Improved Approximation Algorithms for Capacitated Network Design and Flexible Graph Connectivity
Ishan Bansal, Joseph Cheriyan, Sanjeev Khanna, Miles Simmons

TL;DR
This paper introduces improved approximation algorithms for Capacitated Network Design and Flexible Graph Connectivity, achieving better ratios by leveraging LP relaxations and recent algorithms for Cover Small Cuts.
Contribution
It presents new approximation algorithms with improved ratios for two network design problems using LP relaxations and advanced rounding techniques.
Findings
Achieved an $O(\log k)$-approximation for Cap-$k$-ECSS.
Designed a 7-approximation for $(1,q)$-FGC.
Linked small cut covering problems to the $(2,q)$-FGC variant.
Abstract
We present improved approximation algorithms for some problems in the related areas of Capacitated Network Design and Flexible Graph Connectivity. In the Cap--ECSS problem, we are given a graph whose edges have non-negative costs and positive integer capacities, and the goal is to find a minimum-cost edge-set such that every non-trivial cut of the graph has capacity at least . We present an -approximation algorithm for the Cap--ECSS problem, asymptotically improving upon the previous best approximation ratio of whenever , where denotes . (See section 1, for a detailed discussion.) In the -Flexible Graph Connectivity problem, denoted -FGC, the input is a graph where is partitioned into safe and unsafe edges, and the goal is to find a minimum cost set of edges…
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