Pareto Optimality in Multilayer Network Growth

2017/10/31 by Andrea Santoro, Vito Latora, Giuseppe Nicosia +1 · 1 citation
Business, Management and Accounting · Economics, Econometrics and Finance · Engineering · Mathematics · Physics and Astronomy · Social Sciences · #Artificial intelligence #Aviation Industry Analysis and Trends #Business #Business Strategy and Innovation #Competition (biology) #Computer network #Computer science #Ecology #Economics #Economies of scale #Engineering #Function (biology) #Mathematical optimization #Mathematics #Microeconomics #Multi-objective optimization #Operations research #Pareto principle #Process (computing) #Routing (electronic design automation) #Selection (genetic algorithm) #Service (business) #Transportation Planning and Optimization #cond-mat.dis-nn #cond-mat.stat-mech #math.OC #nlin.AO #physics.soc-ph

paper · pdf · doi:10.1103/physrevlett.121.128302

published as Phys. Rev. Lett. 121, 128302 (2018) · 6 pages, 4 figures, Supplemental Material

arxiv created 2018/07/19 · openalex publication_date 2018/09/20 · arxiv updated 2018/09/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

We model the formation of multilayer transportation networks as a multiobjective optimization process, where service providers compete for passengers, and the creation of routes is determined by a multiobjective 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 multiobjective 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.

Citations

• Irreducibility of multilayer network dynamics: the case of the voter model
• Catastrophic cascade of failures in interdependent networks
• Emergence of network features from multiplexity
• Growing Multiplex Networks
• The structure and dynamics of multilayer networks
• Statistical mechanics of complex networks
• The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles
• Monte Carlo sampling methods using Markov chains and their applications
• The Structure and Function of Complex Networks
• The architecture of complex weighted networks
• The effects of network structure, competition and memory time on social spreading phenomena
• Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks

Cited by

• Minimal branching and fusion morphogenesis approaches biological multi-objective optimality