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The logistics industry plays a crucial role in facilitating regional economic development. Serving as a vital link connecting producers, consumers, and various components of the supply chain, it has a direct and profound impact on the prosperity and advancement of regional economies. Based on the panel data of 11 provinces in the Yangtze River Economic Belt from 2016 to 2020, this paper constructs the logistics capability evaluation index system from four aspects: regional economic base, logistics infrastructure, logistics development scale, information technology and talent support, and uses the entropy weight TOPSIS method to measure the logistics capability of each province. The adjacency space weight matrix, geographical distance weight matrix and economic distance weight matrix are selected to build a spatial econometric model to analyze the influencing factors and spatial spillover effects of regional logistics capability. The following conclusions can be drawn from the analysis. From 2016 to 2020, the regional logistics capacity of the Yangtze River Economic Belt shows a trend of increasing year by year, but the logistics capacity of different provinces within the region has a large room for improvement. From the perspective of spatial dimension, the logistics capacity of the Yangtze River Economic Belt is "high in the east and low in the west". The results of spatial econometric analysis based on the spatial Durbin model show that there are significant spatial spillover effects on the logistics capacity of provinces in the Yangtze River Economic Belt. Factors such as road network density, port throughput, water freight turnover, transportation, warehousing and postal employment will not only affect the logistics capacity of the region, but also have a spillover effect on the material capacity of neighboring provinces in the Yangtze River Economic Belt. This study improves the level of regional logistics capacity and promotes the regional economic development of the Yangtze River Economic Belt. It can be used as a reference for other regions or countries in terms of enhancing regional logistics capacity and promoting regional economic development. [ABSTRACT FROM AUTHOR]

The construction of major railway projects poses significant risks, which present considerable challenges to construction management. To accurately assess the level of construction management for these projects, this study incorporated resilience theory into the field. The grounded theory method was utilized to establish a resilience evaluation indicator system for managing a major railway project construction. Additionally, a resilience evaluation model based on the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation method was proposed. This model was applied to evaluate the construction management resilience of a major railway project located in the mountainous region of southwest China. The results indicated that the project exhibits a very high overall level of construction management resilience. Specifically, it demonstrates high levels of ability to monitor and warn, an ability to resist absorption, and an ability to respond to emergencies. Additionally, it showcases high levels of ability to recover and rebuild, and an ability to learn to adapt. The evaluation results were consistent with the actual situation and verified the correctness and reliability of the method. Based on the aforementioned research findings, this paper puts forward recommendations on material redundancy and resource security from a resource perspective, and suggestions on organizational optimization and personnel capacity improvement from a subject perspective, thus indicating directions for enhancing the management level of major engineering railway constructions. [ABSTRACT FROM AUTHOR]

Intelligent vehicular networks can not only connect various smart terminals to manned or unmanned vehicles but also to roads and people's hands. In order to support diverse vehicle-to-everything (V2X) applications in dynamic, intelligent vehicular networks, efficient and flexible routing is fundamental but challenging. Aimed to eliminate routing voids in traditional Euclidean geographic greedy routing strategies, we propose a hyperbolic-embedding-aided geographic routing strategy (HGR) in this paper. By embedding the network topology into a two-dimensional Poincaré hyperbolic disk, greedy forwarding is performed according to nodes' hyperbolic coordinates. Simulation results demonstrated that the proposed HGR strategy can greatly enhance the routing success rate through a smaller stretch of the routing paths, with little sacrifice of routing computation time. [ABSTRACT FROM AUTHOR]

In the rapidly evolving global marketplace, the logistics sector faces a multitude of challenges that demand implementation of more resilient solutions to respond to any future disturbance. Synchromodal transport, which is viewed as an extension of multimodal transport, is known as a key answer to this issue, as it provides more flexible and sustainable freight transport and also focuses on collaboration between different logistics players. We consider synchromodal transport as a collection of agents that not only have their own characteristics and behaviors, but also interact with each other, which impacts the entire system. In this paper, we study the system using an Agent-Based Modeling approach. The network represents the combination of long-haul and drayage transport, where pre-haulage and end-haulage are done only by truck, and the rest can be done by trucks, trains, or barges. A numerical experiment is conducted to evaluate cost savings and emissions reduction under different logistics service providers' relation and re-routing scenarios. Our findings show that synchromodal scenarios are more economically and environmentally efficient, and that they lead to higher flexibility and reliability compared to business-as-usual scenarios. Additionally, our model verifies that the cost saving is considerable when logistics service providers collaborate with each other. The results of sensitivity analyses show consistent overall trends when comparing the different scenarios. Therefore, the conclusions drawn from the original experiment appear to be applicable, not only for that specific instance, but have broader relevance and applicability. [ABSTRACT FROM AUTHOR]

