Single-leg airline revenue management with overbooking

Airline revenue management is about identifying the maximum revenue seat allocation policies. Since a major loss in revenue results from cancellations and no-show passengers, over the years overbooking has received a significant attention in the literature. In this study, we propose new models for static and dynamic single-leg overbooking problems. In the static case, we introduce computationally tractable models that give upper and lower bounds for the optimal expected revenue. In the dynamic case, we propose a new dynamic programming model, which is based on two streams of arrivals. The first stream corresponds to the booking requests and the second stream represents the cancellations. We also conduct simulation experiments to illustrate the proposed models and the solution methods

New models for single leg airline revenue management with overbooking, no-shows, and cancellations

Airline revenue management (ARM) problem focuses on finding a seat allocation policy, which results in the maximum profit. Overbooking has been receiving significant attention in ARM over the years, since a major loss in revenue results from cancellations and no-shows. Basically, overbooking problem aims at maximizing the profit by minimizing the number of vacant seats. However, this problem is difficult to handle due to the demand and cancellation uncertainties and the size of the problem. In this study, we propose new models for the static and the dynamic overbooking problems. Due to the complex analytical form of the overbooking problem, in the static case we introduce models that give upper and lower bounds on the optimal expected profit. In the dynamic case, however, we propose a new dynamic programming model, which is based on two streams of arrivals; one for booking and the other one is for cancellation. This approach allows us to come up with a computationally tractable model. We also present numerical results to show the effectiveness of our models