Abstract flows over time: A first step towards solving dynamic packing problems

TL;DR

This paper extends the concept of flows over time to abstract systems, demonstrating that maximum flows can be efficiently computed and capturing key properties of classical network flows within this generalized framework.

Contribution

It introduces a novel model of abstract flows over time and proves that maximum flows can be obtained via weighted abstract flow solutions, generalizing classical network flow results.

Findings

Maximum abstract flow over time can be computed using weighted abstract flow solutions.

The switching property of abstract networks captures essential properties of classical networks.

The model generalizes classical network flow concepts to abstract systems.

Abstract

Flows over time generalize classical network flows by introducing a notion of time. Each arc is equipped with a transit time that specifies how long flow takes to traverse it, while flow rates may vary over time within the given edge capacities. In this paper, we extend this concept of a dynamic optimization problem to the more general setting of abstract flows. In this model, the underlying network is replaced by an abstract system of linearly ordered sets, called "paths" satisfying a simple switching property: Whenever two paths P and Q intersect, there must be another path that is contained in the beginning of P and the end of Q. We show that a maximum abstract flow over time can be obtained by solving a weighted abstract flow problem and constructing a temporally repeated flow from its solution. In the course of the proof, we also show that the relatively modest switching property of abstract networks already captures many essential properties of classical networks.