Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Properties of complexity measures for prams and wrams
Theoretical Computer Science
Finding the Optimal Variable Ordering for Binary Decision Diagrams
IEEE Transactions on Computers
Lower bounds for depth-restricted branching programs
Information and Computation
Efficient implementation of a BDD package
DAC '90 Proceedings of the 27th ACM/IEEE Design Automation Conference
Shared binary decision diagram with attributed edges for efficient Boolean function manipulation
DAC '90 Proceedings of the 27th ACM/IEEE Design Automation Conference
DAC '91 Proceedings of the 28th ACM/IEEE Design Automation Conference
Symbolic Boolean manipulation with ordered binary-decision diagrams
ACM Computing Surveys (CSUR)
Randomized algorithms
Who are the variables in your neighborhood
ICCAD '95 Proceedings of the 1995 IEEE/ACM international conference on Computer-aided design
Binary decision diagrams and beyond: enabling technologies for formal verification
ICCAD '95 Proceedings of the 1995 IEEE/ACM international conference on Computer-aided design
Improving the Variable Ordering of OBDDs Is NP-Complete
IEEE Transactions on Computers
On the effect of local changes in the variable ordering of ordered decision diagrams
Information Processing Letters
Some optimal inapproximability results
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Dynamic variable ordering for ordered binary decision diagrams
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
Fast exact minimization of BDDs
DAC '98 Proceedings of the 35th annual Design Automation Conference
Variable orderings and the size of OBDDs for random partially symmetric Boolean functions
Random Structures & Algorithms
Branching programs and binary decision diagrams: theory and applications
Branching programs and binary decision diagrams: theory and applications
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Multi-Terminal Binary Decision Diagrams: An Efficient DataStructure for Matrix Representation
Formal Methods in System Design
Algebric Decision Diagrams and Their Applications
Formal Methods in System Design
On the Complexity of Constructing Optimal Ordered Binary Decision Diagrams
MFCS '94 Proceedings of the 19th International Symposium on Mathematical Foundations of Computer Science 1994
The Complexity of the Optimal Variable Ordering Problems of Shared Binary Decision Diagrams
ISAAC '93 Proceedings of the 4th International Symposium on Algorithms and Computation
On the Existence of Polynomial Time Approximation Schemes for OBDD Minimization (Extended Abstract)
STACS '98 Proceedings of the 15th Annual Symposium on Theoretical Aspects of Computer Science
The complexity of minimizing and learning OBDDs and FBDDs
Discrete Applied Mathematics
Distributed Hybrid Genetic Programming for Learning Boolean Functions
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
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
Minimization of decision trees is hard to approximate
Journal of Computer and System Sciences
Representation of graphs by OBDDs
Discrete Applied Mathematics
Weighted A∗ search -- unifying view and application
Artificial Intelligence
Incremental algorithms for approximate compilation
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
A framework for quasi-exact optimization using relaxed best-first search
KI'06 Proceedings of the 29th annual German conference on Artificial intelligence
Survey: Linear Temporal Logic Symbolic Model Checking
Computer Science Review
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The size of ordered binary decision diagrams (OBDDs) is determinedby the chosen variable ordering. A poor choice may cause an OBDD tobe too large to fit into the available memory. The decision variantof the variable ordering problem is known to be NP-complete.We strengthen this result by showing that, unlessP=NP, for each constant c1 there is nopolynomial time approximation algorithm with the performance ratioc for the variable ordering problem, i.e., no polynomialtime algorithm that guarantees the computation of a variableordering so that the resulting OBDD size is larger than the minimumsize by a factor of at most c. This result justifies, alsofrom a theoretical point of view, the use of heuristics for thevariable ordering problem.