Resilience assessment for bus-metro multimodal networks considering various attacking scenarios
Resilience assessment for bus-metro multimodal networks considering various attacking scenarios
16
- 10.1016/j.tranpol.2023.06.016
- Jul 3, 2023
- Transport Policy
36
- 10.1016/j.trd.2024.104085
- Jan 29, 2024
- Transportation Research Part D
59
- 10.1016/j.physa.2020.124925
- Jul 14, 2020
- Physica A: Statistical Mechanics and its Applications
114
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- Feb 3, 2017
- Computer-Aided Civil and Infrastructure Engineering
27
- 10.1016/j.jclepro.2022.133237
- Jul 21, 2022
- Journal of Cleaner Production
345
- 10.1016/j.jtrangeo.2015.05.006
- May 16, 2015
- Journal of Transport Geography
28
- 10.1016/j.ress.2023.109250
- Mar 16, 2023
- Reliability Engineering & System Safety
- Retracted
21
- 10.1016/j.apm.2023.04.002
- Apr 11, 2023
- Applied Mathematical Modelling
16
- 10.1016/j.chaos.2017.11.009
- Nov 15, 2017
- Chaos, Solitons & Fractals
28
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- Oct 4, 2023
- Reliability Engineering & System Safety
- Research Article
- 10.56028/aetr.9.1.818.2024
- Feb 19, 2024
- Advances in Engineering Technology Research
As transit nodes in the field of international trade, ports are of critical importance for establishing and maintaining the effectiveness of the trade supply chain. However, the system performance of ports is vulnerable to disruptions caused by unexpected events such as natural disasters, accidental catastrophes, and public health emergency. These disruptive events will have serious negative impacts on the normal operation performance of ports and international trade among countries. This paper is to propose a comprehensive assessment framework of the system resilience of the port multimodal transport networks before and after the occurrence of disruption events, which can effectively improve its ability to deal with emergencies, minimize losses, and enhance the system performance levels. This paper also establishes several simulation experiments focusing on the full lifecycle of resilience based on topology of the transport networks, and simulates a variety of scenarios regarding different damage and recovery modes, such as deliberate attack, random attack, planned recovery, and random recovery, in the assessment process. Then the actual transport situation of Shanghai port is taken as a case study, and three multimodal transport networks including the sea-rail network, the sea-road network, and the sea-road-rail network under different disruption scenarios are compared,and evaluate the evolutions of the network resilience of the multimodal transport networks of Shanghai port stage by stage. In addition, managerial suggestions are also proposed based on the resilience assessments of different disruption scenarios to maximize the resilience of multimodal transport networks of Shanghai port.
- Research Article
10
- 10.1142/s0218126622503108
- Jul 30, 2022
- Journal of Circuits, Systems and Computers
With the development of urbanization and the evolution of urban network systems, multimodal urban transport network (MUTN) systems play a vital role in improving network effects and operational efficiency. However, urban transport networks are easily affected by natural disasters and traffic incidents, which can lead to significant human and economic losses. Accordingly, it is vital to be able to assess the resilience of transport networks in the face of various disruptions. This study, therefore, utilizes complex network theory to analyze the resilience of multimodal urban transport networks, with the resilience accessed based on topological indices. The MUTN in Beijing is selected as a case study for simulation analysis. Based on the road network and subway network, a model MUTN is established, and the Monte Carlo method is used to simulate random attacks. The results show that the MUTN in Beijing has good resilience against disruptions. This study guides the evaluation of the overall resilience of multimodal urban transport networks and will be useful for transportation planners and decision-makers in dealing with emergencies and natural disasters in the future.
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