High-speed Railway Passenger Ticket Assignment Model And Its Applications Study Based On Revenue Management

ABSTRACT:In the1970s, high speed railway caused the attention of many countries in the world, raised a big wave of high-speed railway, our country’s high-speed railway has been an unprecedented development after entering the new century. As the mass construction of passenger dedicated line and opened in recent years, intensified competition between high-speed railway and other transportation way, many countries is introduced the revenue management theory into its operations management, in order to improve the competitiveness of the high-speed railway.In this paper, we further study of the high-speed railway passenger ticket allocation problem based on the relative theory of revenue management. First of all, on the basis of the research status at home and abroad are reviewed in this paper, then build research content and framework. Second, the basic concept of revenue management are reviewed, the research content and algorithm model, laid the foundation for the application of the revenue management. Third, applied the ideas of revenue management to put forward the method and model of high-speed railway ticket allocation, establish high speed railway short-term traffic demand forecasting model, and provide the necessary data for the ticket allocation model, and construct ticket dynamic adjustment model is based on the ticket distribution. Finally, with the Beijing-Shanghai high-speed railway passenger ticket data has carried on the empirical analysis.In the demand forecast of passenger flow, reference the thought of combination forecast method, raise the method of the passenger flow forecasting demand for this article, is the combination forecasting method of embedded empirical mode decomposition (EEMD) and grey support vector machine (GSVM). Railway passenger flow belongs to nonlinear and non-stationary data, and high speed railway in China’s development time is shorter, less passenger data, synthesized these characteristics selects two methods of combination forecasting, the prediction result is more accurate, it provides the data basis for the ticket allocation and dynamic adjustment.In the ticket allocation, firstly, we predict the daily passenger flow data using the EEMD-GSVM method on the line station accurately, then with the ticket maximum income of the selected line as the target to construct the ticket allocation model, considering the train capacity sufficient and insufficient situation were respectively constructed models, after on the basis of ticket allocation model, construct the dynamic adjustment model to maximize the ticket income.The empirical results show that the demand prediction results are more accurate, explain the validity of the forecasting model. Ticket income applied allocation model is more than the original ticket allocation, and the ticket income was further improved by dynamic adjustment, it indicated that the reasonable ticket allocation can not only improve the economic benefit of railway sector, but also can reduce the waste of the high-speed railway transportation resources.