3,000,000 Queens in less than one minute
ACM SIGART Bulletin
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
ModGen: theorem proving by model generation
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
Automatic generation of some results in finite algebra
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Domain-independent extensions to GSAT: solving large structured satisfiability problems
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
SEM: a system for enumerating models
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Coloration Neighbourhood Search With Forward Checking
Annals of Mathematics and Artificial Intelligence
AIMSA '00 Proceedings of the 9th International Conference on Artificial Intelligence: Methodology, Systems, and Applications
Parallel Execution of Stochastic Search Procedures on Reduced SAT Instances
PRICAI '02 Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
A Hybrid Seachr Architecture Applied to Hard Random 3-SAT and Low-Autocorrelation Binary Sequences
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Local Probing Applied to Scheduling
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Modelling and Solving Employee Timetabling Problems
Annals of Mathematics and Artificial Intelligence
Combining local search and look-ahead for scheduling and constraint satisfaction problems
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Heuristic techniques for variable and value ordering in CSPs
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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Backtracking techniques are well-known traditional methods for solving many constraint satisfaction problems (CSPs), including the satisfiability (SAT) problem in the propositional logic. In recent years, it has been reported that local search techniques are very effective in solving some large-scale instances of the SAT problem. In this research, we combine the backtracking and local search techniques into a single method for solving SAT and CSPs. When setting a parameter of the method to either of its two extreme values, we obtain the ordinary backtracking procedure or the local search procedure. For some problems, if the parameter takes values in the middle of the two extremes, the new method is much more effective than either backtracking or local search. We tested the method with classical problems like the n-Queens and random SAT instances, as well as some difficult problems from finite mathematics. In particular, using the new method, we solved four open problems in design theory.