On a Partition LP Relaxation for Min-Cost 2-Node Connected Spanning Subgraphs
Logan Grout, Joseph Cheriyan, Bundit Laekhanukit
TL;DR
This paper introduces a new LP relaxation based on partition constraints for the minimum-cost 2-node connected spanning subgraph problem, providing improved approximation guarantees and a greedy algorithm for the special case 2NC-TAP.
Contribution
It proposes a novel partition LP relaxation and a greedy algorithm for 2NC-TAP, along with an analysis using dual-fitting to enhance approximation guarantees.
Findings
Developed a new partition LP relaxation for the problem.
Designed a greedy algorithm for the special case 2NC-TAP.
Analyzed the algorithm's performance using dual-fitting techniques.
Abstract
Our motivation is to improve on the best approximation guarantee known for the problem of finding a minimum-cost 2-node connected spanning subgraph of a given undirected graph with nonnegative edge costs. We present an LP (Linear Programming) relaxation based on partition constraints. The special case where the input contains a spanning tree of zero cost is called 2NC-TAP. We present a greedy algorithm for 2NC-TAP, and we analyze it via dual-fitting for our partition LP relaxation. Keywords: 2-node connected graphs, approximation algorithms, connectivity augmentation, greedy algorithm, network design, partition relaxation
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Optical Network Technologies · Interconnection Networks and Systems