Large-scale multimodal transportation network models and algorithms-Part II: Network capacity and network design problem - Wang, Yu; Liu, Haoxiang; Fan, Yinchao; Ding, Jianxun; Long, Jiancheng (Transportation research. Part E, Logistics and transportation review, 2022)
•This paper proposes a novel bi-level multimodal network capacity problem.•A tri-level multimodal network design model is then formulated.•Kriging-surrogate-based optimization algorithms are developed to solve the models.•Numerical studies are conducted on the real-scale Nanjing network with 12,000 ODs.•Results show the efficiency of the proposed models and approaches. 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.