Transportation Research Part E-Logistics and Transportation Review最新文献_第6页

Semi-flexible transit service optimization considering scenario-based demand fluctuations 考虑场景需求波动的半柔性公交服务优化

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-12-12 DOI: 10.1016/j.tre.2025.104589

Yating Liu , Ziyulong Wang , Oded Cats , Xin Pei , Pan Shang

Semi-flexible transit, integrating fixed-route and on-demand services, offers a demand-adaptive and cost-effective alternative for public transit users, particularly in low-demand conditions. Despite the growing interest in this system, existing approaches have failed to develop comprehensive optimization methods for managing demand fluctuations across distinct scenarios, thereby significantly constraining operational adaptability in semi-flexible transit services. To address this research gap, we propose a scenario-based optimization model that jointly determines the fleet size and master routes at the tactical level as well as sub-routes at the operational level. The objective is to minimize travel costs while ensuring service feasibility under varying passenger demand scenarios, accounting for constraints such as travel time, state changes, time windows, and route consistency. Then, an Augmented Lagrangian Relaxation under Alternating Direction Method of Multipliers (ALR-ADMM) decomposition solution framework is introduced to decouple the proposed integrated problem into three sub-problems, namely master route, sub-route and service planning problems. Numerical experiments on the Sioux-Falls network validate the proposed model and solution approach, achieving a 94.93 % reduction in computation time while maintaining an average optimality difference of 0.57 % compared to the Gurobi optimizer. Sensitivity analysis further examines the effects of vehicle capacity limits, penalty parameters, and demand stop selection, revealing their impact on computational efficiency and operational costs. The applicability of our approach is further assessed through a real-world case study on the West Jordan network, which provides evidence of the ALR-ADMM-based algorithm in terms of both solution quality and computational efficiency. Our findings illustrate the feasibility and potential of the proposed model and algorithm in navigating both the tactical and operational scheme of semi-flexible transit within modern urban transit systems.

半灵活交通，结合了固定路线和按需服务，为公共交通用户提供了一种适应需求和具有成本效益的替代方案，特别是在需求低的条件下。尽管人们对这一系统的兴趣日益浓厚，但现有方法未能开发出管理不同情况下需求波动的综合优化方法，从而大大限制了半灵活运输服务的运营适应性。为了解决这一研究缺口，我们提出了一种基于场景的优化模型，该模型在战术层面共同确定车队规模和主路线，在作战层面共同确定子路线。目标是在考虑旅行时间、状态变化、时间窗口和路线一致性等约束的情况下，最大限度地降低旅行成本，同时确保服务在不同乘客需求情景下的可行性。然后，引入增广拉格朗日松弛交替方向乘数法（ALR-ADMM）分解解框架，将综合问题解耦为主路、子路和服务规划三个子问题。在Sioux-Falls网络上的数值实验验证了所提出的模型和解决方法，与Gurobi优化器相比，计算时间减少了94.93%，同时保持了0.57%的平均最优性差异。敏感性分析进一步考察了车辆容量限制、惩罚参数和需求停止选择的影响，揭示了它们对计算效率和运营成本的影响。通过对西约旦网络的实际案例研究，进一步评估了我们方法的适用性，该研究在解决方案质量和计算效率方面提供了基于alr - adm的算法的证据。我们的研究结果说明了所提出的模型和算法在导航现代城市交通系统中半灵活交通的战术和操作方案方面的可行性和潜力。

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引用次数: 0

Trade dynamics of the global dry bulk shipping network 全球干散货航运网络的贸易动态

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-12-12 DOI: 10.1016/j.tre.2025.104597

Yan Li , Carol Alexander , Michael Coulon , István Zoltán Kiss

The primary objective of this study is to determine how global shocks and commodity-specific geographical factors interact to shape the structure, resilience, and vulnerability of the dry bulk shipping network. To do so, we examine the global dry bulk shipping network and its coal, grain, and iron ore sub-networks from 2015 to 2023 using micro-level trade flow data. We find that these networks are highly concentrated around a small number of key export ports, with heavy-tailed degree distributions and strong core-periphery structures. However, the impact of external shocks is sharply commodity-specific: the COVID-19 pandemic triggered a major reorganisation of coal trade communities, while the war in Ukraine fragmented the grain network and drastically reduced Ukraine’s exports. In contrast, iron ore trade patterns remained relatively stable during the same period. Small-world features are present mainly within the densely interconnected core of each commodity network, where bi-directional trades are observed, while most peripheral ports function as either importers or exporters only. These findings clarify how the interplay of geography, trade imbalance, and global disruptions shapes network structure and resilience, offering insights for supply chain risk management in maritime logistics.

