  We study the susceptibility propagation, a message-passing algorithm to
compute correlation functions. It is applied to constraint satisfaction
problems and its accuracy is examined. As a heuristic method to find a
satisfying assignment, we propose susceptibility-guided decimation where
correlations among the variables play an important role. We apply this novel
decimation to locked occupation problems, a class of hard constraint
satisfaction problems exhibited recently. It is shown that the present method
performs better than the standard belief-guided decimation.
