Network Revenue Management with Cancellations and No‐Shows

Customer cancellations and no‐shows have an important impact on the performance of an airline's revenue management system. In this study, we study airline network revenue management problems with customer cancellations and no‐shows, considering two types of demand models: independent‐demand and choice‐based‐demand models. In independent‐demand models, the booking request rates for different products are independent of the assortment of products offered by the airline (exogenous), whereas in choice‐based‐demand models they depend on the airline's assortment (endogenous). The stochastic problems of optimizing the booking policies for the two demand models are not tractable because of the high‐dimensional state space. Therefore, for each model, we use the corresponding deterministic, continuous‐time, and continuous‐state model, known as the fluid model. A booking policy based on the fluid solution can be implemented for the original stochastic, discrete model. This fluid policy is shown to be asymptotically optimal when the arrival rates become high and the seat capacities become large. In the independent‐demand setting, an optimal fluid solution can be computed by solving a convex optimization problem for which efficient algorithms exist, whereas for some choice‐based‐demand models, the fluid control problems are known to be intractable. We also develop mixed fluid policies for the independent‐demand setting, taking advantage of the real‐time booking state, to improve the performance over the fluid policy. In a factorial experiment of 20 small‐sized single‐leg problems, the revenue loss under one of the mixed fluid policies is demonstrated to be less than 1% of the optimal value for all problems.