707 research outputs found
Graph Symmetry Detection and Canonical Labeling: Differences and Synergies
Symmetries of combinatorial objects are known to complicate search
algorithms, but such obstacles can often be removed by detecting symmetries
early and discarding symmetric subproblems. Canonical labeling of combinatorial
objects facilitates easy equivalence checking through quick matching. All
existing canonical labeling software also finds symmetries, but the fastest
symmetry-finding software does not perform canonical labeling. In this work, we
contrast the two problems and dissect typical algorithms to identify their
similarities and differences. We then develop a novel approach to canonical
labeling where symmetries are found first and then used to speed up the
canonical labeling algorithms. Empirical results show that this approach
outperforms state-of-the-art canonical labelers.Comment: 15 pages, 10 figures, 1 table, Turing-10
Symmetry in Finite Combinatorial Objects: Scalable Methods and Applications.
Symmetries of combinatorial objects are known to complicate search algorithms, but such obstacles can often be removed by detecting symmetries early and discarding symmetric subproblems. Canonical labeling of combinatorial objects facilitates easy equivalence checking through quick matching. All existing canonical-labeling software also finds symmetries, but the fastest symmetry-finding software does not perform canonical labeling. In this thesis, we describe highly scalable symmetry-detection algorithms for two widely-used combinatorial objects: graphs and Boolean functions. Our algorithms are based on a decision tree that combines elements of group-theoretic computation with branching and backtracking search. Moreover, we contrast the search for graph symmetries and a canonical labeling to dissect typical algorithms and identify their similarities and differences. We develop a novel approach to graph canonical labeling where symmetries are found first and then used to speed up the canonical-labeling routines. Empirical results are given for graphs with millions of vertices and Boolean functions with hundreds of I/Os, where our algorithms can often find all symmetry group generators or a canonical labeling in seconds.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/100003/1/hadik_1.pd
Solving the Canonical Representation and Star System Problems for Proper Circular-Arc Graphs in Log-Space
We present a logspace algorithm that constructs a canonical intersection
model for a given proper circular-arc graph, where `canonical' means that
models of isomorphic graphs are equal. This implies that the recognition and
the isomorphism problems for this class of graphs are solvable in logspace. For
a broader class of concave-round graphs, that still possess (not necessarily
proper) circular-arc models, we show that those can also be constructed
canonically in logspace. As a building block for these results, we show how to
compute canonical models of circular-arc hypergraphs in logspace, which are
also known as matrices with the circular-ones property. Finally, we consider
the search version of the Star System Problem that consists in reconstructing a
graph from its closed neighborhood hypergraph. We solve it in logspace for the
classes of proper circular-arc, concave-round, and co-convex graphs.Comment: 19 pages, 3 figures, major revisio
An adaptive prefix-assignment technique for symmetry reduction
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)
parallelizability---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
practical applicability of our technique, we have prepared an experimental
open-source implementation of the technique and carry out a set of experiments
that demonstrate ability to reduce symmetry on hard instances. Furthermore, we
demonstrate that the implementation effectively parallelizes to compute
clusters with multiple nodes via a message-passing interface.Comment: Updated manuscript submitted for revie
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