Time-Dependent Pricing for High-Speed Railway in China Based on Revenue Management

Abstract

High-speed railway (HSR) is recognized as a green transportation mode with lower energy consumption and less pollution emission than other transportation. At present, China has the largest HSR network globally, but the maximum revenue of railway transportation corporations has not been realized. In order to make HSR achieve a favorable position within the fierce competition in the market, increase corporate revenue, and achieve the sustainable development of HSR and railway corporations, we introduce the concept of revenue management in HSR operations and propose an innovative model to optimize the price and seat allocation for HSR simultaneously. In the study, we formulate the optimization problem as a mixed-integer nonlinear programming (MINLP) model, which appropriately captures passengers’ choice behavior. To reduce the computational complexity, we further transform the proposed MINLP model into an equivalent model. Finally, the effectiveness of both the proposed model and solution algorithm are tested and validated by numerical experiments. The research results show that the model can flexibly adjust the price and seat allocation of the corresponding ticketing period according to the passenger demand, and increase the total expected revenue by 5.92% without increasing the capacity.

Collaborative Optimization of Dynamic Pricing and Seat Allocation for High-Speed Railways: An Empirical Study From China

“…Yan et al [21] developed a co-optimization model of resource capacity allocation and fare rates of HSR trains in different operation routes. Qin et al [22] proposed an innovative model to optimize the price and seat allocation for HSR simultaneously.…”

Which High-Speed Rail? LARG Approach between Plan and Design

“…The GDP growth rate related to railway infrastructure investment was significant in the less developed areas of the southwest and relatively modest in the developed regions of the east. However, considering the Chinese case from a different point of view, the China Railway Corporation has a significant debt problem due to their large investment into the HSR construction [28,29], and if this situation does not change, the HSR program will slow down, with a crucial impact on the sustainable development of rural areas…”

Discrete dynamic pricing and application of network revenue management for FlixBus

“…Dynamic pricing can only influence the booking time distribution. Qin et al (2019) as well as Zhu and Zhao (2020) need booking limits together with dynamic pricing because their model includes an upper bound constraint on the price. The resulting mathematical programs are solved by a heuristic algorithm or LINGO, respectively.…”