Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Survey propagation: An algorithm for satisfiability
Random Structures & Algorithms
Additive versus multiplicative clause weighting for SAT
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
SATenstein: automatically building local search SAT solvers from components
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A new method for solving hard satisfiability problems
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Local search with edge weighting and configuration checking heuristics for minimum vertex cover
Artificial Intelligence
Captain Jack: new variable selection heuristics in local search for SAT
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
EagleUP: solving random 3-SAT using SLS with unit propagation
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
Improving stochastic local search for SAT with a new probability distribution
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
Dynamic scoring functions with variable expressions: new SLS methods for solving SAT
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
An empirical study of optimal noise and runtime distributions in local search
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
Choosing probability distributions for stochastic local search and the role of make versus break
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
Satisfying versus falsifying in local search for satisfiability
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
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It is widely acknowledged that stochastic local search (SLS) algorithms can efficiently find models of satisfiable formulae for the Boolean Satisfiability (SAT) problem. There has been much interest in studying SLS algorithms on random k-SAT instances. Compared to random 3-SAT instances which have special statistical properties rendering them easy to solve, random k-SAT instances with long clauses are similar to structured ones and remain very difficult. This paper is devoted to efficient SLS algorithms for random k-SAT instances with long clauses. By combining a novel variable property subscore with the commonly used property score, we design a scoring function named comprehensive score, which is utilized to develop a new SLS algorithm called CScoreSAT. The experiments show that CScoreSAT outperforms state-of-the-art SLS solvers, including the winners of recent SAT competitions, by one to two orders of magnitudes on large random 5-SAT and 7-SAT instances. In addition, CScoreSAT significantly outperforms its competitors on random k-SAT instances for each k = 4; 5; 6; 7 from SAT Challenge 2012, which indicates its robustness.