Binary decision diagrams (BDDs) can compactly rep- resent ad-hoc n-ary Boolean constraints. However, there is no gen- eralized arc consistency (GAC) algorithm which exploit BDDs. For example, the global case constraint by SICStus Prolog for ad-hoc constraints is designed for non-Boolean domains. In this paper, we introduce a new GAC algorithm, bddc, for BDD constraints. Our empirical results demonstrate the advantages of a new BDD-based global constraint – bddc is more efficient both in terms of mem- ory and time than the case constraint when dealing with ad-hoc Boolean constraints. This becomes important as the size of the ad- hoc constraints becomes large.
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