) the two-stage stochastic programming with fixed recourse approach via scenario analysis to model randomness in the right-hand side and left-hand side coefficients by minimizing the expected recourse penalty costs due to constraints’ violations; (3) incorporation of the MV model within the framework developed in Approach 2 to minimize both the expectation and variance of the recourse costs; and (4) reformulation of the model in Approach 3 by adopting mean-absolute deviation (MAD) as the risk metric imposed by the recourse costs for a novel application to the petroleum refining industry. A representative numerical example is illustrated with the resulting outcome of higher net profits and increased robustness in solutions proposed by the stochastic models.en
dc.format.extent1577672 bytes
dc.publisherUniversity of Waterlooen
dc.subjectTwo-stage stochastic programmingen
dc.subjectRefinery planningen
dc.subjectOptimization under uncertaintyen
dc.subjectScenario analysisen
dc.subjectRisk managementen
dc.subjectMean - varianceen
dc.subjectMean-absolute deviation (MAD)en
dc.titleA Hybrid of Stochastic Programming Approaches with Economic and Operational Risk Management for Petroleum Refinery Planning under Uncertaintyen
dc.typeMaster Thesisen
dc.subject.programChemical Engineeringen Engineeringen
uws-etd.degreeMaster of Applied Scienceen

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