Planning for a Big Bang in a Supply Chain: Fast Hedging for Production Indicators

Abstract

We concern ourselves with the process of making optimized production planning decisions in the face of low frequency, high impact uncertainty, which takes the form of a small number of discrete scenarios. Computational results provide evidence that the computational effort for the full stochastic mixed integer problem can be reduced by first solving scenario sub-problems and then blending them to find values for some of the binary variables.