Transport optimization on complex networks

TL;DR

This paper compares a heuristic algorithm for optimizing transport on complex networks, demonstrating improved traffic capacity and reduced travel times while preserving small-world properties.

Contribution

It introduces a heuristic routing algorithm that balances network load by minimizing maximum node betweenness, enhancing traffic capacity without significantly increasing path lengths.

Findings

Optimal routing increases network traffic capacity.

Routing optimization reduces average travel time under congestion.

Small-world properties are preserved with optimized routing.

Abstract

We present a comparative study of the application of a recently introduced heuristic algorithm to the optimization of transport on three major types of complex networks. The algorithm balances network traffic iteratively by minimizing the maximum node betweenness with as little path lengthening as possible. We show that by using this optimal routing, a network can sustain significantly higher traffic without jamming than in the case of shortest path routing. A formula is proved that allows quick computation of the average number of hops along the path and of the average travel times once the betweennesses of the nodes are computed. Using this formula, we show that routing optimization preserves the small-world character exhibited by networks under shortest path routing, and that it significantly reduces the average travel time on congested networks with only a negligible increase in the average travel time at low loads. Finally, we study the correlation between the weights of the links in the case of optimal routing and the betweennesses of the nodes connected by them.