A Clause-Based Heuristic for SAT Solvers

We propose a new decision heuristic for DPLL-based propositional SAT solvers. Its essence is that both the initial and the conflict clauses are arranged in a list and the next decision variable is chosen from the top-most unsatisfied clause. Various methods of initially organizing the list and moving the clauses within it are studied. Our approach is an extension of one used in Berkmin, and adopted by other modern solvers, according to which only conflict clauses are organized in a list, and a literal-scoring-based secondary heuristic is used when there are no more unsatisfied conflict clauses. Our approach, implemented in the 2004 version of zChaff solver and in a generic Chaff-based SAT solver, results in a significant performance boost on hard industrial benchmarks.

[1]  Joao Marques-Silva,et al.  GRASP: A Search Algorithm for Propositional Satisfiability , 1999, IEEE Trans. Computers.

[2]  Jinchang Wang,et al.  Solving propositional satisfiability problems , 1990, Annals of Mathematics and Artificial Intelligence.

[3]  Sharad Malik,et al.  Efficient conflict driven learning in a Boolean satisfiability solver , 2001, IEEE/ACM International Conference on Computer Aided Design. ICCAD 2001. IEEE/ACM Digest of Technical Papers (Cat. No.01CH37281).

[4]  Eugene Goldberg,et al.  BerkMin: A Fast and Robust Sat-Solver , 2002, Discret. Appl. Math..

[5]  Lawrence Ryan.  Efficient algorithms for clause-learning SAT solvers , 2004 .

[6]  Joao Marques-Silva,et al.  The Impact of Branching Heuristics in Propositional Satisfiability Algorithms , 1999, EPIA.

[7]  David A. McAllester,et al.  A Rearrangement Search Strategy for Determining Propositional Satisfiability , 1988, AAAI.

[8]  Sharad Malik,et al.  Chaff: engineering an efficient SAT solver , 2001, Proceedings of the 38th Design Automation Conference (IEEE Cat. No.01CH37232).

[9]  João P. Silva.  The Impact of Branching Heuristics in Propositional Satisfiability Algorithms , 1999 .

[10]  Laurent Simon,et al.  Fifty-Five Solvers in Vancouver: The SAT 2004 Competition , 2004, SAT (Selected Papers.

[11]  Bart Selman,et al.  Planning as Satisfiability , 1992, ECAI.

[12]  Sharad Malik,et al.  Zchaff2004: An Efficient SAT Solver , 2004, SAT (Selected Papers.

[13]  A. Campbell,et al.  Progress in Artificial Intelligence , 1995, Lecture Notes in Computer Science.

[14]  Armin Biere,et al.  A survey of recent advances in SAT-based formal verification , 2005, International Journal on Software Tools for Technology Transfer.

[15]  Bart Selman,et al.  Boosting Combinatorial Search Through Randomization , 1998, AAAI/IAAI.

[16]  Donald W. Loveland,et al.  A machine program for theorem-proving , 2011, CACM.

[17]  Niklas Sörensson,et al.  An Extensible SAT-solver , 2003, SAT.

[18]  Roberto J. Bayardo,et al.  Using CSP Look-Back Techniques to Solve Real-World SAT Instances , 1997, AAAI/IAAI.