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Large-scale multimodal transportation network models and algorithms-Part I: The combined mode split and traffic assignment problem

Author

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  • Fan, Yinchao
  • Ding, Jianxun
  • Liu, Haoxiang
  • Wang, Yu
  • Long, Jiancheng

Abstract

Modelling the combined mode split and traffic assignment (CMSTA) problem is essential to capture the travelers’ behaviors and predict the flow distribution in multimodal transportation networks. In this paper, a general fixed-point model that combines the CNL-based mode split and the VI-based traffic assignment is developed to formulate the CMSTA problem in a more realistic multimodal network. The transit common line problem and asymmetric travel cost are considered. A new solution algorithm that integrated with several effective methods and strategies is proposed to solve the fixed-point model in large-scale networks. Numerical results show the effectiveness of the proposed model and algorithm.

Suggested Citation

  • Fan, Yinchao & Ding, Jianxun & Liu, Haoxiang & Wang, Yu & Long, Jiancheng, 2022. "Large-scale multimodal transportation network models and algorithms-Part I: The combined mode split and traffic assignment problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    • Handle: RePEc:eee:transe:v:164:y:2022:i:c:s1366554522002186
    DOI: 10.1016/j.tre.2022.102832
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    References listed on IDEAS

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    Cited by:

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    3. 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).
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    5. Wang, Zhenjie & Zhang, Dezhi & Tavasszy, Lóránt & Fazi, Stefano, 2023. "Integrated multimodal freight service network design and pricing with a competing service integrator and heterogeneous shipper classes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).

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