A BAYESIAN NETWORK FOR QUANTIFYING UNCERTAINTY FOR DISTRIBUTION PLANNING MODEL

Abstract

Uncertainty is a key issue in engineering design: optimal solutions generally do not involve safety margins, but real systems involve having uncertainty, variability, and error. For example, geometry, material parameters, boundary conditions, or even the model itself includes uncertainty. To provide safe designs, uncertainty must be considered in optimization models.