Speeding up constraint propagation by redundant modeling

Abstract

The paper describes a simple modeling and programming approach for speeding up constraint propagation. The idea, although similar to redundant constraints, is based on the concept of redundant modeling. We define CSP model and model redundancy formally, and show how mutually redundant models can be combined and connected using channeling constraints. The combined model contains the original but redundant models as sub-models. Channeling constraints allow the sub-models to cooperate during constraint-solving by propagating constraints freely amongst the sub-models. This extra level of pruning and propagation activities becomes the source of execution speedup. We apply our method to the design and construction of a real-life nurse rostering system. Experimental results provide empirical evidence in line with our prediction.