A new approach to O&D revenue management based on scenario trees

Andris Moïler is a research fellow at the Institute of Mathematics of the Humboldt-University Berlin. Before that, he was a research fellow at the Weierstrass Institute for Applied Analysis and Stochastics in Berlin and the Humboldt-University Berlin. His research interests include unit commitment in power production planning, optimal control of destillation processes with probabilistic constraints and airline revenue management. His web address is interests include the theory and solution methods for large-scale mixed-integer stochastic programming problems, and he is actively working on several industrial applications. research interests include revenue management, decision support systems, fuzzy and stochastic optimisation, and agent technology. His web address is ABSTRACT KEYWORDS: O&D revenue management, seat inventory control, multistage stochas-tic programming, scenario tree generation Origin and destination (O&D) revenue management (RM), either leg-based or PNR based, has become a standard in the airline industry. This paper presents a new approach to O&D RM which does not make any assumptions on demand distributions or on the correlations of the booking process. Protection levels are determined for all origin–destination itineraries, fare classes, points of sale and data collection points (DCPs), and for a variety of demand patterns over the complete booking period. This approach to the seat inventory problem is modelled as a multistage stochastic program, where its stages correspond to the DCPs of the booking horizon. The stochastic passenger demand process is approximated by a scenario tree generated from historical data by a recursive scenario reduction procedure. The stochastic program represents a specially structured large scale linear program (LP) that may be solved by standard LP software (eg CPLEX). Preliminary numerical experience is reported. INTRODUCTION Revenue management (RM) refers to strategies for controlling the sale of (perishable) products or services in order to maximise revenue. It started in the early 1970s with the work of Littlewood (1972) and was enforced after the deregulation of became most popular for single-leg problems. They are commonly used under the assumption that demand for each fare class is independent and normally distributed. Extension for different types of distributions or depen-, the first network formulation of the RM was given. Optimal booking limits were applied to the network problem by Curry (1990). Smith and Penn (1988) and Simpson (1989) proposed the bid price concept for network revenue management. An extensive study of bid prices in comparison with other methodol-ogies was done by Williamson (1992). Theoretical properties of bid-price controls were provided by …