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A Link-Node Nonlinear Complementarity Model for a Multiclass Simultaneous Transportation Dynamic User Equilibria

Author

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  • Mohamad K. Hasan

    (Department of Quantitative Methods and Information Systems, College of Business Administration, Kuwait University, Kuwait City, Kuwait)

  • Xuegang Ban

    (Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA)

Abstract

Static transportation network equilibrium models have evolved from traditional sequential models to simultaneous (combined) models, and then to the multiclass simultaneous models to improve prediction of traffic flow. Most Dynamic Traffic Assignment (DTA) models, however, still deal only with the trip assignment step (traveler route choice) that is one of several steps in the transportation planning process. In this paper, the authors combine a dynamic link-node based discrete-time Nonlinear Complementarity Problem (NCP) DTA model with a static Multiclass Simultaneous Transportation Equilibrium Model (MSTEM) in a unified dynamic link-node based discrete-time NCP Dynamic Multiclass Simultaneous Transportation Equilibrium Model (DMSTEM) model. The new model improves the prediction process and eliminates inconsistencies that arise when the DTA or Dynamic Traffic Assignment with Departure Time (DTA-DT) is embedded in a more comprehensive transportation planning framework. An iterative solution algorithm for the proposed DMSTEM model is proposed by solving several relaxed NCPs in each iteration of the algorithm.

Suggested Citation

  • Mohamad K. Hasan & Xuegang Ban, 2013. "A Link-Node Nonlinear Complementarity Model for a Multiclass Simultaneous Transportation Dynamic User Equilibria," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 4(1), pages 27-48, January.
    • Handle: RePEc:igg:joris0:v:4:y:2013:i:1:p:27-48
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    Cited by:

    1. P. Senthil Kumar, 2018. "Linear Programming Approach for Solving Balanced and Unbalanced Intuitionistic Fuzzy Transportation Problems," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 9(2), pages 73-100, April.

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