Improving Arc-Consistency Algorithms with Double-Support Checks

Arc-consistency algorithms are widely used to simplify Constraint Satisfaction Problems. The new notion of a double-support check is presented to improve the average performance of arc-consistency algorithms. The improvement is that, where possible, consistencychecks are used to find supports for two values, one value in the domain of each variable, which were previously known to be unsupported. It is motivated by the insight that in order to minimize the number of consistency-checks it is necessary to maximize the number of uncertainties which are resolved per check. The idea is used to improve AC-3 and DEE and results in a new general purpose arc-consistency algorithm called AC-3b. Experimental results of a comparison of AC-3, DEE, AC-3b and AC-7 are presented. The results seem to indicate that AC-3b always performs better than DEE and usually performs better than both AC-3 and AC-7 for the set of testproblems under consideration.