A Comparison of Approaches for Solving Hard Graph-Theoretic Problems
Abstract
In order to formulate mathematical conjectures likely to be true, a number of base cases must be determined. However, many combinatorial problems are NP-hard and the computational complexity makes this research approach difficult using a standard brute force approach on a typical computer. One sample problem explored is that of finding a minimum identifying code. To work around the computational issues, a variety of methods are explored and consist of a parallel computing approach using Matlab, a quantum annealing approach using the D-Wave computer, and lastly using satisfiability modulo theory (SMT) and corresponding SMT solvers. Each of these methods requires the problem to be formulated in a unique manner. In this paper, we address the challenges of computing solutions to this NP-hard problem with respect to each of these methods.
Cite
@article{arxiv.1504.08011,
title = {A Comparison of Approaches for Solving Hard Graph-Theoretic Problems},
author = {Victoria Horan and Steve Adachi and Stanley Bak},
journal= {arXiv preprint arXiv:1504.08011},
year = {2015}
}
Comments
23 pages, 13 figures; revised/reformatted: same main results but includes additional references and run times