An Adaptive Prefix-Assignment Technique for Symmetry Reduction

Abstract

Abstract. This paper presents a technique for symmetry reduction that adaptively assigns a prefix of variables in a system of constraints so that the generated prefix-assignments are pairwise nonisomorphic under the action of the symmetry group of the system. The technique is based on McKay's canonical extension framework [J. Algorithms 26 (1998), no. 2, 306-324]. Among key features of the technique are (i) adaptability-the prefix sequence can be user-prescribed and truncated for compatibility with the group of symmetries; (ii) parallelisability-prefix-assignments can be processed in parallel independently of each other; (iii) versatility-the method is applicable whenever the group of symmetries can be concisely represented as the automorphism group of a vertex-colored graph; and (iv) implementability-the method can be implemented relying on a canonical labeling map for vertex-colored graphs as the only nontrivial subroutine. To demonstrate the tentative practical applicability of our technique we have prepared a preliminary implementation and report on a limited set of experiments that demonstrate ability to reduce symmetry on hard instances.