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Large-scale multimodal transportation network models and algorithms-Part II: Network capacity and network design problem

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

Abstract

Transportation network capacity enhancement is essential in urban transportation planning. In this paper, a general multimodal network capacity problem (MNCP) is proposed, which can depict the transfers, mode overlap, and common line problem and congestion effect of transit. The problem is established as a bi-level model with combined mode choice and traffic assignment as the lower-level programming. Based on the MNCP, a tri-level multimodal network design problem (MNDP-MNCP) is developed to maximize the network capacity. The models are solved with an efficient Kriging-surrogate-based optimization algorithm in real-scale urban networks. Numerical results demonstrate the performances of the proposed framework.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:transe:v:167:y:2022:i:c:s1366554522002952
    DOI: 10.1016/j.tre.2022.102918
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