Shared-memory branch-and-reduce for multiterminal cuts

Henzinger MH, Noe A, Schulz C. 2020. Shared-memory branch-and-reduce for multiterminal cuts. 2020 Symposium on Algorithm Engineering and Experiments. ALENEX: Symposium on Algorithm Engineering and Experiments, 42–55.

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Author
Henzinger, MonikaISTA ; Noe, Alexander; Schulz, Christian
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.
Publishing Year
Date Published
2020-01-01
Proceedings Title
2020 Symposium on Algorithm Engineering and Experiments
Publisher
Society for Industrial and Applied Mathematics
Page
42-55
Conference
ALENEX: Symposium on Algorithm Engineering and Experiments
Conference Location
Salt Lake City, UT, United States
Conference Date
2020-01-05 – 2020-01-06
IST-REx-ID

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Henzinger MH, Noe A, Schulz C. Shared-memory branch-and-reduce for multiterminal cuts. In: 2020 Symposium on Algorithm Engineering and Experiments. Society for Industrial and Applied Mathematics; 2020:42-55. doi:10.1137/1.9781611976007.4
Henzinger, M. H., Noe, A., & Schulz, C. (2020). Shared-memory branch-and-reduce for multiterminal cuts. In 2020 Symposium on Algorithm Engineering and Experiments (pp. 42–55). Salt Lake City, UT, United States: Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611976007.4
Henzinger, Monika H, Alexander Noe, and Christian Schulz. “Shared-Memory Branch-and-Reduce for Multiterminal Cuts.” In 2020 Symposium on Algorithm Engineering and Experiments, 42–55. Society for Industrial and Applied Mathematics, 2020. https://doi.org/10.1137/1.9781611976007.4.
M. H. Henzinger, A. Noe, and C. Schulz, “Shared-memory branch-and-reduce for multiterminal cuts,” in 2020 Symposium on Algorithm Engineering and Experiments, Salt Lake City, UT, United States, 2020, pp. 42–55.
Henzinger MH, Noe A, Schulz C. 2020. Shared-memory branch-and-reduce for multiterminal cuts. 2020 Symposium on Algorithm Engineering and Experiments. ALENEX: Symposium on Algorithm Engineering and Experiments, 42–55.
Henzinger, Monika H., et al. “Shared-Memory Branch-and-Reduce for Multiterminal Cuts.” 2020 Symposium on Algorithm Engineering and Experiments, Society for Industrial and Applied Mathematics, 2020, pp. 42–55, doi:10.1137/1.9781611976007.4.
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