“…It is worth noting that both metrics are approximations of the real values. First of all, they suppose that aircraft always minimise the total flown distance; while this is generally true, other aspects are also taken into account, like heterogeneous navigation taxes, other operational considerations, or local weather phenomena -see [72], [73], [74], [75] for examples of more complex rerouting strategies. Secondly, we do not allow for rerouting outside the existing ARN, e.g.…”
In spite of the dynamic nature of air transport, air route networks, i.e. the backbone used to organise aircraft flows, are expected to be mostly static, with small changes occasionally being introduced to improve the efficiency and resilience of the system. By leveraging a large data set of European flights comprising years 2015 to 2018, we analyse its structure and evolution from the perspective of complex networks, with the aim of firstly describing it, and secondly to confirm its static nature. Results depict a highly dynamic system, with major topological changes happening at the end of 2017. Peripheral links are usually more vulnerable, due to the lack of effective reroutings, as well as central regions; additionally, the overall resilience of the network is almost constant throughout time, in spite of an increase in traffic. We further test several hypotheses regarding the design considerations driving such evolution. Beyond specific operational insights, these results highlight the importance of taking into account the evolution of this network in the study of traffic flows.
“…It is worth noting that both metrics are approximations of the real values. First of all, they suppose that aircraft always minimise the total flown distance; while this is generally true, other aspects are also taken into account, like heterogeneous navigation taxes, other operational considerations, or local weather phenomena -see [72], [73], [74], [75] for examples of more complex rerouting strategies. Secondly, we do not allow for rerouting outside the existing ARN, e.g.…”
In spite of the dynamic nature of air transport, air route networks, i.e. the backbone used to organise aircraft flows, are expected to be mostly static, with small changes occasionally being introduced to improve the efficiency and resilience of the system. By leveraging a large data set of European flights comprising years 2015 to 2018, we analyse its structure and evolution from the perspective of complex networks, with the aim of firstly describing it, and secondly to confirm its static nature. Results depict a highly dynamic system, with major topological changes happening at the end of 2017. Peripheral links are usually more vulnerable, due to the lack of effective reroutings, as well as central regions; additionally, the overall resilience of the network is almost constant throughout time, in spite of an increase in traffic. We further test several hypotheses regarding the design considerations driving such evolution. Beyond specific operational insights, these results highlight the importance of taking into account the evolution of this network in the study of traffic flows.
“…The formulation has been then used widely in the related literature Agustín et al (2012a, b); Alonso et al (2000); Bertsimas et al (2008Bertsimas et al ( , 2011Bertsimas et al ( , 2012; Boujarif et al (2021b); Churchill et al (2009); Hamdan et al (2018);Dal Sasso et al (2018; Hamdan et al (2019Hamdan et al ( , 2020Hamdan et al ( , 2021; Vossen et al (2012). Although the binary formulation is widely used in the literature, other formulations and approaches exist, such as the graph coloring Barnier and Brisset (2004), the real-time holding and rerouting Chen et al (2020), the non-time segmented Akgunduz and Kazerooni (2018) and the shortest path with common capacity constraint Garcća-Heredia et al (2019). This paper contributes to the literature by discussing the widely used binary formulation and highlighting circumstances where this formulation will give incorrect solutions.…”
We discuss a widely used air traffic flow management formulation. We show that this formulation can lead to a solution where air delays are assigned to flights during their take-off which is prohibited in practice. Although air delay is more expensive than ground delay, the model may assign air delay to a few flights during their take-off to save more on not having as much ground delay. We present a modified formulation and verify its functionality in avoiding incorrect solutions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.