Shared-Memory Branch-and-Reduce for Multiterminal Cuts
Data Structures and Algorithms
2019-08-20 v2 Distributed, Parallel, and Cluster Computing
Abstract
We introduce the fastest known exact algorithm~for~the multiterminal cut problem with k terminals. In particular, we engineer existing as well as new data reduction rules. We use the rules within a branch-and-reduce framework and to boost the performance of an ILP formulation. Our algorithms achieve improvements in running time of up to multiple orders of magnitudes over the ILP formulation without data reductions, which has been the de facto standard used by practitioners. This allows us to solve instances to optimality that are significantly larger than was previously possible.
Cite
@article{arxiv.1908.04141,
title = {Shared-Memory Branch-and-Reduce for Multiterminal Cuts},
author = {Monika Henzinger and Alexander Noe and Christian Schulz},
journal= {arXiv preprint arXiv:1908.04141},
year = {2019}
}