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This paper summarizes the use of a linear programming model used to optimize refinery crude oil purchasing while meeting a specific uncertain demand. The model was optimized by maximizing the gross refinery margin (GRM). The model includes catalytic reforming units, naphtha pre-treating units, a kerosene treating unit, a hydrodesulfurization unit, and an isomerization unit. Using the basic linear Bangchak Refinery model in GAMS, it was shown that the results of a successive linear programming (SLP) method depend on the starting point selected. Different initial conditions resulted in different stream output values.
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