AIRLINE SEAT INVENTORY CONTROL


Edgars K. Vasermanis 1, Nicholas A. Nechval 1, Konstantin N. Nechval 2
a) University of Latvia, Department of Mathematical Statistics, Raina Blvd 19, LV-1050, Riga, Latvia,
e-mail: nechval@junik.lv
b) Transport and Telecommunication Institute, Department of Computer Science, Lomonosov Street 1, LV-1019, Riga, Latvia
e-mail: konstan@tsi.lv

ABSTRACT: It is common practice for airlines to charge several different fares for a common pool of seats. This paper presents the optimization algorithms that have been used to address the problem of when to refuse booking requests for a given fare level to save the seat for a potential request at a higher fare level. Dynamic and dynamic adaptive booking policies for multiple fare classes that share the same seating pool on one leg of an airline flight, when seats are booked in a nested fashion and when lower fare classes book before higher ones, are determined. The dynamic policy of airline booking makes repetitive use of a static method over the booking period, based on the most recent demand and capacity information. It allows one to allocate seats dynamically and anticipatory over time. The dynamic adaptive policy, in addition, deals with the case when only the functional forms of the probability density functions for reservation requests for various fare classes are given. In this case actual airline demand data are used to obtain estimates of expected demand for input into the airline optimization models, where we illustrate the practical importance of invariance for eliminating nuisance (unspecified) parameters from the problem. Although the traditional use of invariance has been in a decision theoretic setting, we instead use invariance to find a transformation of the data such that the distribution of the transformed data does not involve nuisance parameters. Illustrative examples are given.

KEYWORDS: Air Transportation, Passenger Demand, Fare Classes, Airline Seat Inventory Control, Optimal Policies of Airline Booking.


Back to HMS2003 Home Page