Seat revenue management optimization

Abstract

Revenue Management in airline industry has become essential since the introduction of low cost airlines. Established airline companies need a new strategy of operating in order to be able to compete with these low cost airlines. The aim of this work is to determine and develop an efficient dynamic programming algorithm for the revenue optimization problem together with selected heuristic algorithms. This is done by solving the Seat Inventory Control problem which is concerned about the allocation of the finite seat inventory to the demand that occurs over time before the flight is scheduled to depart, so as to maximize the total expected revenue. The model is first solved using two static solution methods. Then, a dynamic programming model is set up and two different solution methods are introduced for solving this DP model. Finally the four different methods are tested by simulating an arrival process on actual data provided by Malta's national airline, Air Malta, and results are compared together in order to obtain the most efficient algorithm.