Joint Optimization of Ticket Pricing Strategy and Train Stop Plan for High-Speed Railway: A Case Study

Jin Qin, Xiqiong Li, Kang Yang and Guangming Xu
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Jin Qin: School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China
Xiqiong Li: School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China
Kang Yang: School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China
Guangming Xu: School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China

Mathematics, 2022, vol. 10, issue 10, 1-17

Abstract: In this study, we examined ticket pricing and train stop planning for the high-speed railway (HSR), which integrates two key aspects of railway operation and organization. We considered that passenger demand is sensitive to the generalized travel cost (depending on the ticket price and the travel time) and that the train stop plan can affect the travel time and passenger distribution. Then, a mixed-integer non-linear optimization model was proposed for the joint problem of ticket pricing and train stop planning to maximize HSR’s transport revenue and minimize passengers’ travel time. Based on the high similarity between combinatorial optimization problems and the solid annealing principle, we designed a combined simulated annealing (CSA) algorithm to solve practical problems. The results of a numerical example in the real HSR network showed that the proposed method can improve transport revenue by 5.1% and reduce passengers’ travel time loss by 11.15% without increasing transport capacity.

Keywords: high-speed railway; ticket pricing; train stop plan; seat allocation; joint optimization; combined simulated annealing algorithm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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