English

Semi-Streaming Algorithms for Submodular Function Maximization Under b-Matching, Matroid, and Matchoid Constraints

Data Structures and Algorithms 2022-01-11 v3

Abstract

We consider the problem of maximizing a non-negative submodular function under the bb-matching constraint, in the semi-streaming model. When the function is linear, monotone, and non-monotone, we obtain the approximation ratios of 2+ε2+\varepsilon, 3+225.8283 + 2 \sqrt{2} \approx 5.828, and 4+237.4644 + 2 \sqrt{3} \approx 7.464, respectively. We also consider a generalized problem, where a kk-uniform hypergraph is given, along with an extra matroid or a kk'-matchoid constraint imposed on the edges, with the same goal of finding a bb-matching that maximizes a submodular function. When the extra constraint is a matroid, we obtain the approximation ratios of k+1+εk + 1 + \varepsilon, k+2k+1+2k + 2\sqrt{k+1} + 2, and k+2k+2+3k + 2\sqrt{k + 2} + 3 for linear, monotone and non-monotone submodular functions, respectively. When the extra constraint is a kk'-matchoid, we attain the approximation ratio 83k+649k+O(1)\frac{8}{3}k+ \frac{64}{9}k' + O(1) for general submodular functions.

Keywords

Cite

@article{arxiv.2107.13071,
  title  = {Semi-Streaming Algorithms for Submodular Function Maximization Under b-Matching, Matroid, and Matchoid Constraints},
  author = {Chien-Chung Huang and François Sellier},
  journal= {arXiv preprint arXiv:2107.13071},
  year   = {2022}
}
R2 v1 2026-06-24T04:34:43.232Z