With the rapid development of China’s high-speed railway, the ticket fare structure of high-speed trains is an urgent need of intelligent optimization. A reasonable fare scheme should maximize the revenue of Railway Company, at the same time balancing passengers’ choice behavior. This paper applies bi-level programming to deal with this ticket fare optimization problem. A bi-level programming model is built first, of which the upper level programming is the revenue maximization problem, and the lower level programming is the elastic-demand network flow equilibrium problem. Then, a heuristic algorithm based on sensitivity analysis is proposed to solve the model. At last, the actual case and data is applied to verify our method.
Intelligent Optimization of Ticket Fare for China High-Speed Railway
19th COTA International Conference of Transportation Professionals ; 2019 ; Nanjing, China
CICTP 2019 ; 5247-5256
2019-07-02
Conference paper
Electronic Resource
English
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