Affiliations: [a] School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China
| [b] National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu, China
| [c] School of Logistics, Chengdu University of Information Technology, Chengdu, China
Correspondence:
[*]
Corresponding author. Jingni Guo, Southwest Jiaotong University Xipu campus, School of Transportation and Logistics, Southwest Jiaotong University, Southwest Jiaotong University Xipu campus, 611756, China. E-mail: 947082371@qq.com.
Note: [1] Supported by: National Key Research and Development Project of China (2018YFB1601400).
Note: [2] About the First Author: Guo Jingni (1994-), female, Han nationality, born in Yuncheng, Shanxi, Ph.D. candidate, focused on risk management and control.
Abstract: The multimodal transport network in the region with complex environment and being easily affected by disturbance factors is used as the research object in our work. The characteristics of the cascading failure of such multimodal transport network were analyzed. From the perspective of network load redistribution, the risk control methods for the cascading failure of the multimodal transport network were investigated. This research aims to solve the problem that traditional load redistribution methods usually ignore the original-destination (OD) constraint and uncertain risks. The conditional value-at-risk (CVaR) was improved based on the Bureau of Public Roads (BPR) road impedance function to quantify the uncertainty of the disturbance factors. A nonlinear programming model was established with the generalized travel time as the objective function. A parallelly-running cellular ant colony algorithm was designed to solve the model. Empirical analysis was conducted on the multimodal transport network in Sichuan-Tibet region of China. The results of the empirical analysis verified the applicability of the proposed load redistribution method to such kind of regions and the effectiveness of the algorithm. This research provides theoretical basis and practical reference for the risk control of the cascading failure of multimodal transport networks in some regions.
Keywords: Uncertain disturbance, multimodal transport network, risk control, load redistribution, cellular ant colony algorithm
