Skip to main navigation Skip to search Skip to main content

Swift: A Data-Driven Flight Planning System at Scale

  • Chang Gao
  • , Tianlong Zhang
  • , Yuxiang Zeng*
  • , Yi Xu*
  • , Shuyuan Li
  • , Yuanyuan Zhang
  • *Corresponding author for this work
  • Beihang University
  • North China Institute of Computing Technology

Research output: Contribution to journalConference articlepeer-review

Abstract

Flight planning, a pivotal challenge in the airline industry, strives to achieve economic and flexible scheduling of airplanes to serve designated flight itineraries. As the demand for air transportation soars, traditional planning methods can be inefficient in managing large-scale flights. Thus, we introduce Swift, a data-driven system tailored to enhance the scalability and effectiveness of flight planning. Swift primarily employs the bipartite graph model to derive optimal and economic flight plans for airlines. Our method not only minimizes the number of required planes but also ensures a balanced workload across these planes. Furthermore, Swift offers the capability of dynamic updates to flight plans in response to unexpected incidents at airports, such as bad weather conditions. Besides, Swift incorporates other functionalities like predicting future flight demand and monitoring real-time flight trajectories. Conference participants can interact with this system and explore our flight planning solution in real-world scenarios.

Original languageEnglish
Pages (from-to)4465-4468
Number of pages4
JournalProceedings of the VLDB Endowment
Volume17
Issue number12
DOIs
StatePublished - 2024
Event50th International Conference on Very Large Data Bases, VLDB 2024 - Guangzhou, China
Duration: 24 Aug 202429 Aug 2024

Fingerprint

Dive into the research topics of 'Swift: A Data-Driven Flight Planning System at Scale'. Together they form a unique fingerprint.

Cite this