Published online by Cambridge University Press: 29 November 2013
In this paper we present a robust real-time optimization method for the online linear oilblending process. The blending process consists in determining the optimal mix ofcomponents so that the final product satisfies a set of specifications. We examinedifferent sources of uncertainty inherent to the blending process and show how to addressthis uncertainty applying the Robust Optimization techniques. The polytopal structure ofour problem permits a simplified robust approach. Our method is intended to avoidreblending and we measure its performance in terms of the blend quality giveaway andfeedstocks prices. The difference between the nominal and the robust optimal values (theprice of robustness) provides a benchmark for the cost of reblending which is difficult toestimate in practice. This new information can be used to adjust the level of conservatismin the model. We analyze the feasibility of a blend to be produced from a set offeedstocks when the heel of a previous blend is used in the composition of the new blend.Additional critical information for the control system is then produced.