A New Filtering Based on Decomposition of Constraint Sub-Networks

In this paper, we introduce a new partial consistency for constraint networks which is called Structural Consistency of level w and is denoted w-SC consistency. This consistency is based on a new approach. While conventional consistencies generally rely on local properties extended to the entire network, this new partial consistency considers global consistency on subproblems. These subproblems are defined by partial constraint graphs whose tree-width is bounded by a constant w. We introduce a filtering algorithm which achieves w-SC consistency. We also analyze w-SC filtering w.r.t. other classical local consistencies to show that this consistency is generally incomparable although this consistency can be regarded as a special case of inverse consistency. Finally, we present experimental results to assess the usefulness of this approach. We show that w-SC is a significantly more powerful level of filtering and more effective w.r.t. the runtime than SAC. We also show that w-SC is a complementary approach to AC or SAC. So we can offer a combination of filterings, whose power is greater than w-SC or SAC.