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 language | English |
|---|---|
| Pages (from-to) | 4465-4468 |
| Number of pages | 4 |
| Journal | Proceedings of the VLDB Endowment |
| Volume | 17 |
| Issue number | 12 |
| DOIs | |
| State | Published - 2024 |
| Event | 50th International Conference on Very Large Data Bases, VLDB 2024 - Guangzhou, China Duration: 24 Aug 2024 → 29 Aug 2024 |
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