Abstract 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.
Highlights New Multi-commodity Flow model optimally solves large-scale Gate Allocation Problem. Schedule robustness and taxiing optimized to improve airport operations. Outperforms former model by orders of magnitude on real data at major airport. Fast enough to enable real-time applications.
A new multi-commodity flow model to optimize the robustness of the Gate Allocation Problem
2021-11-22
Article (Journal)
Electronic Resource
English