Minimization of BDDs using linear transformations based on evolutionary techniques

Binary Decision Diagrams (BDDs) are frequently used in many applications in VLSI CAD. However, they are very sensitive to the variable ordering and their size often becomes infeasible. Recently, a new approach for BDD minimization based on Linear Transformations (LTs), i.e., a special type of spectral technique, has been proposed. We present an Evolutionary Algorithm (EA) to find an LT for which the BDD becomes small. The genetic operators make use of problem specific knowledge. Experimental results are given to show the efficiency of our approach