IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v44y2010i4p447-459.html
   My bibliography  Save this article

A game theoretic framework for the robust railway transit network design problem

Author

Listed:
  • Laporte, Gilbert
  • Mesa, Juan A.
  • Perea, Federico

Abstract

This paper proposes a game theoretic framework for the problem of designing an uncapacitated railway transit network in the presence of link failures and a competing mode. It is assumed that when a link fails, another path or another transportation mode is provided to transport passengers between the endpoints of the affected link. The goal is to build a network that optimizes a certain utility function when failures occur. The problem is posed as a non-cooperative two-player zero-sum game with perfect information. The saddle points of the corresponding mixed enlarged game yield robust network designs.

Suggested Citation

  • Laporte, Gilbert & Mesa, Juan A. & Perea, Federico, 2010. "A game theoretic framework for the robust railway transit network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 447-459, May.
    • Handle: RePEc:eee:transb:v:44:y:2010:i:4:p:447-459
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(09)00112-X
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kelly J. Cormican & David P. Morton & R. Kevin Wood, 1998. "Stochastic Network Interdiction," Operations Research, INFORMS, vol. 46(2), pages 184-197, April.
    2. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    3. Terry L. Friesz & Javier Luque & Roger L. Tobin & Byung-Wook Wie, 1989. "Dynamic Network Traffic Assignment Considered as a Continuous Time Optimal Control Problem," Operations Research, INFORMS, vol. 37(6), pages 893-901, December.
    4. Chaisak Suwansirikul & Terry L. Friesz & Roger L. Tobin, 1987. "Equilibrium Decomposed Optimization: A Heuristic for the Continuous Equilibrium Network Design Problem," Transportation Science, INFORMS, vol. 21(4), pages 254-263, November.
    5. Gilbert Laporte & Juan Mesa & Francisco Ortega & Ignacio Sevillano, 2005. "Maximizing Trip Coverage in the Location of a Single Rapid Transit Alignment," Annals of Operations Research, Springer, vol. 136(1), pages 49-63, April.
    6. Bell, Michael G. H., 2000. "A game theory approach to measuring the performance reliability of transport networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(6), pages 533-545, August.
    7. Bell, Michael G. H. & Cassir, Chris, 2002. "Risk-averse user equilibrium traffic assignment: an application of game theory," Transportation Research Part B: Methodological, Elsevier, vol. 36(8), pages 671-681, September.
    8. Fisk, C. S., 1984. "Game theory and transportation systems modelling," Transportation Research Part B: Methodological, Elsevier, vol. 18(4-5), pages 301-313.
    9. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    10. Mustafa Abdulaal & Larry J. LeBlanc, 1979. "Methods for Combining Modal Split and Equilibrium Assignment Models," Transportation Science, INFORMS, vol. 13(4), pages 292-314, November.
    11. Yaron Hollander & Joseph Prashker, 2006. "The applicability of non-cooperative game theory in transport analysis," Transportation, Springer, vol. 33(5), pages 481-496, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ng, ManWo & Waller, S. Travis, 2010. "A computationally efficient methodology to characterize travel time reliability using the fast Fourier transform," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1202-1219, December.
    2. Pablo E. Achurra-Gonzalez & Panagiotis Angeloudis & Nils Goldbeck & Daniel J. Graham & Konstantinos Zavitsas & Marc E. J. Stettler, 2019. "Evaluation of port disruption impacts in the global liner shipping network," Journal of Shipping and Trade, Springer, vol. 4(1), pages 1-21, December.
    3. Dadkar, Yashoda & Nozick, Linda & Jones, Dean, 2010. "Optimizing facility use restrictions for the movement of hazardous materials," Transportation Research Part B: Methodological, Elsevier, vol. 44(2), pages 267-281, February.
    4. Reilly, Allison & Nozick, Linda & Xu, Ningxiong & Jones, Dean, 2012. "Game theory-based identification of facility use restrictions for the movement of hazardous materials under terrorist threat," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 115-131.
    5. Yaron Hollander & Joseph Prashker, 2006. "The applicability of non-cooperative game theory in transport analysis," Transportation, Springer, vol. 33(5), pages 481-496, September.
    6. Clark, Stephen & Watling, David, 2005. "Modelling network travel time reliability under stochastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 39(2), pages 119-140, February.
    7. Ng, ManWo & Szeto, W.Y. & Travis Waller, S., 2011. "Distribution-free travel time reliability assessment with probability inequalities," Transportation Research Part B: Methodological, Elsevier, vol. 45(6), pages 852-866, July.
    8. Luan, Jianlin & Polak, John & Krishnan, Rajesh, 2019. "The structure of public-private sector collaboration in travel information markets: A game theoretic analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 19-38.
    9. Xuejie Bai & Yankui Liu, 2016. "Robust optimization of supply chain network design in fuzzy decision system," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1131-1149, December.
    10. Beck, Yasmine & Ljubić, Ivana & Schmidt, Martin, 2023. "A survey on bilevel optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 311(2), pages 401-426.
    11. Antonio G. Martín & Manuel Díaz-Madroñero & Josefa Mula, 2020. "Master production schedule using robust optimization approaches in an automobile second-tier supplier," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 143-166, March.
    12. Sebastian Rachuba & Brigitte Werners, 2017. "A fuzzy multi-criteria approach for robust operating room schedules," Annals of Operations Research, Springer, vol. 251(1), pages 325-350, April.
    13. Roy, Bernard, 2010. "Robustness in operational research and decision aiding: A multi-faceted issue," European Journal of Operational Research, Elsevier, vol. 200(3), pages 629-638, February.
    14. Hanks, Robert W. & Weir, Jeffery D. & Lunday, Brian J., 2017. "Robust goal programming using different robustness echelons via norm-based and ellipsoidal uncertainty sets," European Journal of Operational Research, Elsevier, vol. 262(2), pages 636-646.
    15. Donya Rahmani, 2019. "Designing a robust and dynamic network for the emergency blood supply chain with the risk of disruptions," Annals of Operations Research, Springer, vol. 283(1), pages 613-641, December.
    16. Seyed Babak Ebrahimi & Ehsan Bagheri, 2022. "A multi-objective formulation for the closed-loop plastic supply chain under uncertainty," Operational Research, Springer, vol. 22(5), pages 4725-4768, November.
    17. Mohsen Jalalimajidi & SM Seyedhosseini & Ahmad Makui & Masoud Babakhani, 2018. "Developing a comprehensive model for new energy replacement in the country’s development program using a robust optimization approach," Energy & Environment, , vol. 29(6), pages 868-890, September.
    18. Szeto, W.Y. & Farahani, R.Z. & Sumalee, Agachai, 2017. "Link-based multi-class hazmat routing-scheduling problem: A multiple demon approach," European Journal of Operational Research, Elsevier, vol. 261(1), pages 337-354.
    19. Gilani, H. & Sahebi, H. & Oliveira, Fabricio, 2020. "Sustainable sugarcane-to-bioethanol supply chain network design: A robust possibilistic programming model," Applied Energy, Elsevier, vol. 278(C).
    20. Yang, Hai & Bell, Michael G. H., 2001. "Transport bilevel programming problems: recent methodological advances," Transportation Research Part B: Methodological, Elsevier, vol. 35(1), pages 1-4, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:44:y:2010:i:4:p:447-459. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.