Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Slot Allocation in a Multi-airport System under Flying Time Uncertainty

Domaine:

mobility

Type de record:

paper
Créateur:
LiuLiaHanWan
Éditeur:
NanAirENAANR
Éditeur:
CCSDJap
Hôte:avatar
International audience Slot allocation in a single airport aims to maximize the utilization of airport-declared capacity under operational and regulation constraints, while that in a multi-airport system (MAS) has to take airspace capacity into account. This is due to the fact that the conflict of using the limited capacity of certain departure/arrival fixes in the terminal airspace could induce unnecessary flight delays. The uncertainty of flying times between the airport and congested fixes makes it even more complicated for slot allocation in a MAS. Traffic flow may exceed capacity when the flying times of flights change. In this paper, the authors propose an uncertainty slot allocation model for a MAS (USAM). The objective of the model is to minimize the total displacement of slot requests in the MAS while considering all of the capacity constraints, as well as the uncertainty of flying time. The constraints of departure/arrival fixes are formulated as chance constraints, and then the Lyapunov theorem is applied for reformulation. The USAM is applied in the MAS of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Specifically, the impact of the uncertainty of flying times from five airports to airspace fix YIN is investigated. Results show that the total displacement would increase if the uncertainty of flying time was considered. The optimized schedule using the USAM, however, is more robust and can satisfy capacity constraints under various scenarios.

Visit

enac.hal.science

Tags

Chance ConstraintUncertainty ModelMulti-airport SystemSlot AllocationSlot Allocation Multi-airport System Uncertainty Model Chance Constraint[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Licenses

info:eu-repo/semantics/OpenAccess

Similaires

Carine-Ishimwe2025/UVUBIO-lab-time-allocation-systemWater-energy system design under uncertainty – lessons and recent advancesSMALLHOLDER FARMERS’ RESOURCE ALLOCATION DECISIONS IN A MAIZE-FARMING SYSTEM UNDER CLIMATE RISKS IN MALAWIEmergent Communication in Multi-Agent Reinforcement Learning for Flying Base StationsFlying Ad Hoc Network for Emergency Applications connected to a Fog SystemTaxi-out time prediction at Mohammed V Casablanca Airport

Carine-Ishimwe2025/UVUBIO-lab-time-allocation-system

An UVU BIO Rwanda Bioeconomy Hub comprehensive web-based laboratory scheduling platform for multipl

Water-energy system design under uncertainty – lessons and recent advances

Interdependencies between water, energy, and food systems motivate linking system simulations with d

SMALLHOLDER FARMERS’ RESOURCE ALLOCATION DECISIONS IN A MAIZE-FARMING SYSTEM UNDER CLIMATE RISKS IN MALAWI

Using household data from Lilongwe districts, along with crop phenology, agronomic management and cl

Emergent Communication in Multi-Agent Reinforcement Learning for Flying Base Stations

Flying Ad Hoc Network for Emergency Applications connected to a Fog System

International audience The main objective of this paper is to improve the efficiency

Taxi-out time prediction at Mohammed V Casablanca Airport

Airports are vital for global connectivity. However, the increasing volume of air travel has present