Air transportation networks develop independently based on the needs of carriers, economic and political factors, as well as their interactions. A deeper study of these networks can provide insights into the growing process and the characteristics of this multi-billion dollar industry. In this regard, reliable network-formation models are required. Generating synthetic models for airline transportation networks is a difficult and current endeavor. The subnetworks induced by airline companies lead naturally to a multilayer structure. Upon a profound analysis of the benchmark European Air Transportation Network (EATN), we propose a novel approach, called Airline Network Generation Emphasizing Layers (ANGEL), to create synthetic multilayer networks mimicking the two patterns typical in air transportation networks, i.e., hub-and-spoke and point-to-point structures. Moreover, we introduce new statistics to analyze the EATN and to validate the synthetic network model, which can be applied to study multilayer networks in general.

ANGEL: A Synthetic Model for Airline Network Generation Emphasizing Layers

Tagarelli Andrea
2020-01-01

Abstract

Air transportation networks develop independently based on the needs of carriers, economic and political factors, as well as their interactions. A deeper study of these networks can provide insights into the growing process and the characteristics of this multi-billion dollar industry. In this regard, reliable network-formation models are required. Generating synthetic models for airline transportation networks is a difficult and current endeavor. The subnetworks induced by airline companies lead naturally to a multilayer structure. Upon a profound analysis of the benchmark European Air Transportation Network (EATN), we propose a novel approach, called Airline Network Generation Emphasizing Layers (ANGEL), to create synthetic multilayer networks mimicking the two patterns typical in air transportation networks, i.e., hub-and-spoke and point-to-point structures. Moreover, we introduce new statistics to analyze the EATN and to validate the synthetic network model, which can be applied to study multilayer networks in general.
2020
air transportation systems; multiplex network analysis; synthetic multilayer network generation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/303129
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