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Article Dans Une Revue Transportation research. Part C, Emerging technologies Année : 2022

A new multi-commodity flow model to optimize the robustness of the Gate Allocation Problem

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Résumé

The Gate Allocation Problem (GAP) is one of the numerous operational problems that all busy airports have to handle and to optimize every day. In this article, we focus on two important objectives for the GAP: the robustness and the taxiing times. We first analyze a basic model which optimizes the robustness of the solution to the GAP and propose a more realistic and compact Multi-commodity Flow Problem model (MFP) to optimize both the robustness and the taxiing times. Based on tests with real data at Paris-Charles-de-Gaulle airport, this new efficient MFP model outperforms the basic one by orders of magnitude.
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Dates et versions

hal-03632887 , version 1 (06-04-2022)

Identifiants

Citer

Ruixin Wang, Cyril Allignol, Nicolas Barnier, Alexandre Gondran, Jean-Baptiste Gotteland, et al.. A new multi-commodity flow model to optimize the robustness of the Gate Allocation Problem. Transportation research. Part C, Emerging technologies, 2022, 136, pp.103491. ⟨10.1016/j.trc.2021.103491⟩. ⟨hal-03632887⟩
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