Alain Helfenstein: Forecasting OD-Path Booking Data for Airline Revenue Management using a Random Forest Approach

Adviser: Prof. Dr. Peter Bühlmann

August 2010

Abstract:

A main issue of an airline's revenue management is to calculate an accurate forecast of the future demand of bookings. Poor estimates of demand lead to inadequate inventory controls and sub-optimal revenue performance. Within this thesis we describe the structure of booking data within the airline industry that needs to be forecasted and discuss the current bayesian forecasting model implemented by Swiss Revenue Management.

We then implement new forecasting models using different random forest (regression) approaches and discuss the accuracy of the predicted demand of all models. As a further result we will illustrate how an implementation of a regression using the random forest algorithm can fail.