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Author

Tobias Mömke

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Preprint Sep 2026

A Reusable Framework for Robust Approximation Algorithms in the Interval Uncertainty Model

Robust optimization under interval uncertainty aims to compute solutions that perform well on a range of scenarios that are described by interval-constrained costs. In this paper, we revisit a framework introduced by Ganesh, Maggs and Panigrahi in 2020 to study the robust optimization of NP-hard problems under interval...

Ralf Klasing, Tobias Mömke, Émile Naquin · 0 citations
Preprint Sep 2026

A $59/33$ Cut-LP Guarantee for Matching Augmentation

The Matching Augmentation Problem (MAP) asks for a minimum-cardinality set of unit-cost edges that, together with a zero-cost matching, forms a 2-edge-connected spanning multigraph. We study the standard cut relaxation. Bamas, Drygala, and Svensson proposed a particularly simple LP-guided algorithm: compute an extreme...

Morteza Alimi, Tobias Mömke · 0 citations

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