Exact BDD Minimization for Path-Related Objective Functions

  • Rüdiger Ebendt
  • Rolf Drechsler
Conference paper
Part of the IFIP International Federation for Information Proc book series (IFIPAICT, volume 240)

In this paper we investigate the exact optimization of BDDs with respect to path-related objective functions. We aim at a deeper understanding of the computational effort of exact methods targeting the new objective functions. This is achieved by an approach based on Dynamic Programming which generalizes the framework of Friedman and Supowit. A prime reason for the computational complexity can be identified using this framework. For the first time, experimental results give the minimal expected path length of BDDs for benchmark functions. They have been obtained by an exact Branch&Bound method which can be derived from the general framework. The exact solutions are used to evaluate a heuristic approach. Apart from a few exceptions, the results prove the high quality of the heuristic solutions.


Cost Function Boolean Function Output Node Terminal Node Benchmark Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Rüdiger Ebendt
    • 1
  • Rolf Drechsler
    • 1
  1. 1.Institute of Computer ScienceUniversity of BremenGermany

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