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Improved Approximation Algorithms by Generalizing the Primal-Dual Method Beyond Uncrossable Functions

Authors Ishan Bansal, Joseph Cheriyan, Logan Grout, Sharat Ibrahimpur

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Author Details

Ishan Bansal
  • Operations Research and Information Engineering, Cornell University, Ithaca, NY, USA
Joseph Cheriyan
  • Department of Combinatorics and Optimization, University of Waterloo, Canada
Logan Grout
  • Operations Research and Information Engineering, Cornell University, Ithaca, NY, USA
Sharat Ibrahimpur
  • Department of Mathematics, London School of Economics and Political Science, UK

Funding

  • Bansal, Ishan: Partially supported by Office of Naval Research (ONR) Grant N00014-21-1-2575.
  • Cheriyan, Joseph: Supported in part by NSERC, RGPIN-2019-04197.
  • Ibrahimpur, Sharat: Received funding from the following sources: NSERC grant 327620-09 and an NSERC DAS Award, European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. ScaleOpt–757481), and Dutch Research Council NWO Vidi Grant 016.Vidi.189.087.

Acknowledgements

We thank the anonymous reviewers and the ICALP PC for their comments. We are grateful to Cedric Koh and Madison Van Dyk for reading a preliminary version, and for their detailed comments and feedback.

Cite AsGet BibTex

Ishan Bansal, Joseph Cheriyan, Logan Grout, and Sharat Ibrahimpur. Improved Approximation Algorithms by Generalizing the Primal-Dual Method Beyond Uncrossable Functions. In 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 261, pp. 15:1-15:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.ICALP.2023.15

Abstract

We address long-standing open questions raised by Williamson, Goemans, Vazirani and Mihail pertaining to the design of approximation algorithms for problems in network design via the primal-dual method (Combinatorica 15(3):435-454, 1995). Williamson et al. prove an approximation ratio of two for connectivity augmentation problems where the connectivity requirements can be specified by uncrossable functions. They state: "Extending our algorithm to handle non-uncrossable functions remains a challenging open problem. The key feature of uncrossable functions is that there exists an optimal dual solution which is laminar... A larger open issue is to explore further the power of the primal-dual approach for obtaining approximation algorithms for other combinatorial optimization problems." Our main result proves a 16-approximation ratio via the primal-dual method for a class of functions that generalizes the notion of an uncrossable function. There exist instances that can be handled by our methods where none of the optimal dual solutions have a laminar support. We present applications of our main result to three network-design problems. 1) A 16-approximation algorithm for augmenting the family of small cuts of a graph G. The previous best approximation ratio was O(log |V(G)|). 2) A 16⋅⌈k/u_min⌉-approximation algorithm for the Cap-k-ECSS problem which is as follows: Given an undirected graph G = (V,E) with edge costs c ∈ ℚ_{≥0}^E and edge capacities u ∈ ℤ_{≥0}^E, find a minimum cost subset of the edges F ⊆ E such that the capacity across any cut in (V,F) is at least k; u_min (respectively, u_max) denote the minimum (respectively, maximum) capacity of an edge in E, and w.l.o.g. u_max ≤ k. The previous best approximation ratio was min(O(log|V|), k, 2u_max). 3) A 20-approximation algorithm for the model of (p,2)-Flexible Graph Connectivity. The previous best approximation ratio was O(log|V(G)|), where G denotes the input graph.

Subject Classification

ACM Subject Classification
  • Theory of computation → Approximation algorithms analysis
Keywords
  • Approximation algorithms
  • Edge-connectivity of graphs
  • f-Connectivity problem
  • Flexible Graph Connectivity
  • Minimum cuts
  • Network design
  • Primal-dual method
  • Small cuts

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