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Operators-Users Equilibrium Model in a Partially Regulated Transit System

Author

Listed:
  • Enrique Fernandez

    (Pontificia Universidad Católica de Chile, Santiago 22 Chile)

  • Patrice Marcotte

    (Université de Montréal, Montréal, Québec H3C 3J7, Canada and Collège militaire royal de Saint-Jean, Saint-Jean-sur-Richelieu, Québec J0J 1R0, Canada)

Abstract

We present two formulations of a model for finding equilibrium passenger and operator flows in a partially regulated transit system where bus operators are free to choose the routes on which they offer public transport services. The transit fares are assumed fixed and known. The model offers a detailed representation of the transit system network and of the transit users behavior. Congestion effects are also considered as a consequence of the operation of cars and buses over a common road network. Two algorithmic solution approaches are investigated.

Suggested Citation

  • Enrique Fernandez & Patrice Marcotte, 1992. "Operators-Users Equilibrium Model in a Partially Regulated Transit System," Transportation Science, INFORMS, vol. 26(2), pages 93-105, May.
    • Handle: RePEc:inm:ortrsc:v:26:y:1992:i:2:p:93-105
    DOI: 10.1287/trsc.26.2.93
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    Citations

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    Cited by:

    1. Zhi-Chun Li & William Lam & S. Wong, 2009. "The Optimal Transit Fare Structure under Different Market Regimes with Uncertainty in the Network," Networks and Spatial Economics, Springer, vol. 9(2), pages 191-216, June.
    2. Zhi-Chun Li & William Lam & S. Wong, 2012. "Optimization of Number of Operators and Allocation of New Lines in an Oligopolistic Transit Market," Networks and Spatial Economics, Springer, vol. 12(1), pages 1-20, March.
    3. Chavis, Celeste & Daganzo, Carlos F., 2013. "Analyzing the structure of informal transit: The evening commute problem," Research in Transportation Economics, Elsevier, vol. 39(1), pages 277-284.
    4. Wichiensin, Muanmas & Bell, Michael G.H. & Yang, Hai, 2007. "Impact of congestion charging on the transit market: An inter-modal equilibrium model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(7), pages 703-713, August.
    5. Preston, John, 2008. "Competition in transit markets," Research in Transportation Economics, Elsevier, vol. 23(1), pages 75-84, January.
    6. Szeto, W.Y. & Jiang, Y., 2014. "Transit route and frequency design: Bi-level modeling and hybrid artificial bee colony algorithm approach," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 235-263.
    7. Zhou, Jing & Lam, William H.K. & Heydecker, Benjamin G., 2005. "The generalized Nash equilibrium model for oligopolistic transit market with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 39(6), pages 519-544, July.
    8. Yuan Liu & Heshan Zhang & Tao Xu & Yaping Chen, 2022. "A Heuristic Algorithm Based on Travel Demand for Transit Network Design," Sustainability, MDPI, vol. 14(17), pages 1-17, September.
    9. Zubieta, Lourdes, 1998. "A network equilibrium model for oligopolistic competition in city bus services," Transportation Research Part B: Methodological, Elsevier, vol. 32(6), pages 413-422, August.
    10. Liu, Qi & Chow, Joseph Y.J., 2022. "Efficient and stable data-sharing in a public transit oligopoly as a coopetitive game," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 64-87.
    11. Matsubayashi, Nobuo & Umezawa, Masashi & Masuda, Yasushi & Nishino, Hisakazu, 2002. "Merger effect of two firms under network equilibrium," European Journal of Operational Research, Elsevier, vol. 137(2), pages 434-447, March.

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