As a key component of high‐performance switches and routers, the packet forwarding engine (PFE) is mainly responsible for selecting the appropriate output port for tens of thousands of packets within an extremely short time frame. However, the performance of PFE is determined by the selected group membership algorithm. This paper puts forth a hybrid strategy–caching scalar‐pair and vectors routing and forwarding (CSVRF), consisting of virtual output port bitmap caching (VOPBC) and fractional‐N SVRF to address major multicast forwarding issues such as scalability by using content addressable memory. In CSVRF, a virtual output port bitmap cache is introduced, which includes the most popular combinations of output port bitmap and divides the big scalar‐pair into N sub‐groups to achieve parallel compute and the reusability of less bit‐length prime. The results demonstrate that the memory space and the forwarding latency are effectively reduced compared with previous work. In space efficiency, it only required 10% memory space compared with the original SVRF/fractional‐N SVRF, decreased 10% memory usage compared with pure VOPBC and nearly improved 1 to 4 orders of magnitude of packet processing time compared with the original SVRF and the fractional‐N SVRF respectively. [ABSTRACT FROM AUTHOR]

UAVs in most real-world deployments communicate with a ground control station either in a one-hop manner, which has a limited working range, or relies on infrastructure support such as satellite communication, which is expensive. Although multi-hop transmission is more economic, it is lossy and generally incurs large delays. In this paper, we consider a mixed method, where a few UAVs are equipped with satellite modules, and aggregate and forward traffic of nearby UAVs. The surrounding UAVs and the forwarding UAV form a star topology. Based on this model, we design an UAV formation strategy to cover a given region to minimize both the total number of UAVs and the number of UAVs with satellite modules. Since these two goals may be competing, we propose seven strategies and analyze them theoretically. Simulations show that a good tradeoff between the two goals can be obtained when each star network consists of four UAVs. [ABSTRACT FROM AUTHOR]

This research emphasises the transformative power of digital solutions in Lithuanian forwarding companies, addressing the necessity for a systematic risk assessment to optimise processes and mitigate associated risks. The survey indicates an increasing adoption of digital solutions, with around two-thirds of companies already utilising them. A case study employing the AHP method identifies three key digital solutions: invoice automation, waybill digitisation and blockchain. A combined solution called a “document flow and management system”, showed significant potential for time and cost savings. Three risks – synchronising participants, employee resistance, and a lack of specialists – are identified as having the highest overall assessment and were selected for further analysis while implementing the prioritised digital solution. The expert evaluation identifies employee resistance as the most probable risk, posing potential significant losses in the initial post-implementation phase. Although issues with synchronising participants could yield similar losses, experts view this risk as less probable than employee resistance. After the AHP analysis, it was decided to evaluate the current information and document flow process, in other words, to optimise the process. The optimisation results show that freight forwarding companies could reduce document management time by up to 59%. [ABSTRACT FROM AUTHOR]

With the frequent occurrence of drone black flying in large stadiums and airports, the requirement of precise electromagnetic interference to achieve unmanned aerial vehicle (UAV) displacement and forced landing in these protected area became urgent. Since traditional suppression jamming will affect normal communication, and forwarding deceptive jamming has coverage hole, a smart forwarding deceptive jamming distribution optimal algorithm (SFDJDO) is proposed. It gives a mapping error scale factor and the optimal distribution of multistation forwarding equivalent mapping to solve the problem of distortion on the mapping scale caused by different distribution methods and reduces the influence of the mapping errors and the differences between the virtual and real point neighborhoods of the jamming source. A comparison of the proposed SFDJDO method to the existing jamming source distribution optimisation method is conducted in the aspect of area mapping and trajectory mapping. The findings reveal that when the GNSS receiver clock bias is within the capture range, SFDJDO demonstrates significant enhancements in mapping precision and jamming success rates. [ABSTRACT FROM AUTHOR]

Background: Due to the absence of unified global regulations, defining the service and legal role of freight forwarders is challenging. This, as well as the lack of a standardized limit to the freight forwarder's liability for loss or damage to the cargo, introduces misunderstandings into his relationship with the client. The purpose of this study is to analyze the most widely used limit for freight forwarder's liability, set in Special Drawing Rights (SDR) units, and to adjust it, which will allow for maintaining the purchasing power of the compensation amount over different periods of time. Methods: In this study, two methods of adjusting the liability limit were proposed. In accordance with the first one, the limit was adjusted considering the impact of dollar inflation on the SDR unit. The second method involves changes in the limit of liability, taking into account changes in world prices for goods. Results: The result of this study showed that the second method is more functional, helping to preserve the purchasing power of the liability limit most effectively over time. Conclusions: This study revealed the fluctuating purchasing power of the forwarder's liability limit over time and suggests utilizing a methodology tied to changes in global goods' prices for adjustment. [ABSTRACT FROM AUTHOR]

