IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v44y2010i4p482-492.html
   My bibliography  Save this article

Global optimum of the linearized network design problem with equilibrium flows

Author

Listed:
  • Wang, David Z.W.
  • Lo, Hong K.

Abstract

The road network design problem, typically formulated as a bi-level program or a mathematical program with equilibrium constraints, is generally non-convex. The non-convexity stems from both the traffic assignment equilibrium conditions and the non-linear travel time function. In this study, we formulate the network design problem as a single-level optimization problem with equilibrium constraints, and then we transform the equilibrium constraints into a set of mixed-integer constraints and linearize the travel time function. The final result is that we cast the network design problem with equilibrium flows into a mixed-integer linear program, whose solution possesses the desirable property of global optimality, subject to the resolution of the linearization scheme adopted.

Suggested Citation

  • Wang, David Z.W. & Lo, Hong K., 2010. "Global optimum of the linearized network design problem with equilibrium flows," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 482-492, May.
    • Handle: RePEc:eee:transb:v:44:y:2010:i:4:p:482-492
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(09)00120-9
    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. 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.
    2. Abdulaal, Mustafa & LeBlanc, Larry J., 1979. "Continuous equilibrium network design models," Transportation Research Part B: Methodological, Elsevier, vol. 13(1), pages 19-32, March.
    3. Lo, Hong K., 1999. "A novel traffic signal control formulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(6), pages 433-448, August.
    4. Lo, Hong K. & Chen, Anthony, 2000. "Traffic equilibrium problem with route-specific costs: formulation and algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 34(6), pages 493-513, August.
    5. Hong K. Lo, 2001. "A Cell-Based Traffic Control Formulation: Strategies and Benefits of Dynamic Timing Plans," Transportation Science, INFORMS, vol. 35(2), pages 148-164, May.
    6. Chiou, Suh-Wen, 2005. "Bilevel programming for the continuous transport network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 39(4), pages 361-383, May.
    7. Meng, Q. & Yang, H. & Bell, M. G. H., 2001. "An equivalent continuously differentiable model and a locally convergent algorithm for the continuous network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 35(1), pages 83-105, January.
    8. Terry L. Friesz & Hsun-Jung Cho & Nihal J. Mehta & Roger L. Tobin & G. Anandalingam, 1992. "A Simulated Annealing Approach to the Network Design Problem with Variational Inequality Constraints," Transportation Science, INFORMS, vol. 26(1), pages 18-26, February.
    9. Yang, Hai, 1997. "Sensitivity analysis for the elastic-demand network equilibrium problem with applications," Transportation Research Part B: Methodological, Elsevier, vol. 31(1), pages 55-70, February.
    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. Liu, Haoxiang & Wang, David Z.W., 2015. "Global optimization method for network design problem with stochastic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 72(C), pages 20-39.
    2. Meng, Qiang & Liu, Zhiyuan & Wang, Shuaian, 2012. "Optimal distance tolls under congestion pricing and continuously distributed value of time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(5), pages 937-957.
    3. Luathep, Paramet & Sumalee, Agachai & Lam, William H.K. & Li, Zhi-Chun & Lo, Hong K., 2011. "Global optimization method for mixed transportation network design problem: A mixed-integer linear programming approach," Transportation Research Part B: Methodological, Elsevier, vol. 45(5), pages 808-827, June.
    4. Li, Changmin & Yang, Hai & Zhu, Daoli & Meng, Qiang, 2012. "A global optimization method for continuous network design problems," Transportation Research Part B: Methodological, Elsevier, vol. 46(9), pages 1144-1158.
    5. Farahani, Reza Zanjirani & Miandoabchi, Elnaz & Szeto, W.Y. & Rashidi, Hannaneh, 2013. "A review of urban transportation network design problems," European Journal of Operational Research, Elsevier, vol. 229(2), pages 281-302.
    6. Wang, Shuaian & Meng, Qiang & Yang, Hai, 2013. "Global optimization methods for the discrete network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 42-60.
    7. Gallo, Mariano & D'Acierno, Luca & Montella, Bruno, 2010. "A meta-heuristic approach for solving the Urban Network Design Problem," European Journal of Operational Research, Elsevier, vol. 201(1), pages 144-157, February.
    8. Bar-Gera, Hillel & Hellman, Fredrik & Patriksson, Michael, 2013. "Computational precision of traffic equilibria sensitivities in automatic network design and road pricing," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 485-500.
    9. Tan, Zhijia & Yang, Hai & Tan, Wei & Li, Zhichun, 2016. "Pareto-improving transportation network design and ownership regimes," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 292-309.
    10. Meng, Qiang & Yang, Hai, 2002. "Benefit distribution and equity in road network design," Transportation Research Part B: Methodological, Elsevier, vol. 36(1), pages 19-35, January.
    11. Ukkusuri, Satish V. & Patil, Gopal, 2009. "Multi-period transportation network design under demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 625-642, July.
    12. Patriksson, Michael, 2008. "On the applicability and solution of bilevel optimization models in transportation science: A study on the existence, stability and computation of optimal solutions to stochastic mathematical programs," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 843-860, December.
    13. Meng, Q. & Yang, H. & Bell, M. G. H., 2001. "An equivalent continuously differentiable model and a locally convergent algorithm for the continuous network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 35(1), pages 83-105, January.
    14. 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.
    15. Diana P. Moreno-Palacio & Carlos A. Gonzalez-Calderon & John Jairo Posada-Henao & Hector Lopez-Ospina & Jhan Kevin Gil-Marin, 2022. "Entropy-Based Transit Tour Synthesis Using Fuzzy Logic," Sustainability, MDPI, vol. 14(21), pages 1-25, November.
    16. Wang, Yu & Liu, Haoxiang & Fan, Yinchao & Ding, Jianxun & Long, Jiancheng, 2022. "Large-scale multimodal transportation network models and algorithms-Part II: Network capacity and network design problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    17. Dung-Ying Lin & Ampol Karoonsoontawong & S. Waller, 2011. "A Dantzig-Wolfe Decomposition Based Heuristic Scheme for Bi-level Dynamic Network Design Problem," Networks and Spatial Economics, Springer, vol. 11(1), pages 101-126, March.
    18. Chiou, Suh-Wen, 2005. "Bilevel programming for the continuous transport network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 39(4), pages 361-383, May.
    19. Bastiaan Possel & Luc J. J. Wismans & Eric C. Berkum & Michiel C. J. Bliemer, 2018. "The multi-objective network design problem using minimizing externalities as objectives: comparison of a genetic algorithm and simulated annealing framework," Transportation, Springer, vol. 45(2), pages 545-572, March.
    20. Ge, Qian & Han, Ke & Liu, Xiaobo, 2021. "Matching and routing for shared autonomous vehicles in congestible network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).

    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:482-492. 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.