Many combinatorial optimization problems can be phrased in the language of constraint satisfaction problems. We introduce a graph neural network architecture for solving such optimization problems. The architecture is generic; it works for all binary constraint satisfaction problems. https://www.infonoticiasgandia.com/product-category/coffee-espresso-tea-machine-cleaners/