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Optimization of Fare Structure and Service Frequency for Maximum Profitability of Transit Systems

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  • Steven I.-J. Y. Chien
  • Chuck F. M. Tsai

Abstract

Providing efficient public transportation has been recognized as a potential way of alleviating congestion, improving mobility, mitigating air pollution, and reducing energy consumption. Many people use public transportation systems for their daily commute, while others use different transportation modes (e.g. cars, taxis, carpools, etc.). Inexpensive fares with good transit service encourages ridership, and the resulting revenue may be used to provide better service. Optimization of transit service frequency and its associated fare structure is desirable in order to increase revenue at reasonable transit operating expenditure. The objective of the study reported here is to maximize profit subject to service capacity constraint, while elastic demand is considered. The solution methodology is developed and applied to solve the profit maximization problem in a case study based on Newark, NJ, USA. Numerical results, including optimal solutions and sensitivity analyses, are presented. It is found that an optimal temporal headway and differential fare structure that maximizes total profit for the studied subway system can be efficiently solved.

Suggested Citation

  • Steven I.-J. Y. Chien & Chuck F. M. Tsai, 2007. "Optimization of Fare Structure and Service Frequency for Maximum Profitability of Transit Systems," Transportation Planning and Technology, Taylor & Francis Journals, vol. 30(5), pages 477-500, July.
    • Handle: RePEc:taf:transp:v:30:y:2007:i:5:p:477-500
    DOI: 10.1080/03081060701599961
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    References listed on IDEAS

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    1. Voith, Richard, 1991. "The long-run elasticity of demand for commuter rail transportation," Journal of Urban Economics, Elsevier, vol. 30(3), pages 360-372, November.
    2. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    3. Voith, Richard, 1997. "Fares, Service Levels, and Demographics: What Determines Commuter Rail Ridership in the Long Run?," Journal of Urban Economics, Elsevier, vol. 41(2), pages 176-197, March.
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    Cited by:

    1. Huang, Di & Liu, Zhiyuan & Liu, Pan & Chen, Jun, 2016. "Optimal transit fare and service frequency of a nonlinear origin-destination based fare structure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 1-19.
    2. Sun, S. & Szeto, W.Y., 2019. "Optimal sectional fare and frequency settings for transit networks with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 147-177.
    3. Guo, Qianwen & Sun, Yanshuo & Schonfeld, Paul & Li, Zhongfei, 2021. "Time-dependent transit fare optimization with elastic and spatially distributed demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 353-378.
    4. Bing-Zheng Liu & Ying-En Ge & Kai Cao & Xi Jiang & Lingyun Meng & Ding Liu & Yunfeng Gao, 2017. "Optimizing a desirable fare structure for a bus-subway corridor," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-21, October.

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