Risk and uncertainty in managing chemical manufacturing supply chains

A new metric is presented for evaluating supply chain design and planning p rojects in which there are significant elements of uncertainty and thus ris k. The risk premium construct provides the basis for a rational balance bet ween expected value of investment performance and variance. An effective po lytope integration method for evaluation of expected values and variances o f revenue is adopted which can account for the effects of demand uncertaint ies on revenue while recognizing the uncertainty in inventory over time. Th e combination of these elements with conventional deterministic mathematica l programming models offers the promise of providing an effective approach to accommodating uncertainties and a rational basis for balancing risk. A s mall scale example is used to contrast the proposed approach with conventio nal stochastic programming-based methods. Another example shows the nature of the return and risk for a multiperiod production plan with stochastic ef fects on inventory. The computational complexities which are introduced by the risk premium construct are reviewed, and some directions for future res earch discussed. (C) 2000 Elsevier Science Ltd. All rights reserved.