Improved BDD compression by combination of variable ordering techniques

Variable ordering is the most important task done with the Binary Decision Diagrams (BDDs) in order to reduce their size. Many researchers have proposed different algorithms for variable ordering for reduction in size of BDDs. This paper presents an innovative technique by combining the variable ordering algorithms available to get the best possible minimum sized BDDs. Colorado University Decision Diagram (CUDD) package is used as the tool for the process. Testing is carried out on the ISCAS benchmark circuits and better results have been found out.