Node-Connectivity Terminal Backup, Separately-Capacitated Multiflow, and Discrete Convexity

Abstract

The terminal backup problems (Anshelevich and Karagiozova (2011)) form a class of network design problems: Given an undirected graph with a requirement on terminals, the goal is to find a minimum cost subgraph satisfying the connectivity requirement. The node-connectivity terminal backup problem requires a terminal to connect other terminals with a number of node-disjoint paths. This problem is not known whether is NP-hard or tractable. Fukunaga (2016) gave a $4/3$-approximation algorithm based on LP-rounding scheme using a general LP-solver. In this paper, we develop a combinatorial algorithm for the relaxed LP to find a half-integral optimal solution in $O(m\log (nUA)\cdot \mathrm{MF}(kn,m+k^{2}n))$ time, where $n$ is the number of nodes, $m$ is the number of edges, $k$ is the number of terminals, $A$ is the maximum edge-cost, $U$ is the maximum edge-capacity, and $\mathrm{MF}(n^{\prime },m^{\prime })$ is the time complexity of a max-flow algorithm in a network with $n^{\prime }$ nodes and $m^{\prime }$ edges. The algorithm implies that the $4/3$-approximation algorithm for the node-connectivity terminal backup problem is also efficiently implemented. For the design of algorithm, we explore a connection between the node-connectivity terminal backup problem and a new type of a multiflow, called a separately-capacitated multiflow. We show a min-max theorem which extends Lovász-Cherkassky theorem to the node-capacity setting. Our results build on discrete convexity in the node-connectivity terminal backup problem.

A preliminary version of this paper was appeared in the proceedings of the 47th International Colloquium on Automata, Languages and Programming (ICALP 2020)