Huiyong Li

In the context of globalization and the Belt and Road Initiative, maintaining the stability and security of the China Railway Express network (CRN) is critical for international logistics operations. However, unexpected events can lead to node and edge failures within the CRN, potentially triggering cascading failures that critically compromise network performance. This study introduces a Coupled Map Lattice model that incorporates cargo flow dynamics, distributing cargo based on distance and the residual capacity of neighboring nodes. We analyze cascading failures in the CRN under three scenarios, isolated node failure, isolated edge disruption, and simultaneous node and edge failure, to assess the network’s vulnerability during emergencies. Our findings show that deliberate attacks targeting cities with high node strength result in more significant damage than attacks on cities with a high node degree or betweenness. Additionally, when edges are disrupted by unexpected events, the impact of edge removals on cascading failures depends on their strategic position and connections within the network, not just their betweenness and weight. The study further reveals that removing collinear edges can effectively slow the propagation of cascading failures in response to deliberate attacks. Furthermore, a single-factor cargo flow allocation method significantly enhances the network’s resilience against edge failures compared to node failures. These insights provide practical guidance and strategic support for the CR Express in mitigating the effects of both unforeseen events and intentional attacks.

Although the New International Land-Sea Trade Corridor (ILSTC) and China-Europe Railway Express (CR Express) have grown rapidly, few studies have proposed a unified approach to logistics hub selection that integrates these two corridors. This study addresses this research gap by conducting a comprehensive analysis of an integrated network, aiming to identify optimal logistics hubs that minimize costs and enhance environmental benefit. We first establish an initial logistics hub network consisting of 37 cities, chosen through a rigorous three-criterion screening process. Following this, we develop an evaluation indicator system that combines socio-economic metrics with network topology importance. Using an improved entropy-weighted TOPSIS model, we rank these cities to create a shortlist of candidate logistics hubs. Based on this ranking, we then formulate a logistics hub selection model tailored for both the CR Express and ILSTC networks, taking into account multimodal transport, congestion, and carbon emissions associated with hub operations. Our findings suggest that Chongqing, Zhengzhou, Changsha, Shijiazhuang, Urumqi, and Nanning are optimal logistics hubs within the integrated network. Comparative analysis demonstrates that this integrated approach to hub selection not only optimizes cargo transportation routes but also significantly enhances cost-effectiveness and operational efficiency, while meeting both economic and environmental goals.

To solve low delivery time-efficiency, high delivery cost, and other problems of logistics enterprises involved in intra-city parcel delivery, we developed a model that integrated the existing urban metro and road transportation networks into a multi-layer hub-and-spoke delivery network. First, we evaluated the transshipment capacity of metro stations using an entropy-weighted TOPSIS model. Four centrality indicators were chosen for evaluation to overcome the shortcomings of previous evaluations which did not take into account the actual spatial distances between metro stations. Based on the evaluation results we selected the candidate hub nodes. Then, in order to minimize the total delivery distance, we developed a new hub-and-spoke delivery network model in which service nodes are able to transfer parcels to the nearest hub directly, particularly in cases where their corresponding spoke is comparatively more distant. Finally, we use the Shanghai logistics enterprise YD as an example to verify the model. This study provides reference for building a hub-and-spoke logistics network for the intra-city logistics enterprise.

To solve the problem of excessive carbon emissions during transportation by China Railway Express, which results from excessive competition for freight, duplication of routes, and unbalanced development of China Railway Express between regions, we proposed a hub-and-spoke network that minimizes carbon emissions. First, we applied complex network theory to evaluate the importance of railway network nodes and used a gravity model to define the importance of highway and waterway transportation network nodes that integrate with the railway network. Next, we evaluated the railway, highway and waterway networks using an E-TOPSIS model and identified 13 candidate hub cities that comply with Chinese government policies. We then developed a mixed-integer programming model that accounted for both operating and carbon costs, with the carbon costs estimated based on carbon emission and different carbon trading prices in China and Europe. Finally, we selected Chongqing, Urumqi, Lanzhou, Tianjin, Changchun, Shenyang, and Xuzhou as the hub cities and another 65 cities as spoke cities for the China Railway Express transportation network.

As more and more China Railway (CR) express lines have opened under the government's 'Belt and Road Initiative', the performance of CR express operations has varied widely. Many CR express lines fa...