Large-scale multimodal transportation network models and algorithms-Part II: Network capacity and network design problem
•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...
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| Published in: | Transportation research. Part E, Logistics and transportation review Vol. 167; p. 102918 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
01.11.2022
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| ISSN: | 1366-5545, 1878-5794 |
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| Abstract | •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. |
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| AbstractList | •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. |
| ArticleNumber | 102918 |
| Author | Ding, Jianxun Liu, Haoxiang Wang, Yu Fan, Yinchao Long, Jiancheng |
| Author_xml | – sequence: 1 givenname: Yu surname: Wang fullname: Wang, Yu organization: School of Management, Hefei University of Technology, Hefei 230009, China – sequence: 2 givenname: Haoxiang surname: Liu fullname: Liu, Haoxiang email: liuhaoxiang@hfut.edu.cn organization: School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009, China – sequence: 3 givenname: Yinchao surname: Fan fullname: Fan, Yinchao organization: School of Management, Hefei University of Technology, Hefei 230009, China – sequence: 4 givenname: Jianxun surname: Ding fullname: Ding, Jianxun organization: School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009, China – sequence: 5 givenname: Jiancheng surname: Long fullname: Long, Jiancheng organization: School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009, China |
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