Answer Set Programming via Mixed Integer Programming

Answer set programming is a programming paradigm where a given problem is formalized as a logic program whose answer sets correspond to the solutions to the problem. In this paper, we link answer set programming with another widely applied paradigm, viz. mixed integer programming. As a theoretical result, we establish translations from non-disjunctive logic programs to linear constraints used in mixed integer programming so that the solutions to the constraints correspond to the answer sets of the programs. These translations create the basis for an extended answer set programming language that includes linear constraints as a primitive and enables more compact encodings of problems. On a practical level, we have implemented a prototype system that computes answer sets using a state-of-the-art mixed integer programming solver. The reported experiments demonstrate the effectiveness of this approach applied to a number of optimization problems and problems with variables ranging over large domains.