Airline Seats Allocation Optimization Through Revenue Management

Abstract

Revenue Management has recently gained a solid recognition in Airline industry. It acts as a strategic and tactic provider to manage the uncertainty in demand for their perishable products in the most profitable manner as possible. The Airline Revenue Management tries to attain an effective seat inventory control by utilizing the forecasts of future bookings, the revenue values related with each fare class, and the booking requests by the passengers which in turn will maximize the total revenue of a flight. This paper attempts to propose a novel approach in optimizing the seat inventory control by jointly utilizing the statistical forecasting together with revenue management. The revenue value associated with each point of sale (origin) has been considered when locating seats for a future departure instead of concerning the revenue values of each fare class. Further, it describes a method to obtain optimal seat protection levels that should be reserved from a lower fare origin for a higher fare origin and the nested structure of booking limits for each fare origin so as to optimize the seat allocation in a future departure. A novel approach using Functional Principal Component Regression (FPCR) was carried out to model and forecast the future demand and revenue value for each origin, using historical bookings and revenue values. The Expected Marginal Seat Revenue (EMSR) decision model was developed to address the uncertainty associated with this forecasted future demand and to gain the nested structure of booking limits. Finally, the forecasted booking limits were updated with actual booking requests prior to the flight departure. At the point of verification, it showed a remarkably maximized total revenue over the existing method. Thus, it is suggested that the optimal seat allocation for a better seat inventory control in airlines can be achieved by jointly utilizing the proposed FPCR and EMSR methods.