Recent directions in netlist partitioning: a survey
Integration, the VLSI Journal
Experimental results on the crossover point in random 3-SAT
Artificial Intelligence - Special volume on frontiers in problem solving: phase transitions and complexity
A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
An empirical analysis of search in GSAT
Journal of Artificial Intelligence Research
Domain-independent extensions to GSAT: solving large structured satisfiability problems
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Efficient 2 and 3-Flip Neighborhood Search Algorithms for the MAX SAT
COCOON '98 Proceedings of the 4th Annual International Conference on Computing and Combinatorics
Random walk with continuously smoothed variable weights
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
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One of the important components of a local search strategy for satisfiability testing is the variable selection heuristic, which determines the next variable to be flipped. In a greedy local search such as GSAT, the major decision in variable selection is the strategy for breaking ties between variables that offer the same improvement in the number of unsatisfied clauses. In this paper, we analyze a number of tie-breaking strategies for GSAT and evaluate the strategies empirically using randomly generated 3-SAT instances from a hard distribution of random instances. We find that the property of fairness, which was proposed in the literature as being the critical property of a successful variable strategy, is not a sufficient property, and show that randomness plays a significant role in the success of variable selection heuristics.