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Extended Aircraft Arrival Management under Uncertainty: A Computational Study

Abstract : The arrival manager operational horizon, in Europe, is foreseen to be extended up to 500 n miles around destination airports. In this context, arrivals need to be sequenced and scheduled a few hours before landing, when uncertainty is still significant. A computational study, based on a two-stage stochastic program, is presented and discussed to address the arrival sequencing and scheduling problem under uncertainty. This preliminary study focuses on a single initial approach fix and a single runway. Different problem characteristics, optimization parameters, as well as fast solution methods for real-time implementation are analyzed in order to evaluate the viability of our approach. Paris Charles-De-Gaulle airport is taken as a case study. A simulation-based validation experiment shows that the current approach can decrease the number of expected conflicts near the terminal area by up to 70%. Moreover, in a high-density traffic situation, the total time to lose inside the terminal area can be decreased by more than 71%, whereas the expected landing rate can be increased by 7.7% as compared to the first-come/first-served policy. This computational study demonstrates that sequencing and scheduling arrivals under uncertainty a few hours before landing can successfully diminish the need for holding stacks by relying more on upstream linear holding.
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Submitted on : Tuesday, May 21, 2019 - 11:44:10 AM
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Ahmed Khassiba, Fabian Bastin, Bernard Gendron, Sonia Cafieri, Marcel Mongeau. Extended Aircraft Arrival Management under Uncertainty: A Computational Study. Journal of Air Transportation, AIAA, 2019, 27 (3), pp.131-143. ⟨10.2514/1.D0135⟩. ⟨hal-02135040⟩

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