Abstract: The China Railway Express involves multi-regional cross-border transportation, posing high uncertainty and complexity in security management. To enhance the risk prevention and control capacity of the China Railway Express transportation network, this paper combined network flow theory and resilience theory, employing the entropy-weighted TOPSIS method to comprehensively evaluate node risk and incorporate it into the network-weighted attack process. Virtual arcs are used to represent disturbance-induced unmet transportation demand, and a disturbed cargo flow allocation model was constructed. Global network efficiency was used as the structural metric, while the freight flow retention ratio is adopted as the functional metric. The resilience performance of the China Railway Express transportation network under different disturbance nodes and scales was quantified from both structural and functional perspectives, and corresponding resilience optimization strategies were proposed. The results indicate that: (1) The transportation network of the China Railway Express demonstrates a certain level of risk mitigation capability. When a disturbance occurs at a single node, 74.36% of the nodes cause less than 1% structural loss to the network, and 53.45% cause less than 1% functional loss. Nodes with low resilience in the network are mainly distributed in the western exit channels, assembly centers, and along the route of the New Eurasian Continental Bridge. (2) The functional resilience of the China Railway Express transportation network is more sensitive to disruption than its structural resilience, and its recovery process exhibits non-linear characteristics. (3) Regarding resilience enhancement, the comprehensive protection strategy proposed in this paper based on risk and resilience clustering can improve the resilience of the network by 38.24% when responding to a large-scale disturbance. This strategy outperforms the traditional node-protection strategy based on the magnitude of node risks. The research findings provide theoretical support and practical insights for the comprehensive evaluation and improvement of resilience in the China Railway Express network.

Key words: railway transportation, network resilience, resilience triangle theory, China Railway Express, risk perturbations, complex networks

摘要： 中欧班列涉及多地区跨国运输，安全管理面临高度不确定性和复杂性。为提升中欧班列运输网络的风险防控能力，本文结合网络流理论与韧性理论，采用熵权-优劣解距离(TOPSIS)法评估节点风险，并将其融入网络加权扰动过程；引入虚拟弧表示扰动下的未满足运输需求，构建风险扰动下的货流分配模型；以全局网络效率为结构指标，以货流保留比为功能指标，从结构与功能双视角量化不同扰动节点与扰动规模下中欧班列运输网络的韧性表现，并提出相应的韧性优化策略。结果表明：中欧班列运输网络自身具有一定的风险化解能力，单节点发生扰动时，74.36%的节点给网络带来的结构损失小于1%，53.45%的节点功能损失小于1%，网络中的低韧性节点主要分布在西部出境通道、集结中心与新亚欧大陆桥沿线；中欧班列运输网络的功能韧性比结构韧性更容易受到风险扰动影响，且其恢复过程呈现出非线性特征；韧性提升方面，本文提出的基于风险和韧性聚类的综合保护策略可以使网络在应对大规模扰动时韧性表现同比提升38.24%，效果优于基于节点风险大小的传统节点保护策略。研究成果可为中欧班列网络韧性评估与抗风险能力提升提供参考。

关键词: 铁路运输, 网络韧性, 韧性三角理论, 中欧班列, 风险扰动, 复杂网络