Fully Dynamic Electrical Flows: Sparse Maxflow Faster Than Goldberg-Rao

TL;DR

This paper introduces a faster algorithm for exact maximum flow computation in graphs, improving upon previous bounds by dynamically maintaining electrical flows using novel data structures.

Contribution

It presents the first sub-0 time bound for maximum flow in sparse graphs with integer capacities, leveraging dynamic electrical flow maintenance.

Findings

Achieves rac{3}{2} -
7328} time complexity for maximum flow

Introduces data structures for dynamic electrical flow maintenance

Improves upon Goldberg-Rao algorithm for sparse graphs

Abstract

We give an algorithm for computing exact maximum flows on graphs with $m$ edges and integer capacities in the range $[1, U]$ in $\widetilde{O}(m^{\frac{3}{2} - \frac{1}{328}} \log U)$ time. For sparse graphs with polynomially bounded integer capacities, this is the first improvement over the $\widetilde{O}(m^{1.5} \log U)$ time bound from [Goldberg-Rao JACM `98]. Our algorithm revolves around dynamically maintaining the augmenting electrical flows at the core of the interior point method based algorithm from [M\k{a}dry JACM `16]. This entails designing data structures that, in limited settings, return edges with large electric energy in a graph undergoing resistance updates.