A new scheme to compute variable orders for binary decision diagrams

Abstract
Introduces some new methods for estimating the "importance" of a variable in a Boolean function, and uses them to compute variable orders for OBDD construction. These measures are based on information theoretic criteria, and require the computation of the entropy of a variable in a given function. These entropy measures prove quite effective in distinguishing the importance of variables. Experimental results show this to be a very encouraging approach to help in the solution of this well known problem.

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