Width Helps and Hinders Splitting Flows
Manuel C\'aceres, Massimo Cairo, Andreas Grigorjew, Shahbaz Khan,, Brendan Mumey, Romeo Rizzi, Alexandru I. Tomescu, Lucia Williams

TL;DR
This paper explores how graph width influences the complexity and approximation of minimum flow decomposition problems, introduces new classes of graphs, and extends the problem to circulations with negative weights, providing new algorithms and disproving existing conjectures.
Contribution
It characterizes width-stable graphs for non-negative flows, improves approximation ratios, introduces the Minimum Cost Circulation Decomposition, and generalizes flow decomposition to negative weights with new algorithms.
Findings
Width-stable graphs enable better approximation guarantees.
Improved worst-case approximation ratio from () to ()/a0loga0m for sparse graphs.
Disproved a conjecture on the linear independence of minimum flow decompositions.
Abstract
Minimum flow decomposition (MFD) is the NP-hard problem of finding a smallest decomposition of a network flow/circulation on a directed graph into weighted source-to-sink paths whose superposition equals . We show that, for acyclic graphs, considering the \emph{width} of the graph (the minimum number of paths needed to cover all of its edges) yields advances in our understanding of its approximability. For the version of the problem that uses only non-negative weights, we identify and characterise a new class of \emph{width-stable} graphs, for which a popular heuristic is a \gwsimple-approximation ( being the total flow of ), and strengthen its worst-case approximation ratio from to for sparse graphs, where is the number of edges in the graph. We also study a new problem on graphs with cycles, Minimum Cost Circulation…
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