Graph Neural Modeling of Network Flows

arXiv:2209.05208v3 Announce Type: replace
Abstract: Network flow problems, which involve distributing traffic such that the underlying infrastructure is used effectively, are ubiquitous in transportation and logistics. Among them, the general Multi-Commodity Network Flow (MCNF) problem concerns the distribution of multiple flows of different sizes between several sources and sinks, while achieving effective utilization of the links. Due to the appeal of data-driven optimization, these problems have increasingly been approached using graph learning methods. In this paper, we propose a novel …

abstract arxiv concerns cs.ai cs.lg cs.ni distribution flow general graph infrastructure logistics modeling multiple network them traffic transportation type