Multi-objective Pricing of High-speed Railway Passenger Tickets Based on Epsilon-constraint Method

被引:0
|
作者
Li X.-M. [1 ]
Cao H.-Z. [1 ]
机构
[1] School of Economics and Management, Beijing Jiaotong University, Beijing
基金
中国国家自然科学基金;
关键词
Bi-level programming model; Epsilon-constraint method; High-speed railway passenger fares; Multi-objective pricing; Pareto frontier; Railway transportation;
D O I
10.16097/j.cnki.1009-6744.2020.01.002
中图分类号
学科分类号
摘要
High-speed rail (HSR) ticket pricing is a multi-objective pricing problem. It not only ensures passenger welfare, but also increases the operator's reasonable profits. Considering passenger differences and multi-mode competition in different lengths of haul, this paper took profit and passenger welfare as HSR's objectives and discussed the optimal HSR ticket pricing solutions. It built a bi-level programming model combining with the epsilon-constraint method, extracted the multi-objective problems according to lexicographic techniques and designed a relaxation algorithm to derive the Nash equilibrium. Corresponding target values are used to plot the Pareto frontier and optimal pricing was determined. The results from computational experiments show the following findings: First, multi-objective solutions are more suitable for pricing reform because of their smaller fluctuation in price and quantity of passengers and improvements of performance; Second, short-haul tickets and time-sensitive passenger tickets are likely to increase even higher; Third, the competition of multi-mode transportation affects pricing implementation. The innovation is to apply the epsilon-constraint method to solve the multi-objective HSR ticket pricing. The proposed pricing method helps to optimize the interests of operators and passengers and provides thoughts for HSR ticket pricing for railway operator. Copyright © 2020 by Science Press.
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收藏
页码:6 / 11and26
页数:1120
相关论文
共 11 条
  • [1] Van Vuuren D., Optimal pricing in railway passenger transport theory and practice in the Netherlands, Transport Policy, 9, 2, pp. 95-106, (2002)
  • [2] Borndorfer R., Karbstein M., Pfetsch M.E., Models for fare planning in public transport, Discrete Applied Mathematics, 160, 18, pp. 2591-2605, (2012)
  • [3] Talebian A., Zou B., A multi-stage approach to air-rail competition: focus on rail agency objective, train technology and station access, Journal of Rail Transport Planning & Management, 6, 1, pp. 48-66, (2016)
  • [4] Yang H., Zhang A., Effects of high-speed rail and air transport competition on prices, profits and welfare, Transportation Research Part B: Methodological, 46, 10, pp. 1322-1333, (2012)
  • [5] Hwang C.L., Paidy S.R., Yoon K., Et al., Mathematical programming with multiple objectives: A tutorial, Computers & Operations Research, 7, 1-2, pp. 5-31, (1980)
  • [6] Li X.Y., Li X.M., Li X.W., Fare optimization model of high-speed rail and civil aviation based on group evolution under elastic demand, Systems Engineering, 33, 5, pp. 135-141, (2015)
  • [7] Li B., Zhao P., Li Y.F., Et al., Research on dynamic pricing of parallel trains of high-speed railway based on passenger segment, Journal of the China Railway Society, 39, 9, pp. 10-16, (2017)
  • [8] Williams H.C.L., On the formation of travel demand models and economic evaluation measures of user benefits, Environment and Planning A, 9, pp. 285-344, (1977)
  • [9] Cao H., Li X., Vaze V., Et al., Multi-objective pricing optimization for a high-speed rail network under competition, Transportation Research Record: Journal of the Transportation Research Board, 2673, 7, pp. 215-226, (2019)
  • [10] Yu S.Y., The competitive game modeling and empirical research of Chinese high-speed railway and civil aviation, (2012)