Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Aeronautical and Aviation Engineering | en_US |
| dc.contributor.advisor | Liu, Wei (EEE) | en_US |
| dc.creator | Long, Xuanji | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/14539 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Joint optimization of airport slot allocation and gate assignment | en_US |
| dcterms.abstract | During peak operating periods, airports must coordinate flight schedules and gate usage under intertwined risks of capacity congestion, knock-on delays, and limited gate availability. This study investigates the joint optimization of airport slot allocation and gate assignment under capacity constraints with operational uncertainty (e.g., flight delays). Integrating slot allocation with gate assignment is proposed to mitigate inefficiencies from decoupled decisions and the deadweight losses arising from downstream gate conflicts. To better reflect real-world operations, we formulate gate assignment as a real-time problem in which uncertainty is progressively revealed over time. We show that jointly optimizing slots and gates enables temporal smoothing of traffic peaks and alleviates turnaround conflicts. The analysis is then extended to large-scale, realistic settings with multiple airlines and terminals. | en_US |
| dcterms.abstract | We develop two optimization schemes to realize joint slot allocation and gate assignment decisions under uncertainty. First, a two-stage stochastic integer program treats gate assignment as a rolling, real-time recourse decision that incorporates updated delay information; a Benders-based decomposition combined with a rolling horizon approach and tabu search subproblems yields tractable solutions. Second, we enhance slot allocation resilience with a two-stage robust optimization model, solved using a nested column-and-constraint generation algorithm. Using extensive historical data from Shanghai Hongqiao International Airport, we demonstrate that both schemes solve large instances efficiently and achieve significant gains in computational efficiency and operational performance. These results support the practical applicability of joint optimization of slot allocation and gate assignment in airport scheduling and operations for uncertainty-aware capacity management. | en_US |
| dcterms.extent | vii, 88 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2026 | en_US |
| dcterms.educationalLevel | M.Phil. | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.LCSH | Airports -- Management | en_US |
| dcterms.LCSH | Airlines -- Management | en_US |
| dcterms.LCSH | Airplanes -- Ground handling | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | open access | en_US |
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