| Summary |
Yu-Tung, Liang,2007.07
Department of Transportation Technology and Management National Chiao Tung University
Since American Airlines successfully applied revenue management (RM) to raise its revenue, RM has become a common technique in the airline industry. Due to the current hub-and-spoke operation, the focus of the RM research has shifted from the traditional single-leg problem to the network-type problem. It was noticed that, though a mainstream approach for the network RM problem, the bid price control is ill with complicated procedure and heavy computational load. In addition, there are considerable limitations for this approach in terms of both methodological theory and practical application.
Based on the dynamic programming (DP) approach, which generates the optimal control policy, this study develops a method that can generate a suitable seat control policy by approximating the expected revenue function in the DP model. First, this study establishes the model and the associated algorithm for the single-leg RM problem. After performing the mathematical analysis, this approach is extended to the network RM problem. Finally, in order deal with the RM problem under the network context, this study adopts the concept of sampling to generate the approximation function.
Based on the result in the numerical experiment of a two-leg numerical example, the validity and effectiveness of the developed method is verified as the generated solution which is pretty close to the optimal solution and significantly better than the case with no RM control. It is believed that this study should serve as an excellent alternative for the current bid price control and provide an inspiring concept for other network-related RM problems. |
