Tractable Open Loop Policies for Joint Overbooking and Capacity Control Over a Single Flight Leg with Multiple Fare Classes

In this paper, we consider the joint overbooking and capacity control problem over a single flight leg with multiple fare classes. The objective is to maximize the net expected revenue, which is given by the difference between the expected revenue from the accepted requests and the expected penalty...

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Bibliographic Details
Published in:Transportation science 2012-11, Vol.46 (4), p.460-481
Main Authors: Topaloglu, Huseyin, Birbil, S. Ilker, Frenk, J. B. G., Noyan, Nilay
Format: Article
Language:English
Subjects:
Academic progress rate
Air transportation and traffic
Airlines
Applied sciences
Approximation
Computational methods
Control loops
Decision
Departure time
Determinism
Economic performance
Exact sciences and technology
Experiments
Ground, air and sea transportation, marine construction
Management
Optimal solutions
Overbooking
Overbooking (Travel reservations)
Probability
Public revenue
Random variables
Revenue
Revenue management
Services
single leg
Studies
Transportation
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Summary:In this paper, we consider the joint overbooking and capacity control problem over a single flight leg with multiple fare classes. The objective is to maximize the net expected revenue, which is given by the difference between the expected revenue from the accepted requests and the expected penalty cost from the denied reservations. We study a class of open loop policies that accept the requests for each fare class with a fixed acceptance probability. In this case, the challenge becomes finding a set of acceptance probabilities that maximize the net expected revenue. We derive a simple expression that can be used to compute the optimal acceptance probabilities, despite the problem of finding the optimal acceptance probabilities being a high dimensional optimization problem. We show that the optimal acceptance probabilities randomize the acceptance decisions for at most one fare class, indicating that the randomized nature of our open loop policies is not a huge practical concern. We bound the performance loss of our open loop policies when compared with the optimal policy. Computational experiments demonstrate that open loop policies perform remarkably well, providing net expected revenues within two percent of the optimal on average.
ISSN:0041-1655
1526-5447
DOI:10.1287/trsc.1110.0403