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Transportation Network Policy Modeling with Goal Targets and Generalized Penalty Functions

Author

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  • Anna Nagurney

    (Department of Finance and Operations Management, School of Management, University of Massachusetts, Amherst, Massachusetts 01003)

  • Padma Ramanujam

    (Department of Finance and Operations Management, School of Management, University of Massachusetts, Amherst, Massachusetts 01003)

Abstract

In this paper we develop a transportation network policy model that determines the equilibrium flow pattern and the transportation link tolls or taxes/subsidies in the presence of imposed transportation goals on the links of the network. The penalties (and subsidies) are functions of the deviations from the targets. The governing equilibrium conditions are shown to satisfy a variational inequality problem and existence and uniqueness results are presented using this methodology. A decomposition algorithm is proposed that resolves the problem into series of traffic network equilibrium problems and two simpler subproblems. Convergence results are also given. Finally, the algorithm is applied to numerical examples that illustrate how the model can be utilized for transportation pricing policy, as well as the numerical performance of the algorithm. This work extends recent research in spatial market policy modeling with goal targets on bipartite networks and with fixed penalties.

Suggested Citation

  • Anna Nagurney & Padma Ramanujam, 1996. "Transportation Network Policy Modeling with Goal Targets and Generalized Penalty Functions," Transportation Science, INFORMS, vol. 30(1), pages 3-13, February.
    • Handle: RePEc:inm:ortrsc:v:30:y:1996:i:1:p:3-13
    DOI: 10.1287/trsc.30.1.3
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    Citations

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    Cited by:

    1. D.R. Han & H.K. Lo, 2002. "New Alternating Direction Method for a Class of Nonlinear Variational Inequality Problems," Journal of Optimization Theory and Applications, Springer, vol. 112(3), pages 549-560, March.
    2. Xiaomei Dong & Xingju Cai & Deren Han & Zhili Ge, 2020. "Solving a Class of Variational Inequality Problems with a New Inexact Strategy," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 37(01), pages 1-20, January.
    3. Min Zhang & Deren Han & Gang Qian & Xihong Yan, 2012. "A New Decomposition Method for Variational Inequalities with Linear Constraints," Journal of Optimization Theory and Applications, Springer, vol. 152(3), pages 675-695, March.
    4. B. S. He & L. Z. Liao & H. Yang, 1999. "Decomposition Method for a Class of Monotone Variational Inequality Problems," Journal of Optimization Theory and Applications, Springer, vol. 103(3), pages 603-622, December.
    5. Robert B. Dial, 1999. "Network-Optimized Road Pricing: Part I: A Parable and a Model," Operations Research, INFORMS, vol. 47(1), pages 54-64, February.
    6. Deren Han & Wei Xu & Hai Yang, 2010. "Solving a class of variational inequalities with inexact oracle operators," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 71(3), pages 427-452, June.
    7. B. S. He & H. Yang & S. L. Wang, 2000. "Alternating Direction Method with Self-Adaptive Penalty Parameters for Monotone Variational Inequalities," Journal of Optimization Theory and Applications, Springer, vol. 106(2), pages 337-356, August.

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