Hypergraph Connectivity Augmentation in Strongly Polynomial Time
<|reference_start|>Hypergraph Connectivity Augmentation in Strongly Polynomial Time: We consider hypergraph network design problems where the goal is to construct a hypergraph that satisfies certain connectivity requirements. For graph network design problems where the goal is to construct a graph that satisfies certain connectivity requirements, the number of edges in every feasible solution is at most quadratic in the number of vertices. In contrast, for hypergraph network design problems, we might have feasible solutions in which the number of hyperedges is exponential in the number of vertices. This presents an additional technical challenge in hypergraph network design problems compared to graph network design problems: in order to solve the problem in polynomial time, we first need to show that there exists a feasible solution in which the number of hyperedges is polynomial in the input size.   The central theme of this work is to show that certain hypergraph network design problems admit solutions in which the number of hyperedges is polynomial in the number of vertices and moreover, can be solved in strongly polynomial time. Our work improves on the previous fastest pseudo-polynomial run-time for these problems. In addition, we develop strongly polynomial time algorithms that return near-uniform hypergraphs as solutions (i.e., every pair of hyperedges differ in size by at most one). As applications of our results, we derive the first strongly polynomial time algorithms for (i) degree-specified hypergraph connectivity augmentation using hyperedges, (ii) degree-specified hypergraph node-to-area connectivity augmentation using hyperedges, and (iii) degree-constrained mixed-hypergraph connectivity augmentation using hyperedges.<|reference_end|>
@article{bérczi2024hypergraph,
    title={Hypergraph Connectivity Augmentation in Strongly Polynomial Time},
    author={Krist'of B'erczi, Karthekeyan Chandrasekaran, Tam'as Kir'aly,
  Shubhang Kulkarni},
    journal={arXiv preprint arXiv:2402.10861},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.10861},
    primaryClass={cs.DS cs.DM}
}