An integrated reinforced learning and network competition analysis for calibrating airline itinerary choice models with constrained demand

Ahmed Abdelghany (), Khaled Abdelghany () and Ching-Wen Huang ()
Additional contact information
Ahmed Abdelghany: Embry-Riddle Aeronautical University
Khaled Abdelghany: Southern Methodist University
Ching-Wen Huang: Embry-Riddle Aeronautical University

Journal of Revenue and Pricing Management, 2021, vol. 20, issue 3, No 3, 227-247

Abstract: Abstract This paper presents a novel methodology to develop itinerary choice models (ICM) for air travelers that addresses the limitations of the traditional utility-maximization approach. The methodology integrates a reinforcement learning algorithm and an airline network competition analysis model. The reinforcement learning algorithm searches for the values of parameters of the itinerary choice model while considering maximizing a reward function. The reward function is measured as the negative of the difference between the estimated and observed system metrics. The airline network competition analysis model is used to calculate the estimated system metrics. It is a simulation model that represents passenger-itinerary assignment. It captures the demand–supply interactions at the network level while considering the competition among all airlines. An ICM system is calibrated using the developed framework considering the global airline network, which includes more than 500,000 airport pairs. Validating the model against ground truth data shows that the developed model adequately captures the travelers’ itinerary choice behavior and replicates the competition pattern among airlines.

Keywords: Airlines; Competition; Itinerary choice; Reinforced learning; Simulation; Market shares (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1057/s41272-021-00309-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:jorapm:v:20:y:2021:i:3:d:10.1057_s41272-021-00309-y

Ordering information: This journal article can be ordered from
https://www.palgrave.com/gp/journal/41272

DOI: 10.1057/s41272-021-00309-y

Access Statistics for this article

Journal of Revenue and Pricing Management is currently edited by Ian Yeoman

More articles in Journal of Revenue and Pricing Management from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().