A Braess’s Paradox Inspired Method for Enhancing the Robustness of Air Traffic Networks

Abstract

Air traffic is operated in an air traffic network (ATN) environment. It is of great significance to improve the robustness of ATNs as they are frequently exposed to manifold uncertainties which can break down the functioning components of an ATN. Existing studies on improving the robustness of ATNs either rewire the links of a network or add more links to the network. In this paper we suggest a Braess's Paradox inspired method. Specifically, we propose to improve the robustness of an ATN by removing some of its edges. In order to determine the edges whose removal can improve the robustness of a given ATN, we develop a bi-objective optimization model with one objective maximizing the network's robustness and the other one minimizing the number of links to be removed. We further apply and modify a non-dominated sorting genetic algorithm (NSGA-II) to optimize the developed model. In order to validate the effectiveness of the proposed idea, we carry out experiments on nine real-world ATNs. We also compare the modified NSGA-II algorithm against NSGA-III, and MODPSO, which are famous and efficient multiobjective evolutionary algorithms. Experiments indicate that NSGA-II outperforms the compared algorithms and that the robustness of an ATN indeed can be improved by just removing a small amount of its edges. 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 a new perspective for aviation decision makers to better design and manage ATNs.

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