A Robust Model for Choice-Based Capacity Control

Incorporating consumer choice behavior into the process of capacity control decision represents one of the inevitable trends in perishable product revenue management. Because the sales system cannot record the complete data of consumer arrival and exactly collect and analyze the information of consumers' preference, demand forecast is usually far from accurate. Inevitable forecast error is an important limiting factor in applying the choice-based capacity control model to industry practice. In order to systematically mitigate the sensitivity of the optimal control strategy to forecast errors, a robust capacity control model was proposed by applying the theory of Markov decision processes and robust optimization approach, which also consider the demands of overbooking. The monotone property of the robust optimal value was proved. On this basis, a robust optimal control strategy, the robust bid-price strategy, was given. Numerical example was given to illustrate that the optimal robust strategy can significantly improve the total revenue in the case of large errors of demand forecast.