Revenue management (RM) attempts to understand and shape consumer behavior to maximize revenue from a perishable resource. Various algorithms can be used to control bid-prices, and subsequently, perform differently with respect to the total network revenue that they generate. There is currently a need for some method to compare RM engines; a simulation can fulfill this need.

The first module of this thesis will create a statistically accurate representation of customers arriving at ticket purchasing channels. Each customer's attributes are: arrival time, origin and destination, number of destined tickets, and willingness to pay. Each attribute can be generated using a specific distribution.

The created customers will then be used to simulate the purchase of tickets and overall revenue for a flight network. With a valid simulation, airlines will be able to compare the performance of different RM engines under various circumstances.