Research on cascading failure modes and attack strategies of multimodal transport network

Jingni Guo; Junxiang Xu; Zhenggang He; Wei Liao

doi:10.3934/jimo.2020159

Article Contents

2022, Volume 18, Issue 1: 397-410. Doi: 10.3934/jimo.2020159

This issue Previous Article A robust time-cost-quality-energy-environment trade-off with resource-constrained in project management: A case study for a bridge construction project Next Article The approximation algorithm based on seeding method for functional

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-means problem^†

Research on cascading failure modes and attack strategies of multimodal transport network

1.
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
2.
National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China
3.
School of Logistics, Chengdu University of Information Technology, Chengdu 610225, China

^* Corresponding author: Wei Liao
^* Corresponding author: Wei Liao

Received: February 2020

Revised: September 2020

Early access: March 2021

Published: January 2022

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Abstract

Cascading failure overall exists in practical network, which poses a risk of causing significant losses. Studying the effect of different cascading failure modes and attack strategies of the network is conducive to more effectively controlling the network. In the present study, the uniqueness of multimodal transport network is investigated by complying with the percolation theory, and a cascading failure model is built for the multimodal transport network by considering recovery mechanisms and dynamics. Under the three failure modes, i.e., node failure, edge failure and node-edge failure, nine attack strategies are formulated, consisting of random node attacking strategy (RNAS), high-degree attacking strategy (HDAS), high-closeness attacking strategy (HCAS), random edge attacking strategy (REAS), high-importance attacking strategy (HIAS1), high-importance attacking strategy (HIAS2), random node-edge attacking strategy (RN-EAS), high degree-importance1 attacking strategy (HD-I1AS), as well as high closeness-importance2 attacking strategy (HC-I2AS). The effect of network cascading failure is measured at the scale of the affected network that varies with the failure ratio and the network connectivity varying with the step. By conducting a simulation analysis, the results of the two indicators are compared; it is suggested that under the three failure modes, the attack strategies exhibiting high node closeness as the indicator always poses more effective damage to the network. Next, a sensitivity analysis is conducted, and it is concluded that HCAS is the most effective attack strategy. Accordingly, the subsequent study on the cascading failure of multimodal transport network should start with the nodes exhibiting high closeness to optimize the network.

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Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C35.

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Figure 1. Multimodal transport network topology

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Figure 2. State change of node failure network

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Figure 3. State change of edge failure network

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Figure 4. State change of node-edge failure network

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Figure 6. Sensitivity analysis

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Figure 5. Impact of different attack strategies on the network

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Table 1. Network attacking strategy

Failure mode	Attack strategy
Node failure	RNAS	HDAS	HCAS
Edge failure	REAS	HIAS1	HIAS2
Node-edge failure	RN-EAS	HD-I1AS	HC-I2AS

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