Graduation Year


Document Type




Degree Granting Department

Industrial Engineering

Major Professor

Dr. Tapas K. Das.


Dynamic pricing, Heuristics, Optimization, Reinforcement learning, Seat inventory control


The airline industry is facing unprecedented challenges in generating sufficient revenues to stay in business. Airlines must capture the greatest revenue yield from every flight by leaving no seats unsold and not over filling the cabin with discount fares. To succeed in doing the above airlines must be able to accurately forecast each of their market segments, manage product andprice availability to maximize revenue and react quickly to competitive changes in the market place. Thus seat inventory control and ticket pricing form the two major tools of revenue management. The focus of this paper is to consolidate the ideas of seats inventory control and pricing in order to maximize the revenues generated by an airline network. A continuous time yield management model for a network with multiple legs, multiple fare classes and dynamic price changes for all fare classes is considered.