Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/144388
Title: Enhancing the robustness of airport networks by removing links
Authors: Cai, Qing
Ang, Haojie
Alam, Sameer
Ma, Chunyao
Duong, Vu
Keywords: Engineering::Aeronautical engineering
Issue Date: 2020
Source: Cai, Q., Ang, H., Alam, S., Ma, C., & Duong, V. (2020). Enhancing the robustness of airport networks by removing links. Proceedings of the 2020 IEEE Congress on Evolutionary Computation (CEC). doi:10.1109/CEC48606.2020.9185852
Conference: 2020 IEEE Congress on Evolutionary Computation (CEC)
Abstract: Air traffic is playing a leading role in the global economical growth. Air traffic is indispensable from airport networks which accommodate the traffic demands. Note that airport networks are confronted with intractable uncertainties such as severe meteorological conditions, random mechanical failures of aircraft instruments, terrorist attacks, etc., which give rise to the failures of the components of airport networks. It is of great significance to improve the robustness of airport networks to component failures as the failures can cause staggering economical losses. Existing works either employ network rewire mechanism or add more links to an airport network to enhance the robustness of the given network. In this paper, we provide a counter-intuitive way to enhance the robustness of airport networks. Specifically, we propose to remove links from a given airport network to improve its robustness in face of perturbations. To do so, we develop a single-objective genetic algorithm to locate the links of an airport network whose removal will increase its robustness. Experimental studies on six realworld airport networks validate the feasibility of the proposed research idea. This work provides a new perspective for aviation decision makers to manage airports and air routes, and therefore sheds new light towards robust airspace design.
URI: https://hdl.handle.net/10356/144388
DOI: 10.1109/CEC48606.2020.9185852
Schools: School of Mechanical and Aerospace Engineering 
Research Centres: Air Traffic Management Research Institute 
Rights: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work is available at: https://doi.org/10.1109/CEC48606.2020.9185852
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ATMRI Conference Papers

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