English

Pareto optimality in multilayer network growth

Physics and Society 2018-09-26 v2 Disordered Systems and Neural Networks Statistical Mechanics Optimization and Control Adaptation and Self-Organizing Systems

Abstract

We model the formation of multi-layer transportation networks as a multi-objective optimization process, where service providers compete for passengers, and the creation of routes is determined by a multi-objective cost function encoding a trade-off between efficiency and competition. The resulting model reproduces well real-world systems as diverse as airplane, train and bus networks, thus suggesting that such systems are indeed compatible with the proposed local optimization mechanisms. In the specific case of airline transportation systems, we show that the networks of routes operated by each company are placed very close to the theoretical Pareto front in the efficiency-competition plane, and that most of the largest carriers of a continent belong to the corresponding Pareto front. Our results shed light on the fundamental role played by multi-objective optimization principles in shaping the structure of large-scale multilayer transportation systems, and provide novel insights to service providers on the strategies for the smart selection of novel routes.

Keywords

Cite

@article{arxiv.1710.01068,
  title  = {Pareto optimality in multilayer network growth},
  author = {Andrea Santoro and Vito Latora and Giuseppe Nicosia and Vincenzo Nicosia},
  journal= {arXiv preprint arXiv:1710.01068},
  year   = {2018}
}

Comments

6 pages, 4 figures, Supplemental Material

R2 v1 2026-06-22T22:02:08.109Z