1514. Integrated Airline Fleet and Crew Recovery through Local Search
Invited abstract in session TC-57: Air transportation I, stream Transportation.
Tuesday, 12:30-14:00Room: Liberty 1.12
Authors (first author is the speaker)
| 1. | Philip de Bruin
|
| Information and Computing Sciences, Utrecht University | |
| 2. | Marjan van den Akker
|
| Information and Computing Sciences, Utrecht University | |
| 3. | Kunal Kumar
|
| KLM Royal Dutch Airlines | |
| 4. | Lisanne Heuseveldt
|
| Information and Computing Sciences, Utrecht University | |
| 5. | Marc Paelinck
|
| KLM Royal Dutch Airlines |
Abstract
Airline operations are prone to delays and disruptions, since the schedules are generally tight and depend on a lot of resources. When disruptions occur, the flight schedule needs to be adjusted for the operation to continue. This needs to be done as close to real-time as possible, posing a challenge with respect to computation time. Moreover, to limit the impact of disruptions, we need a solution with minimal cost and passenger impact. Airline operations include many interlinked decisions, making the use of sequential methods suboptimal. For this reason, we study an integrated approach, specifically looking at the aircraft and crew schedules. Resolving these disruptions in an integrated way is a complex problem.
To solve this, we developed a fast simulated annealing approach. Our approach is compared with traditional approaches, and an experimental study is done to evaluate different neighbour generation methods, and to investigate different recovery scenarios and strategies. We use real world data from KLM Royal Dutch Airlines. We show that our approach resolves disruptions quickly and in a cost-efficient manner, and that it outperforms traditional approaches. Compared to naive delay propagation, our method saves 40% in non-performance costs. Moreover, while most airlines use tools that consider resources separately, our approach shows that integrated disruption management is possible within 30 seconds.
Keywords
- Airline Applications
- Metaheuristics
Status: accepted
Back to the list of papers