Postponing Optimization to Speed Up MAXSAT Solving

Abstract

maxsat is an optimization version of sat that can represent a wide variety of important optimization problems. A recent approach for solving maxsat is to exploit both a sat solver and a Mixed Integer Programming (mip) solver in a hybrid approach. Each solver generates information used by the other solver in a series of iterations that terminates when an optimal solution is found. Empirical results indicate that a bottleneck in this process is the time required by the mip solver, arising from the large number of times it is invoked. In this paper we present a modified approach that postpones the calls to the mip solver. This involves substituting non-optimal solutions for the optimal ones computed by the mip solver, whenever possible. We describe the new approach and some different instantiations of it. We perform an extensive empirical evaluation comparing the performance of the resulting solvers with other state-of-the-art maxsat solvers. We show that the best performing versions of our approach advance the state-of-the-art in maxsat solving.