Managing risk through a flexible recipe framework

A novel approach is proposed that exploits the use of a flexible recipe framework as a better way to handle the risk associated with the scheduling under uncertainty of batch chemical plants. The proposed solution strategy relies on a novel two-stage stochastic formulation that explicitly includes the trade-off between risk and profit at the decision-making level. The model uses a continuous-time domain representation and the generalized notion of precedence. Management of risk is explicitly addressed by including a control measure (i.e., the profit in the worst scenario), as an additional objective to be considered, thus, leading to a multiobjective optimization problem. To overcome the numerical difficulties associated with such mathematical formulation, a decomposition strategy based on the sample average approximation (SAA) is introduced. The main advantages of this approach are illustrated through a case study, in which a set of solutions appealing to decision makers with different attitudes toward risk are obtained. The potential benefits of the proposed flexible recipe framework as a way of managing the risk associated with the plant operation under demand uncertainty are highlighted through comparison with the conventional approach that considers nominal operating conditions. Numerical results corroborate the advantages of exploiting the capabilities of the proposed flexible recipe framework for risk management purposes. (c) 2008 American Institute of Chemical Engineers.