Most Refineries historically models are deterministic, that is, they use nominal parameter values without taking into
consideration the uncertainty in process, demands, refinery parameters, etc. And as a consequence, they are unable
to perform risk management. In this paper a variety of methodologies for financial risk management in engineering decision have been already developed. We follow the approach presented by Barbaro and Bagajewicz (2004), who
used two-stage stochastic programming model and you, can find all other approaches analyzed and discussed. The
problem addressed here is that of determining the crude oil to purchase and decide on the production level of different products given predicts of demands. The profit is maximized taking into account revenues, crude oil costs, inventory costs, and lost demand costs. The model was tested using data from the Refinery owned by the State Oil Marketing Organization (SOMO) Company, Iraq. The results show that the stochastic model can forecast higher expected profit and lower risk compared to the deterministic model
