Approximate algorithms for minimization of binary decision diagrams on the basis of linear transformations of variables

Abstract

Algorithms for an approximate minimization of binary decision diagrams (BDD) on the basis of linear transformations of variables are proposed. The algorithms rely on the transformations of only adjacent variables and have a polynomial complexity relative to the size of the table that lists values of the function involved.