Optimal discretization for decision analysis

The use of discretization in decision analysis allows practitioners to use only a few assessments to estimate the certain equivalent (CE) or expected value of a decision without knowing the functional form of the distribution of each uncertainty. The discretization shortcuts are fast, but are created with a specific distribution, or families of distributions in mind. The discretizations are not formulated with the decision problem in mind. Each discretization is specific to one uncertainty distribution, or is even more generalized. In this article, we introduce a novel mathematical formulation for selecting an optimal discretization for a specific problem. With optimal discretization, a decision analyst can use the newly-created shortcuts in repeated decisions and improve the expected accuracy of the CE calculations.