On Robustness Paradox in Air Traffic Networks

Abstract

Air traffic is operated in an air traffic network (ATN) environment. It is pertinent to improve the robustness of ATNs as they are frequently exposed to manifold uncertainties which can break down their functioning components. Existing studies improve the robustness of an ATN by either rewiring its links or adding more ones. In this paper we discover the robustness paradox phenomenon in ATNs. Specifically, we claim to improve the robustness of an ATN by removing its links. In order to determine the links whose removal can improve an ATN's robustness, 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. We then carry out experiments on nine real-world ATNs to validate the effectiveness of the proposed idea. 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 robustness paradox phenomenon does exist in ATNs. This work provides a new perspective for aviation decision makers to better design and manage ATNs.