Finding almost-satisfying assignments
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Improved approximation algorithms for MAX SAT
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Improved approximation algorithms for MAX SAT
Journal of Algorithms
Approximation Algorithms for MAX 4-SAT and Rounding Procedures for Semidefinite Programs
Proceedings of the 7th International IPCO Conference on Integer Programming and Combinatorial Optimization
Mechanism design for software agents with complete information
Decision Support Systems - Special issue: Decision theory and game theory in agent design
GRASP with path relinking for the weighted MAXSAT problem
Journal of Experimental Algorithmics (JEA)
ESA'11 Proceedings of the 19th European conference on Algorithms
Improved approximation algorithms for MAX NAE-SAT and MAX SAT
WAOA'05 Proceedings of the Third international conference on Approximation and Online Algorithms
GRASP with path-relinking for the weighted maximum satisfiability problem
WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms
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MAX SAT (the maximum satisfiability problem) is stated as follows: given a set of clauses with weights, find a truth assignment that maximizes the sum of the weights of the satisfied clauses. In this paper, we consider approximation algorithms for MAX SAT proposed by Yannakakis and Goemans-Williamson and present an approximation algorithm which is an improvement of Yannakakis' algorithm. Although Yannakakis' original algorithm has no better performance guarantee than Goemans-Williamson, our improved algorithm has a better performance guarantee and leads to a 0.770-approximation algorithm.