Revisiting Counting Solutions for the Global Cardinality Constraint

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Giovanni Lo Bianco
Xavier Lorca
Charlotte Truchet
Gilles Pesant


Counting solutions for a combinatorial problem has been identified as an important concern within the Artificial Intelligence field. It is indeed very helpful when exploring the structure of the solution space. In this context, this paper revisits the computation process to count solutions for the global cardinality constraint in the context of counting-based search. It first highlights an error and then presents a way to correct the upper bound on the number of solutions for this constraint.

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