Stability and dynamical properties of material flow systems on random networks

TL;DR

This paper investigates the stability and dynamics of material flow networks on various random graph models, revealing how network structure and control policies influence system stability using random matrix theory.

Contribution

It provides a comprehensive phase diagram for stability in random graph-based flow networks and analyzes the effects of different topologies and control strategies.

Findings

Variability in input-output matrices reduces stability.

Random network structures tend to decrease stability.

Fast price dynamics and strong responsiveness enhance stability.

Abstract

The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are characteristic of flow networks in economic, ecological and biological systems. Based on results from random matrix theory, we work out the phase diagram of such systems defined on extensively connected random graphs, and study in detail how the choice of control policies and the network structure affects stability. We also present results for more complex topologies of the underlying graph, focussing on finitely connected Erd\"os-R\'eyni graphs, Small-World Networks and Barab\'asi-Albert scale-free networks. Results indicate that variability of input-output matrix elements, and random structures of the underlying graph tend to make the system less stable, while fast price dynamics or strong responsiveness to stock accumulation promote stability.