Journal
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
Volume 167, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tre.2022.102918
Keywords
Network capacity; Network design problem; Large-scale multimodal network; Tri-level model; Kriging-surrogate-based optimization
Categories
Funding
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- [71925001]
- [72188101]
- [72271079]
- [71801067]
- [2021T140173]
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This paper studies the enhancement of transportation network capacity in urban transportation planning. A general multimodal network capacity problem is proposed to depict transfers, mode overlap, common line problem, and congestion effect of transit. A tri-level multimodal network design problem is developed based on this problem to maximize the network capacity. The proposed framework is evaluated in real-scale urban networks using an efficient optimization algorithm.
Transportation network capacity enhancement is essential in urban transportation planning. In this paper, a general multimodal network capacity problem (MNCP) is proposed, which can de-pict 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.
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