本研究的主要目的是确定全球冲击和特定商品的地理因素如何相互作用，以塑造干散货航运网络的结构、弹性和脆弱性。为此，我们利用微观层面的贸易流数据，研究了2015年至2023年全球干散货航运网络及其煤炭、谷物和铁矿石子网络。研究发现，这些网络高度集中在少数重点出口港口周围，具有重尾度分布和较强的核心-外围结构。然而，外部冲击的影响明显是针对商品的：2019冠状病毒病大流行引发了煤炭贸易社区的重大重组，而乌克兰的战争使粮食网络支离破碎，乌克兰的出口大幅减少。相比之下，同期铁矿石贸易格局保持相对稳定。小世界的特点主要出现在每一个商品网络紧密相连的核心，在那里可以观察到双向贸易，而大多数外围港口只起进出口的作用。这些发现阐明了地理、贸易不平衡和全球中断的相互作用如何影响网络结构和弹性，为海运物流中的供应链风险管理提供了见解。

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引用次数: 0

Towards net-zero shipping: A multi-level optimization model for green maritime corridors integrating bunker network, ship routes, and fleet deployment 迈向净零航运：绿色海上走廊的多层次优化模型，整合燃料库网络、船舶航线和船队部署

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-12-12 DOI: 10.1016/j.tre.2025.104595

Xiaohuan Lyu , Jian Gang Jin , Zhu Wang

Green Maritime Corridors (GMCs) have recently gained prominence as a strategic initiative to accelerate the net-zero transition in maritime shipping. However, their implementation is constrained by underdeveloped bunkering infrastructure, fragmented shipping networks, and industry reluctance to invest in green technologies. Although carbon pricing instruments, such as the Emission Trading System (ETS) and FuelEU Maritime (FuelEU), are in place to internalize environmental externalities and encourage emission reductions, their influence has not been quantitatively assessed, particularly under fluctuating carbon prices. To bridge these gaps, this study develops a novel multi-level optimization model that functions as a decision-support tool for stakeholders, simultaneously addressing the strategic investment in bunkering infrastructure, tactical planning of ship routes, and operational deployment of alternative-fuel vessels. By incorporating dynamic carbon pricing policies in ETS and FuelEU, our model evaluates the viability of ammonia and methanol across diverse trade routes. Our findings, based on the LINER-LIB benchmark, reveal that (i) the transition is primarily capital-intensive, highlighting the critical role of sustainable investment; (ii) carbon policies rapidly shift the cost-competitiveness in favour of GMCs, validating the effectiveness of government intervention; and (iii) route-specific characteristics are more decisive than fuel type alone, underscoring the need for customized business models and strategies. This research delivers a comprehensive decision-support framework that directly facilitates the practical implementation of GMCs. By quantifying the interplay between policy, investment, and operations, the study provides actionable insights to give investors the confidence to secure investment in green projects, guide policymakers in designing effective regulations, and enable operators to navigate the energy transition.

绿色海上走廊（GMCs）最近作为加速海运净零转型的战略举措而受到重视。然而，它们的实施受到不发达的加油基础设施、分散的航运网络和行业不愿投资绿色技术的限制。虽然碳定价工具，如排放交易系统（ETS）和海事燃料联盟（FuelEU），已用于将环境外部性内部化并鼓励减排，但其影响尚未得到定量评估，特别是在碳价格波动的情况下。为了弥补这些差距，本研究开发了一种新的多层次优化模型，作为利益相关者的决策支持工具，同时解决了加油基础设施的战略投资、船舶路线的战术规划和替代燃料船舶的运营部署。通过在ETS和FuelEU中纳入动态碳定价政策，我们的模型评估了氨和甲醇在不同贸易路线上的可行性。基于LINER-LIB基准，我们的研究结果显示：(i)转型主要是资本密集型的，突出了可持续投资的关键作用；（ii）碳政策迅速使成本竞争力向有利于政府管理公司的方向转变，从而验证了政府干预的有效性；(3)航线特征比燃料类型更具有决定性，强调了定制商业模式和战略的必要性。本研究提供了一个全面的决策支持框架，直接促进了gmc的实际实施。通过量化政策、投资和运营之间的相互作用，该研究提供了可操作的见解，使投资者有信心确保绿色项目的投资，指导政策制定者设计有效的法规，并使运营商能够应对能源转型。