With a greater awareness of the challenges regarding environmental, societal, political, and economic factors, where reverse logistics has become a significant part of supply chain networks, this paper presents an integrated forward and reverse logistics network, named the Heterogeneous Fleet Vehicle Routing Problem with Multiple Forward/Reverse Cross-Docks (HF-VRPMFRCD). We consider a heterogeneous fleet of vehicles with different loading capacities and transportation costs. We also consider multiple cross-docks with two different operations: forward and reverse processes. The former focuses on delivering the demand from suppliers to customers, while the latter aims at returning unsold products from customers to suppliers. We propose a Simulated Annealing with Variable Neighborhood Descent (SAVND) algorithm for solving HF-VRPMFRCD, where Variable Neighborhood Descent (VND) is a local search heuristic embedded in the framework of Simulated Annealing (SA). SAVND outperforms the state-of-the-art algorithm in solving the Heterogeneous Fleet Vehicle Routing Problem with Multiple Cross-Docks (HF-VRPMCD), where the VND heuristic significantly improves the quality of solutions. For HF-VRPMFRCD benchmark instances, SAVND provides optimal solutions for small-scale instances and better solutions than those of the GUROBI solver for remaining larger instances. Lastly, we present and discuss the benefits of integrating the forward and reverse processes. • We study the heterogeneous fleet VRP with multiple forward/reverse cross-docks. • We formulate a mixed-integer linear programming model for the problem. • We develop a simulated annealing with variable neighborhood descent approach. • We present sensitivity analyses and managerial insights. [ABSTRACT FROM AUTHOR]

Durability is a desired characteristic for all battery packs in Electric Vehicles. In this study, the service life of the EV battery pack under real-world operating conditions is projected using an Arrhenius mathematical simulation model. The model comprises a 39.2 kWh EV Lithium-Ion battery pack integrated with a three-phase inverter to convert the battery pack's Direct Current output to Alternating Current. In addition, the Alternating Current output is coupled to a 100 kW permanent magnet synchronous motor, which is regarded as the load. A field-oriented controller provides pulse width-modulated output signals that are supplied back to the inverter to generate the correct driving current. Variable conditions of charge rate (C-rate: 1.25C -- 4C), discharge rate (C-rate: 0.5C -- 4C), temperature (25°C-60°C), and depth of discharge (30%-90%) are evaluated to determine the battery pack's service life. Under a 4C charge rate/0.5C discharge rate and 50% depth of discharge, the modeling results indicate the battery pack has a service life of approximately 6,000 h at low temperatures (25°C) and roughly 3,000 h at high temperatures (60°C). The model has been validated by comparing the results with experimental data from the literature. [ABSTRACT FROM AUTHOR]

The relentless expansion of urban populations and the surge in e-commerce have increased the demand for rapid delivery services, leading to an increase in truck traffic that contributes to urban congestion, environmental pollution, and economic inefficiencies. The critical challenge this poses is not only in managing urban spaces efficiently but also in aligning with global sustainability goals. This study addresses the pressing need for innovative solutions to reduce reliance on truck transportation in congested urban areas without compromising the efficiency of freight delivery systems. This study contributes a novel approach that leverages electrified and autonomous aircraft (EAA) cargo shuttles to shift the bulk of air transportable freight from road to air, specifically targeting underutilized airports and establishing vertiports in remote locations. By applying data mining techniques to analyze freight flow data, this research identifies key commodity categories and metropolitan statistical areas (MSAs) where the implementation of EAA services could significantly mitigate truck-induced congestion. The findings reveal that targeting a select few commodities and MSAs can potentially decrease truck traffic, with electronics emerging as the dominant commodity category, and cities like Los Angeles and Chicago as prime candidates for initial EAA service deployment. Stakeholders in urban planning, transportation logistics, and environmental policy will find this study's insights beneficial. This work lays a foundation for future innovations in sustainable urban mobility and logistics. [ABSTRACT FROM AUTHOR]

