Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
A machine program for theorem-proving
Communications of the ACM
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Guided Local Search for Solving SAT and Weighted MAX-SAT Problems
Journal of Automated Reasoning
A Parallel GRASP for MAX-SAT Problems
PARA '96 Proceedings of the Third International Workshop on Applied Parallel Computing, Industrial Computation and Optimization
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
GASAT: a genetic local search algorithm for the satisfiability problem
Evolutionary Computation
Iterated robust tabu search for MAX-SAT
AI'03 Proceedings of the 16th Canadian society for computational studies of intelligence conference on Advances in artificial intelligence
A Tabu history driven crossover operator design for memetic algorithm applied to Max-2SAT-problems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
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Various algorithms have been suggested for the Max-SAT problem. The solution for the Max-2SAT is the starting point for a selection of these approximation algorithms. This paper aims at introducing approaches for Max-2SAT by a brief review of the basic ideas. Moreover, a memetic algorithm for Max-2SAT problems based on a specific crossover operator and an improved tabu search stage is presented. Simulation performed on several instances of Max-2SAT reference problems are used to evaluate the different memetic algorithm strategies applied in our approach. The overall performance is verified by empirical simulation and is used to compare the developed approach to other state up-to-date and of the art algorithms.