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引用次数: 0

An adaptive dynamic vehicle dispatching policy for intelligent-manual mixed fleet in semi-automated container terminals 半自动化集装箱码头智能-人工混合车队自适应动态车辆调度策略

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-12-12 DOI: 10.1016/j.tre.2025.104567

Xuqiang Chang , Rui Chen , Xi Xiang

This study addresses the vehicle dispatching problem in a semi-automated container terminal with an intelligent-manual mixed fleet consisting of electric intelligent guided vehicles and diesel container trucks. We propose a mixed-integer linear programming model with an adaptive dynamic vehicle dispatching policy to optimize multiple objectives, including energy consumption, transportation task completion time, and workload balance. The proposed model requires only minor configuration adjustments to deploy across three common real-world operational modes, leveraging a target-based optimal solution that dynamically adjusts objective weights for equitable trade-offs. Extensive numerical experiments are conducted to validate the proposed policy against three benchmark policies, demonstrating the superior adaptability and efficiency of our proposed policy in real-time dispatching across diverse scenarios. Furthermore, an in-depth analysis of energy replenishment processes underscores the complementary roles and operational distinctions of the two types of vehicles. Sensitivity analyses further reveal that a 60 % electric intelligent guided vehicles fleet proportion minimizes energy-time trade-offs, and energy consumption increases linearly with a higher export container proportion. Additional robustness tests under stochastic disruptions such as vehicle breakdowns and quay crane outages confirm that our proposed policy maintains stable performance and workload balance even under operational uncertainties. These findings provide actionable management insights for semi-automated container terminal operators to configure an intelligent-manual mixed fleet and adapt dispatching policies across dynamic operational modes, ensuring efficiency, sustainability, and scalability in real-world implementations.

本文研究了由电动智能导引车和柴油集装箱卡车组成的智能-手动混合车队的半自动化集装箱码头车辆调度问题。提出了一种混合整数线性规划模型，该模型具有自适应动态车辆调度策略，以优化能源消耗、运输任务完成时间和工作负载平衡等多个目标。所提出的模型只需要在三种常见的现实世界操作模式中进行较小的配置调整，利用基于目标的最优解决方案，动态调整目标权重以实现公平权衡。通过大量的数值实验验证了本文提出的策略与三种基准策略的有效性，证明了本文提出的策略在不同场景下的实时调度中具有优越的适应性和效率。此外，对能源补充过程的深入分析强调了两类车辆的互补作用和操作区别。灵敏度分析进一步表明，60%的电动智能导引车车队比例使能量-时间权衡最小化，能源消耗随着出口集装箱比例的增加而线性增加。在随机中断（如车辆故障和码头起重机中断）下的额外鲁棒性测试证实，即使在操作不确定的情况下，我们提出的策略也能保持稳定的性能和工作负载平衡。这些发现为半自动化集装箱码头运营商提供了可操作的管理见解，以配置智能手动混合船队，并根据动态运营模式调整调度策略，确保实际实施中的效率、可持续性和可扩展性。

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引用次数: 0

Hierarchical graph neural network-based generalized graph partitioning for accelerated large-scale microscopic traffic parallel simulation 基于层次图神经网络的广义图划分加速大规模微观交通并行仿真

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-12-12 DOI: 10.1016/j.tre.2025.104586

Chenxiang Ma , Chengcheng Xu , Pan Liu , Jianhui Huang

This study aims to develop an efficient traffic parallel simulation framework by using hierarchical graph neural network for graph partitioning, improving the scalability and accuracy of large-scale microscopic traffic simulations. To fully utilize road network information for partitioning, graph embedding learning is first introduced to enrich graph node features representation. Based on embedded network graph, aiming for balanced partitioning and minimized communication, graph partitioning model uses a hierarchical graph neural network architecture to infer partitioning result. Additionally, in the design of traffic information transmission mechanism, overlapping states and crossing vehicle groups are employed to ensure the synchronization of macro and micro traffic information between partitions. Experiments conducted on large-scale highway network in Henan Province, China, demonstrate significant improvements in simulation efficiency and accuracy over traditional methods. The framework can achieve efficient acceleration under different traffic demands, with a maximum speed up of 13.23 times in 16 partitions, while ensuring higher load balancing and lower communication cost. Meanwhile, parallel simulation can also achieve nearly 100% accuracy compared to the original simulation. Moreover, in real engineering scenarios, proposed framework can also highly reproduce traffic state changes to replace the original simulation while ensuring a speed up of over 5 times. This study demonstrates the great potential of our parallel simulation framework for large-scale traffic environments, providing robust support for addressing future traffic demand growth and complex road network management.

