A Braess’s Paradox inspired method for enhancing the robustness of air traffic networks

Air traffic networks (ATNs) play an important role in air transport. It is of practical application values to improve the robustness of ATNs. Here we propose a counter-intuitive idea with the inspiration comes from the Braess’s Paradox phenomenon. To be specific, we propose to delete edges from an A...

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Main Authors: Cai, Qing, Alam, Sameer, Ang, Haojie, Duong, Vu
Other Authors: School of Mechanical and Aerospace Engineering
Format: Conference or Workshop Item
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/145863
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1458632021-01-16T20:10:20Z A Braess’s Paradox inspired method for enhancing the robustness of air traffic networks Cai, Qing Alam, Sameer Ang, Haojie Duong, Vu School of Mechanical and Aerospace Engineering 2020 IEEE Symposium Series on Computational Intelligence Air Traffic Management Research Institute Engineering::Aeronautical engineering Air Traffic Management Robustness Air traffic networks (ATNs) play an important role in air transport. It is of practical application values to improve the robustness of ATNs. Here we propose a counter-intuitive idea with the inspiration comes from the Braess’s Paradox phenomenon. To be specific, we propose to delete edges from an ATN to improve its corresponding robustness. To achieve this goal, we formulate a bi-objective optimization problem which aims to maximize the robustness of the focal ATN as well as to minimize the number of edges to be removed. In order to address the developed optimization model, we introduce the nondominated sorting genetic algorithm (NSGA-II) and modify its algorithm operators to make it fit for the established model. To check if the research idea proposed works or not, we conduct experiments on nine real-world ATNs. In the experiments, NSGAII has been compared against its successor–NSGA-III, and another state-of-the-art optimization algorithm named MODPSO. Experiments indicate that NSGA-II performs better than the rest two algorithms on the tested ATNs. For the tested ATNs, three networks have their robustness improved by 100% by removing less than six edges while the remaining six get an improvement of around 10%. This work provides aviation decision makers with a new perspective on ATNs design and management. Accepted version This research is partially supported by NTU-CAAS Research Grant M4062429.052 by ATM Research Institute, School of MAE, NTU, Singapore. 2021-01-13T01:06:50Z 2021-01-13T01:06:50Z 2020 Conference Paper Cai, Q., Alam, S., Ang, H., & Duong, V. (2020). A Braess’s Paradox inspired method for enhancing the robustness of air traffic networks. Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence. doi:10.1109/SSCI47803.2020.9308452 978-1-7281-2547-3 https://hdl.handle.net/10356/145863 10.1109/SSCI47803.2020.9308452 en © 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 in other works. The published version is available at: https://doi.org/10.1109/SSCI47803.2020.9308452 application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Aeronautical engineering
Air Traffic Management
Robustness
spellingShingle Engineering::Aeronautical engineering
Air Traffic Management
Robustness
Cai, Qing
Alam, Sameer
Ang, Haojie
Duong, Vu
A Braess’s Paradox inspired method for enhancing the robustness of air traffic networks
description Air traffic networks (ATNs) play an important role in air transport. It is of practical application values to improve the robustness of ATNs. Here we propose a counter-intuitive idea with the inspiration comes from the Braess’s Paradox phenomenon. To be specific, we propose to delete edges from an ATN to improve its corresponding robustness. To achieve this goal, we formulate a bi-objective optimization problem which aims to maximize the robustness of the focal ATN as well as to minimize the number of edges to be removed. In order to address the developed optimization model, we introduce the nondominated sorting genetic algorithm (NSGA-II) and modify its algorithm operators to make it fit for the established model. To check if the research idea proposed works or not, we conduct experiments on nine real-world ATNs. In the experiments, NSGAII has been compared against its successor–NSGA-III, and another state-of-the-art optimization algorithm named MODPSO. Experiments indicate that NSGA-II performs better than the rest two algorithms on the tested ATNs. For the tested ATNs, three networks have their robustness improved by 100% by removing less than six edges while the remaining six get an improvement of around 10%. This work provides aviation decision makers with a new perspective on ATNs design and management.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Cai, Qing
Alam, Sameer
Ang, Haojie
Duong, Vu
format Conference or Workshop Item
author Cai, Qing
Alam, Sameer
Ang, Haojie
Duong, Vu
author_sort Cai, Qing
title A Braess’s Paradox inspired method for enhancing the robustness of air traffic networks
title_short A Braess’s Paradox inspired method for enhancing the robustness of air traffic networks
title_full A Braess’s Paradox inspired method for enhancing the robustness of air traffic networks
title_fullStr A Braess’s Paradox inspired method for enhancing the robustness of air traffic networks
title_full_unstemmed A Braess’s Paradox inspired method for enhancing the robustness of air traffic networks
title_sort braess’s paradox inspired method for enhancing the robustness of air traffic networks
publishDate 2021
url https://hdl.handle.net/10356/145863
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