Solving Intensional Weighted CSPs by Incremental Optimization with BDDs

We present a method for solving weighted Constraint Satisfaction Problems, based on translation into a Constraint Optimization Problem and iterative calls to an SMT solver, with successively tighter bounds of the objective function. The novelty of the method herewith described lies in representing the bound constraint as a shared Binary Decision Diagram, which in turn is translated into SAT. This offers two benefits: first, BDDs built for previous bounds can be used to build the BDDs for new (tighter) bounds, considerably reducing the BDD construction time; second, as a by-product, many clauses asserted to the solver in previous iterations can be reused.

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