In Search of the Best Constraint Satisfaction Search


We present the results of an empirical study of several constraint satisfaction search algorithms and heuristics. Using a random problem generator that allows us to create instances with given characteristics, we show how the relative performance of various search methods varies with the number of variables, the tightness of the constraints, and the sparseness of the constraint graph. A version of backjumping using a dynamic variable ordering heuristic is shown to be extremely effective on a wide range of problems. We conducted our experiments with problem instances drawn from the 50% satisfiable range.

Extracted Key Phrases

1 Figure or Table


Citations per Year

62 Citations

Semantic Scholar estimates that this publication has 62 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@inproceedings{Frost1994InSO, title={In Search of the Best Constraint Satisfaction Search}, author={Daniel Frost and Rina Dechter}, booktitle={AAAI}, year={1994} }