Abstract:
The focus of Air Cargo Revenue Management (ACRM) is to best estimate cargo capacity, forecast future demand, and take accept or reject decisions on the bookings accordingly. ACRM is a different problem than passenger revenue management due to uncertainty of cargo capacity, business, operations, and cargo booking behavior. These factors add additional complexity to a problem and make traditional revenue management approaches inadequate. Certain additional models need to be developed to solve the ACRM problem. The purposes of this thesis are to discuss the processes of air cargo revenue management and develop a spot allocation model. In the thesis, we develop a spot allocation optimization model. In necessary booking control conditions, this model is solved repetitively to decide on allocating expected demand to cargo capacity. A simulation study is performed after the optimization model to compare the results of our optimization model with a commonly used heuristic, First-Come First-Served, under defined scenarios and other test problem settings. Finally, we conclude that our model performed better than 26 out of 27 scenarios according to t-test statistics with a 95% confidence level.
