Journal Article10.1287/IJOC.1090.0359
A Dynamic Programming Decomposition Method for Making Overbooking Decisions Over an Airline Network
TL;DR: A revenue management model to jointly make the capacity allocation and overbooking decisions over an airline network and uses an approximation strategy to decompose the dynamic programming formulation by the flight legs to construct separable approximations to the value functions.
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Abstract: In this paper, we develop a revenue management model to jointly make the capacity allocation and overbooking decisions over an airline network. Our approach begins with the dynamic programming formulation of the capacity allocation and overbooking problem and uses an approximation strategy to decompose the dynamic programming formulation by the flight legs. This decomposition idea opens up the possibility of obtaining approximate solutions by concentrating on one flight leg at a time, but the capacity allocation and overbooking problem that takes place over a single flight leg still turns out to be intractable. We use a state aggregation approach to obtain high-quality solutions to the single-leg problem. Overall, our model constructs separable approximations to the value functions, which can be used to make the capacity allocation and overbooking decisions for the whole airline network. Computational experiments indicate that our model performs significantly better than a variety of benchmark strategies from the literature.
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Citations
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TL;DR: This work proposes a revenue management model based on Talluri and van Ryzin (2004) that takes cancellations into account in addition to customer choice behaviour, and proposes three dynamic programming formulations to solve the problem.
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References
•Book
The Theory and Practice of Revenue Management
Kalyan T. Talluri,Garrett van Ryzin +1 more
- 17 Jun 2004
TL;DR: In this article, the authors present the economics of RM, including single-resource capacity control, network capacity control and overbooking, as well as dynamic pricing and auctioning.
A Multiproduct Dynamic Pricing Problem and Its Applications to Network Yield Management
TL;DR: The solution to the deterministic problem suggests two heuristics for the stochastic problem that are shown to be asymptotically optimal as the expected sales volume tends to infinity.
An Analysis of Bid-Price Controls for Network Revenue Management
TL;DR: In this paper, it was shown that bid-price control is not optimal in general and that when leg capacities and sales volumes are large, bid price control is asymptotically optimal, provided the right bid prices are used.
On the Choice-Based Linear Programming Model for Network Revenue Management
Qian Liu,Garrett van Ryzin +1 more
TL;DR: It is shown that, asymptotically, as demand and capacity are scaled up, only these efficient sets are used in an optimal policy in the single-leg, choice-based RM problem.
Airline Yield Management with Overbooking, Cancellations, and No-Shows
TL;DR: A Markov decision process (dynamic programming) model for airline seat allocation on a single-leg flight with multiple fare classes, which exploits the equivalence to a problem in the optimal control of admission to a queueing system, which has been well studied in the queueing-control literature.