ITEM TOOLKIT

Binary Decision Diagram (BDD):
Chapter 12 Event Tree 259
The BDD analysis method is an alternative to the Rare Event and Esary-Proschan quantification options. It uses the Binary
Decision Diagram algorithm to obtain cut-sets and quantification results. BDD algorithms distinguish themselves from
conventional quantification methods by returning results that do not involve approximations. Instead, BDD algorithms
produce results that are in accordance with the basic rules of probability theory.
Furthermore, BDD-based algorithms are generally more efficient than other quantification methods. Depending on the
model, these algorithms can identify millions or even billions of cut-sets within seconds. The BDD algorithms embedded in
ITEM products identify all cut-sets for a given model, and then filter out the significant cut-sets based on probability and/or
order.
BDD algorithms do not allow for truncation of probabilistically insignificant elements in the logic. Conventional methods
allow models to be solved by considering only the high-probability cut-sets. Studies have shown however that the numerical
results produced by conventional methods must be treated with care, due to the truncations and approximations involved in
their calculations.