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The connectivity of the urban public transport network and the convenience of transfers between modes of transit are important factors that affect whether passengers choose public transport. Identifying the key nodes that affect network connectivity, direct access, transfers, and clarifying the main factors that restrict the network efficiency play important roles in improving the efficiency of the public transport network and establishing a "green city". On this premise, this paper constructs two single-layer networks and a composite network that can reflect the transfer relationship between 'bus–bus', 'metro–metro', and 'metro–bus' based on the method of Space-P. The composite network realizes the integration study of homogeneous and heterogeneous stops, lines, and transfer relationships in the public transport network. At the same time, five kinds of centrality indexes are applied to the transport transfer network, and the significance of these indexes in the network is explained. Through the comprehensive analysis of these five types of indexes, the key nodes affecting the network connectivity, direct access and transfer efficiency, can be identified more accurately. Taking the public transport network of Xi'an as an example, the structural characteristics of the networks, including scale-free and small-world characteristics, were empirically analyzed. The main stops that play important roles in networks were identified based on the integrated centrality, degrees, and weight degrees. The research results showed the following: (1) Xi'an's metro network, bus network, and metro–bus composite network all have scale-free and small-world characteristics. (2) The influence of the key stops of the metro network is concentrated, while the influence of the key stops of the bus network is scattered. (3) The public transport network in the first ring road area of Xi'an has the highest degree of direct access, and the core areas of the south, west, and north of Xi'an also have high direct access. However, the direct access in the area east of Xi'an is slightly lower. (4) Xi'an's bus transport network covers a large area, showing the characteristics of a dual-core "central + southern" network. (5) The metro–bus composite network demonstrates a closer connection between stops and a more balanced network. (6) Finally, the degree of direct access to stops in the bus transport network and metro transport network shows the characteristics of "the single core is dominant, and the circle diffusion weakens step by step". [ABSTRACT FROM AUTHOR]

For the dynamic takeout delivery vehicle routing problem, which faces fluctuating order demand and time-varying speeds, this study presents a novel approach. We analyze the time distribution of takeout orders and apply a Receding Horizon Control (RHC) strategy to convert the dynamic challenge into a static one. The driving speed of delivery vehicles on different roads at different times is determined based on the subdivision criteria of the urban road network and a traffic congestion measurement method. We propose a dynamic takeout delivery vehicle routing optimization model and a time-varying subdivision road network is established to minimize the total delivery cost. We validated the model through simulation examples. The optimization results show that the total distribution cost is reduced after considering the time-varying subdivision road network, with the penalty cost decreasing by 39%. It is evident that considering the subdivision of the road network can enhance order delivery efficiency and optimize the overall dining experience. The sensitivity analysis of various parameters reveals that the delivery platform must appropriately determine the time domain and allocate the number of delivery personnel based on order scale to avoid escalating delivery costs. These findings provide theoretical guidance for vehicle routing planning in the context of delivery platforms. [ABSTRACT FROM AUTHOR]

This paper focuses on the application of higher-order and multilayer networks in identifying critical causes and relationships contributing to hazardous materials transportation accidents. There were 792 accidents of hazardous materials transportation that occurred on the road from 2017 to 2021 which have been investigated. By considering time sequence and dependency of causes, the hazardous materials transportation accidents causation network (HMTACN) was described using the higher-order model. To investigate the structure of HMTACN such as the importance of causes and links, HMTACN was divided into three layers using the weighted k-core decomposition: the core layer, the bridge layer and the peripheral layer. Then causes and links were analyzed in detail. It was found that the core layer was tightly connected and supported most of the causal flows of HMTACN. The results showed that causes should be given hierarchical attention. This study provides an innovative method to analyze complicated accidents, which can be used in identifying major causes and links. And this paper brings new ideas about safety network study and extends the applications of complex network theory. [ABSTRACT FROM AUTHOR]

The Belt and Road has developed rapidly in recent years. Constructing a comprehensive traffic network is conducive to promoting the development of the the Belt and Road. To optimize the layout of the Belt and Road comprehensive traffic network, this paper identifies important cities. First, a weighted super adjacency matrix is defined, which includes sea, air, railway transportation and trans-shipment transportation between these transportation modes. With this matrix, the Belt and Road comprehensive traffic network (B&RCTN) is constructed. To identify important node cities, this paper proposes a method to calculate multi-layer centrality which considers inter-layer relationships. With the results of the above four centrality indexes, the Entropy Weight TOPSIS is used to synthesize the evaluation of the four indexes. Finally, the multi-layer comprehensive centrality rank of node cities is obtained. Result shows that there are 72 important cities in B&RCTN. These important cities are mainly distributed in the east and west of Eurasia. Eastern cities are located in East Asia and Southeast Asia, including 36 cities such as Singapore, Shanghai, Guangzhou, Shenzhen and Hong Kong. Western cities are concentrated in West Asia, Western Europe and North Africa along the Mediterranean coast, including 31 cities such as Istanbul, Dubai, Vienna, Trieste and Koper. There are few important cities in central Eurasia, except Almaty in Central Asia and Colombo in South Asia. In addition, important cities also include Moscow in Eastern Europe, Lagos and Lome in West Africa. Finally, based on the distribution of important cities, this paper puts forward some suggestions on the development of the Belt and Road comprehensive transportation. [ABSTRACT FROM AUTHOR]

This paper defines the weighted super adjacency matrix based on the existing super adjacency matrix. This paper, for the first time, combines the trade network, competitive network, and complementary network to construct the trade multilayer network, and innovatively defines the interlayer connections. Based on this, we build trade multilayer networks for three major agricultural products in the western region along the "Belt and Road". The paper then proposes analytical methods, including a classification algorithm for local network relations and a comparative analysis of trade development priorities based on the local network relations. The former is used to identify and categorize key trading countries and potential trading countries for western agricultural products along the "Belt and Road". The latter is used to examine the western regions' order of priority in developing trade relations with the classified countries. According to the findings, category I agricultural trade has 37 key trading countries among the "Belt and Road" countries. Their local network relationships are classified into six groups, and their trade development priorities are classified into four levels. There are 49 key trading countries in category II agricultural trade. Their local network relations can be classified into three groups, and their trade development priorities can be classified into two levels. There are 62 key trading countries in category IV agricultural trade. Their local network relationships are classified into six groups, and their trade development priorities are classified into four levels. Furthermore, only Chile is a potential trading partner in category I agricultural trade. Finally, this paper offers policy recommendations for the development of agricultural trade along the "Belt and Road" in the western region. [ABSTRACT FROM AUTHOR]