Robust airline schedule design in a dynamic scheduling environment
Name
Jiang H and Barnhart C Robust Airline Schedule Design In A Dynamic Scheduling Environment.pdf
Size
121.27 KB
Format
Adobe PDF
Checksum (MD5)
0451653a163917ef0c2a05cbfc7942a7
Author(s)
Jiang, Hai
Barnhart, Cynthia
Alternative Title
Robust airline schedule design in a dynamic scheduling environment
Date Issued
July 2011
Journal
Computers and Operations Research
Publisher
Elsevier
Citation
Jiang, Hai and Barnhart, Cynthia“Robust Airline Schedule Design in a Dynamic Scheduling Environment.” Computers & Operations Research 40, no. 3 (March 2013): 831–840. © 2011 Elsevier Ltd.
Version
Original manuscript
Abstract
In the past decade, major airlines in the US have moved from banked hub-and-spoke operations to de-banked hub-and-spoke operations in order to lower operating costs. In Jiang and Barnhart (2009), it is shown that dynamic airline scheduling, an approach that makes minor adjustments to flight schedules in the booking period by re-fleeting and re-timing flight legs, can significantly improve utilization of capacity and hence increase profit. In this paper, we develop robust schedule design models and algorithms to generate schedules that facilitate the application of dynamic scheduling in de-banked hub-and-spoke operations. Such schedule design approaches are robust in the sense that the schedules produced can more easily be manipulated in response to demand variability when embedded in a dynamic scheduling environment. In our robust schedule design model, we maximize the number of potentially connecting itineraries weighted by their respective revenues. We provide two equivalent formulations of the robust schedule design model and develop a decomposition-based solution approach involving a variable reduction technique and a variant of column generation. We demonstrate, through experiments using data from a major U.S. airline that the schedule generated can improve profitability when dynamic scheduling is applied. It is also observed that the greater the demand variability, the more profit our robust schedules achieve when compared to existing ones.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.cor.2011.06.018
