Quasi-Exact BDD Minimization Using Relaxed Best-First Search
ISVLSI '05 Proceedings of the IEEE Computer Society Annual Symposium on VLSI: New Frontiers in VLSI Design
Weighted A∗ search -- unifying view and application
Artificial Intelligence
A microcanonical optimization algorithm for BDD minimization problem
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
On threshold BDDs and the optimal variable ordering problem
COCOA'07 Proceedings of the 1st international conference on Combinatorial optimization and applications
Variable ordering for the application of BDDs to the maximum independent set problem
CPAIOR'12 Proceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
| Hi-index | 0.03 |
Ordered binary decision diagrams (BDDs) are a data structure for efficient representation and manipulation of Boolean functions. They are frequently used in logic synthesis and formal verification. The size of the BDDs depends on a chosen variable ordering, i.e., the size may vary from linear to exponential, and the problem of Improving the variable ordering is known to be NP-complete. In this paper, we present a new exact branch and bound technique for determining an optimal variable order. In contrast to all previous approaches that only considered one lower bound, our method makes use of a combination of three bounds and, by this, avoids unnecessary computations. The lower bounds are derived by generalization of a lower bound known from very large scale integration design. They allow one to build the BDD either top down or bottom up. Experimental results are given to show the efficiency of our approach.