Cost-driven weighted networks evolution

TL;DR

This paper introduces a cost-driven model for weighted network evolution, inspired by airline networks, incorporating economic principles to explain diverse network properties and behaviors.

Contribution

It presents a novel model integrating cost functions based on economies and diseconomies of scale, capturing key features of real airline networks.

Findings

Reproduces degree distributions observed in airline networks

Explains nonlinear strength-degree correlations

Accounts for hierarchical and disassortative/assortative structures

Abstract

Inspired by studies on airline networks we propose a general model for weighted networks in which topological growth and weight dynamics are both determined by cost adversarial mechanism. Since transportation networks are designed and operated with objectives to reduce cost, the theory of cost in micro-economics plays a critical role in the evolution. We assume vertices and edges are given cost functions according to economics of scale and diseconomics of scale (congestion effect). With different cost functions the model produces broad distribution of networks. The model reproduces key properties of real airline networks: truncated degree distributions, nonlinear strength degree correlations, hierarchy structures, and particulary the disassortative and assortative behavior observed in different airline networks. The result suggests that the interplay between economics of scale and diseconomics of scale is a key ingredient in order to understand the underlying driving factor of the real-world weighted networks.