GRASP: A Search Algorithm for Propositional Satisfiability
IEEE Transactions on Computers
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
SATO: An Efficient Propositional Prover
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
ICAL '99 Proceedings of the 26th International Colloquium on Automata, Languages and Programming
Worst-case upper bounds for MAX-2-SAT with an application to MAX-CUT
Discrete Applied Mathematics - The renesse issue on satisfiability
A new approach to proving upper bounds for MAX-2-SAT
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
A new algorithm for optimal 2-constraint satisfaction and its implications
Theoretical Computer Science - Automata, languages and programming: Algorithms and complexity (ICALP-A 2004)
Automated generation of simplification rules for SAT and MAXSAT
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Algorithms based on the treewidth of sparse graphs
WG'05 Proceedings of the 31st international conference on Graph-Theoretic Concepts in Computer Science
MAX-SAT for formulas with constant clause density can be solved faster than in O(2n) time
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Linear-programming design and analysis of fast algorithms for Max 2-CSP
Discrete Optimization
A New Upper Bound for Max-2-SAT: A Graph-Theoretic Approach
MFCS '08 Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science
A universally fastest algorithm for Max 2-Sat, Max 2-CSP, and everything in between
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
A new algorithm for parameterized MAX-SAT
IPEC'12 Proceedings of the 7th international conference on Parameterized and Exact Computation
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To solve a problem on a given CNF formula F a splitting algorithm recursively calls forF[v] and F[-v] for a variable v. Obviously, after the first call an algorithm obtains some information on the structure of the formula that can be used in the second call. We use this idea to design new surprisingly simple algorithms for the MAX-SAT problem. Namely, we show that MAX-SAT for formulas with constant clause density can be solved in time cn, where c m/5.88, where m is the number of clauses (this improves the bound 2m/5.769 proved independently by Kneis et al. and by Scott and Sorkin).