Risk-Based Resilience Analysis and Optimisation for Multimodal Container Ports

Zhang, J (2026) Risk-Based Resilience Analysis and Optimisation for Multimodal Container Ports. Doctoral thesis, Liverpool John Moores University.

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Abstract

Multimodal container ports are critical nodes in global supply chains. As disruptions caused by extreme weather, equipment failures, congestion, public health events, and other uncertainties become increasingly frequent, maintaining the operational resilience of ports has become a major challenge for both industry and academia. Due to the tightly coupled nature of port operations, disruptions occurring in one subsystem may propagate to the others and trigger ripple effects, thereby generating indirect losses that can exceed the direct consequences of the initial disruption. However, most existing studies conceptualise ports as single nodes within broader transport networks, and thus fail to capture the internal operational complexity of multimodal container ports, limiting the accuracy and practical value of their implications for resilience management.
This research aims to develop a holistic resilience-oriented framework for multimodal container ports that explicitly considers micro-level operational processes, subsystem interdependencies, and ripple effects in the event of disruption. The framework is designed to support resilience management across the preparedness, response, and recovery stages. To achieve this, the research first develops a System Dynamics (SD) simulation model to represent the operational processes of five interconnected subsystems, namely liner shipping, feeder shipping, railway, trucking, and container yards, and to analyse how disruptions of different types and magnitudes propagate through the port system. Based on the simulated time-dependent performance of the port, a resilience assessment framework is then established by combining an improved resilience quantification method with Evidential Reasoning (ER) to evaluate resilience across multiple transport modes and Key Performance Indicators (KPIs). Building on these results, a Sobol-based Global Sensitivity Analysis (GSA) framework is proposed to identify the critical disruptions and their interactions that most strongly influence overall port resilience. Finally, focusing on large equipment failures, an Opportunistic Maintenance (OM) optimisation model is developed to determine maintenance strategies that jointly balance cost and expected port resilience.
Using real-world operational, accident, and maintenance data from one of the top 30 container ports in the world, extensive numerical experiments were conducted to assess the performance of the proposed models. The findings confirm that the models can effectively and reliably capture ripple effects, quantify resilience across different disruption scenarios, identify critical risk factors together with their combined effects, and provide decision support for resilience-oriented maintenance planning.
The techniques and models developed in this thesis provide useful insights and valuable implications for port resilience management from both theoretical and practical perspectives. From a theoretical perspective, this research advances port resilience studies from a predominantly network-level to a micro-level, operationally grounded perspective. It also establishes an integrated methodological framework that links dynamic simulation, resilience quantification, uncertainty analysis, and resilience enhancement coherently. From a practical perspective, the proposed methodology can be applied to any container port with a multimodal transport structure. It provides port operators, policymakers, and other multimodal transport stakeholders with a systematic, evidence-based tool to understand disruption mechanisms, assess resilience, prioritise critical risks, and design effective recovery strategies. Key findings demonstrate that quay crane and yard crane failures generate the strongest cross-subsystem impacts, with the yard being the most vulnerable area and congestion producing widespread ripple and lagging effects across port operations. Traffic congestion further disrupts liner, feeder, and railway operations through the linking role of internal trucking, while yard-side disruptions can propagate throughout the entire port system. GSA identifies liner quay crane disruptions as a dominant determinant of overall resilience and reveals that several individually moderate factors can generate substantial interaction effects under compound disruptions. Finally, opportunistic maintenance provides the greatest resilience benefits for deep water quay cranes, whereas additional maintenance of rail gantry and yard cranes often incurs higher costs without comparable resilience improvements. More broadly, this research contributes to enhancing the stability and sustainability of multimodal transport systems and the wider Container Supply Chains (CSCs).

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Port resilience; Maritime safety; Multimodal container terminal; Resilience analysis; Maritime risk
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Engineering and Built Environment
Date of acceptance:	17 September 2026
Date of first compliant Open Access:	25 September 2026
Date Deposited:	25 Sep 2026 13:49
Last Modified:	25 Sep 2026 13:49
Supervisors:	Yang, Z, Nguyen, TT, Dubey, R, Xin, X and Shi, X
URI:	https://researchonline.ljmu.ac.uk/id/eprint/29534

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