Airline Network Revenue Management by Multistage Stochastic Programming

Abstract

A multistage stochastic programming approach to airline network revenue management is presented. The objective is to determine seatprotection levels for all itineraries, fare classes, point of sales of the airlinenetwork and all data collection points of the booking horizon such that theexpected revenue is maximized. While the passenger demand and cance-lation rate processes are the stochastic inputs of the model, the stochasticprotection level process represents its output and allows to control the booking process. The stochastic passenger demand and cancelation rate processesare approximated by a finite number of tree structured scenarios. The scenario tree is generated from historical data using a stability-based recursivescenario reduction scheme. Numerical results for a small hub-and-spoke network are reported.