Exploiting Many-Valued Variables in MaxSAT

Solving combinatorial optimization problems by reducing them to MaxSAT has shown to be a competitive problem solving approach. Since a lot of optimization problems have many-valued variables, we propose to exploit the domain information of the many-valued variables to enhance MaxSAT-based problem solving: first, we define a new way of encoding weighted maximum constraint satisfaction problems to both Boolean MaxSAT and many-valued MaxSAT; and second, we define a variable selection heuristic that takes into account the domain information and allow us to easily implement a many-valued MaxSAT solver. Moreover, the empirical results provide evidence of the good performance of the new encodings and the new branching heuristic on a representative set of instances.