Cold chain logistics are crucial for reducing agricultural product loss, yet the environmental impact of energy and packaging consumption, among others, demands attention, making the search for eco-friendly development modes essential. Based on data from 30 provinces in China from 2015 to 2021, this study analyzes the basic correlation between the development of cold chain logistics of fresh agricultural products (CCLFAP) and the ecological environment (EE) by using a random forest regression model in comparison with the XGBoost model. Correlation heatmaps were used to analyze the relationships between the cold chain logistics of fresh agricultural products and various factors of the ecological environment. The generalized additive model was then used to establish the connection between cold chain logistics and the ecological environment, identifying significant factors impacting EE. The results demonstrate that a higher development level of cold chain logistics corresponds to a better development trend of EE. The economic efficiency and technical aspects of cold chain logistics for fresh agricultural products are closely related to ecological pressures and responses. The number of employees in the logistics industry, the trading volume of fresh agricultural products, the number of refrigerated vehicles, and the capacity of the cold room have significant positive correlations with the ecological environment, while the per capita consumption of fresh agricultural products, the number of cold chain logistics patent applications, and the road density had significant negative correlations with the ecological environment. The effects of the number of cold chain logistics enterprises and the freight turnover of agricultural products transported by the cold chain on the ecological environment fluctuated. These findings contribute to reducing climate and environmental emergencies throughout the life cycle, offering sustainable development solutions for the fresh agricultural product cold chain logistics industry. [ABSTRACT FROM AUTHOR]

Named Data Networking (NDN) has emerged as a promising architecture to overcome the limitations of the conventional Internet Protocol (IP) architecture, particularly in terms of mobility, security, and data availability. However, despite the advantages it offers, producer mobility management remains a significant challenge for NDN, especially for moving vehicles and emerging technologies such as Unmanned Aerial Vehicles (UAVs), known for their high-speed and unpredictable movements, which makes it difficult for NDN to maintain seamless communication. To solve this mobility problem, we propose a Distributed Mobility Management Scheme (DMMS) to support UAV mobility and ensure low-latency content delivery in NDN architecture. DMMS utilizes decentralized Anchors to forward proactively the consumer's Interest packets toward the producer's predicted location when handoff occurs. Moreover, it introduces a new forwarding approach that combines the standard and location-based forwarding strategy to improve forwarding efficiency under producer mobility without changing the network structure. Using a realistic scenario, DMMS is evaluated and compared against two well-known solutions, namely MAP-ME and Kite, using the ndnSIM simulations. We demonstrate that DMMS achieves better results compared to Kite and MAP-ME solutions in terms of network cost and consumer quality-of-service metrics. [ABSTRACT FROM AUTHOR]

Time‐sensitive networking (TSN) is considered one of the most promising solutions to address real‐time scheduling in in‐vehicle network due to its capabilities for providing deterministic service. The TSN working group proposed various traffic shaping mechanisms, while deterministic scheduling of hybrid traffic is still not effectively solved since the traffic requirements are difficult to satisfy by standalone or combined mechanisms with fixed time slot divisions. This article presents a time‐aware multi‐cyclicqueuing and forwarding scheduling model, that integrates the no‐wait enabled time‐aware shaper and multi‐cyclic queuing and forwarding shaping models. Then, a scheduling solution, dubbed "TSN scheduling optimizer" (TSO) is proposed that combines optimization methods and incremental techniques. TSO aims to balance the load to maximize flow schedulability while guaranteeing the service requirements of hybrid traffic. Simulation evaluations through OMNeT++ provide a performance assessment of this proposed scheduling model, which can satisfy multiple types of traffic transmission requirements. Furthermore, TSO is compared with other baseline scheduling solutions, and TSO shows efficacy regarding execution time and schedulability. [ABSTRACT FROM AUTHOR]

As a strategic pillar of the Asian economic trade partnership, the logistics industry is a source of significant industrial relevance and specifically targeted CO2 emission initiatives. Therefore, in order to address the potential environmental risks that are associated with existing Asian free trade agreements and achieve global mitigation targets, it is imperative that one evaluates both the performance of the logistic sector and the factors that drive carbon emissions. As such, our research analyses 16 countries both the Regional Comprehensive Economic Partnership, from one of the largest emerging global trade partnerships in Asia, and the South Asian Association for Regional Cooperation. The results of which act as an important guide in how the green logistic service sector can be driven in emerging economies. In order to conduct this analysis, a balanced panel dataset from 2007 to 2018 is employed and estimated using Generalized Least Square and the Generalized Method of Moments regression approaches, with the issues of cross-sectional dependence, unit-root, stationarity, and cointegration also checked. The results revealed that economic growth, foreign direct investment inflows, and international trade positively affect logistics performance. In addition, improved logistics services, a hassle-free customs clearance process, and the frequency of shipments reduce transport CO2 emissions by 0.177%, 0.026%, and 0.014%, respectively. These findings suggest that renewable energy sources may alleviate the detrimental impact of logistics services on low-carbon transportation and spur economic action with substantial international trade opportunities available. This study hypothetically proposes and verifies a new dimension for two variables: international trade (export–import goods) and transport CO2 emissions. The lessons drawn from the study assist policymakers and stakeholders in rethinking the roles of green logistics infrastructure in the future. [ABSTRACT FROM AUTHOR]