A Complete Random Jump Strategy with Guiding Paths

The restart strategy can improve the effectiveness of SAT solvers for satisfiable problems. In 2002, we proposed the so-called random jump strategy, which outperformed the restart strategy in most experiments. One weakness shared by both the restart strategy and the random jump strategy is the ineffectiveness for unsatisfiable problems: A job which can be finished by a SAT solver in one day cannot not be finished in a couple of days if either strategy is used by the same SAT solver. In this paper, we propose a simple and effective technique which makes the random jump strategy as effective as the original SAT solvers. The technique works as follows: When we jump from the current position to another position, we remember the skipped search space in a simple data structure called guiding path. If the current search runs out of search space before running out of the allotted time, the search can be recharged with one of the saved guiding paths and continues. Because the overhead of saving and loading guiding paths is very small, the SAT solvers is as effective as before for unsatisfiable problems when using the proposed technique.

[1]  Max B hm A fast parallel SAT-solver - efficient workload balancing , 2005 .

[2]  Hantao Zhang,et al.  SATO: An Efficient Propositional Prover , 1997, CADE.

[3]  Hantao Zhang,et al.  Latin Squares with Self-Orthogonal Conjugates , 2004, Discret. Math..

[4]  Ewald Speckenmeyer,et al.  A fast parallel SAT-solver — efficient workload balancing , 2005, Annals of Mathematics and Artificial Intelligence.

[5]  Hilary Putnam,et al.  A Computing Procedure for Quantification Theory , 1960, JACM.

[6]  Joao Marques-Silva,et al.  Using Randomization and Learning to Solve Hard Real-World Instances of Satisfiability , 2000, CP.

[7]  Bart Selman,et al.  Heavy-Tailed Distributions in Combinatorial Search , 1997, CP.

[8]  Inês Lynce,et al.  Stochastic Systematic Search Algorithms for Satisfiability , 2001, Electron. Notes Discret. Math..

[9]  Joao Marques-Silva,et al.  Complete Search Restart Strategies for Satisfiability , 2001 .

[10]  Maria Paola Bonacina,et al.  PSATO: a Distributed Propositional Prover and its Application to Quasigroup Problems , 1996, J. Symb. Comput..

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

[13]  Lie Zhu,et al.  Completing the spectrum of r-orthogonal Latin squares , 2003, Discret. Math..

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

[16]  Nachum Dershowitz,et al.  Parallel Multithreaded Satisfiability Solver: Design and Implementation , 2005, PDMC.

[17]  Hantao Zhang,et al.  System Description: Generating Models by SEM , 1996, CADE.

[18]  Roberto J. Bayardo,et al.  Using CSP Look-Back Techniques to Solve Exceptionally Hard SAT Instances , 1996, CP.

[19]  Mark E. Stickel,et al.  Implementing the Davis–Putnam Method , 2000, Journal of Automated Reasoning.