A study on air cargo revenue management

Abstract

This thesis studies air cargo revenue management (RM) problems in spot market and long-term market. First, we consider a single-leg air cargo booking control problem on the spot market. The booking process is modeled as a discrete-time Markov chain and the airline?s decision on accepting/rejecting booking request is based on a bid-price control policy. To avoid the complexity of high dimensionality, the bid prices are derived from maximizing a reward function of the Markov chain. Numerical experiments show that the proposed model outperforms two existing booking control policies. Second, we study the capacity allocation problem in long-term market, in which one airline serves n forwarders. We propose a capacity bundling policy (CBP) to mitigate the negative impact of seasonal imbalance between supply and demand, and model the problem as a Stackelberg game. Numerical experiments show that CBP can increase the airline?s expected profit and reduce the risk under certain conditions. Last, we integrate the two models above and propose a conceptual framework for an air cargo RM system.