本研究旨在利用层次图神经网络进行图划分，开发高效的交通并行仿真框架，提高大规模微观交通仿真的可扩展性和准确性。为了充分利用路网信息进行分区，首先引入图嵌入学习，丰富图节点特征表示。图划分模型基于嵌入式网络图，以均衡划分和最小化通信为目标，采用层次图神经网络架构对划分结果进行推理。此外，在交通信息传递机制的设计中，采用了重叠状态和交叉车辆组，保证了分区间宏观和微观交通信息的同步。在中国河南省大型公路网上进行的实验表明，与传统方法相比，该方法的仿真效率和精度有了显著提高。该框架可以在不同的流量需求下实现高效的加速，在16个分区中最大速度提升13.23倍，同时保证更高的负载均衡和更低的通信成本。同时，与原始仿真相比，并行仿真也可以达到接近100%的精度。此外，在实际工程场景中，所提出的框架还可以高度再现交通状态变化，取代原始模拟，同时保证速度提高5倍以上。这项研究证明了我们的并行模拟框架在大规模交通环境中的巨大潜力，为解决未来交通需求增长和复杂的道路网络管理提供了强有力的支持。

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引用次数: 0

The periodic vehicle routing problem with multi-day trips 多日行程的周期性车辆路径问题

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-12-11 DOI: 10.1016/j.tre.2025.104582

Aliakbar Izadkhah , Akang Wang , Jose M. Lainez-Aguirre , Jose M. Pinto , Chrysanthos E. Gounaris

This work proposes the Periodic Vehicle Routing Problem with Multi-Day Trips, a new routing problem variant that is inspired by regional distribution operations in the industrial gases sector. In this problem, customers provide multiple visiting patterns, a.k.a. schedules, comprising specific days within the planning horizon when they expect to receive product. The goal is then to assign each customer to one valid schedule and design the corresponding routes for each day such that the distribution costs are minimized across the horizon. In our setting, we allow for long-haul routes that cannot be concluded within the course of one shift and the driver must have one or more layovers, in conformance to applicable hours-of-service regulations. To that end, we introduce a set partitioning model and propose a branch-price-and-cut algorithm, extending the classical periodic vehicle routing solution approach to accommodate the multi-day trips. Our approach is able to properly capture the connections between the time periods such that, along with the normal daily routes, the pricing subproblems and their dynamic programming solver also generate routes that extend across multiple days and are compliant with the regulations, all the while ensuring that customers are visited in accordance to their offered schedules. Instances with schedule-dependent demands, a.k.a. service choice, are also supported. We extend literature benchmark instances as well as use an industrial case study to assess the performance of our approach, which we show can routinely solve to guaranteed optimality instances with 20 customers along a 6-day planning horizon.

这项工作提出了多日行程的周期性车辆路线问题，这是一种新的路线问题变体，受到工业气体部门区域分布操作的启发。在这个问题中，客户提供多种访问模式，也就是时间表，包括他们期望收到产品的计划范围内的特定日期。然后，目标是为每个客户分配一个有效的时间表，并为每天设计相应的路线，以便在整个范围内将配送成本降至最低。在我们的设置中，我们允许在一个班次内无法完成的长途路线，并且司机必须根据适用的服务时间规定进行一次或多次停留。为此，我们引入了一个集合划分模型，并提出了一个分支价格削减算法，扩展了经典的周期车辆路线解决方法，以适应多日行程。我们的方法能够正确地捕捉时间段之间的联系，这样，除了正常的日常路线之外，定价子问题及其动态规划求解器也会生成跨越多天且符合规定的路线，同时确保客户按照提供的时间表访问。还支持具有计划相关需求（即服务选择）的实例。我们扩展了文献基准实例，并使用一个工业案例研究来评估我们的方法的性能，我们表明，我们的方法可以在6天的计划范围内常规地解决20个客户的保证最优性实例。

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引用次数: 0

A branch-and-price algorithm for task allocation and global path planning of multiple AGVs in intelligent warehouses 智能仓库中多agv任务分配与全局路径规划的分支价格算法

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-12-11 DOI: 10.1016/j.tre.2025.104587

Xuefang Han , Kunpeng Li , P.N. Ram Kumar

Automated guided vehicles (AGVs) are essential components of modern intelligent warehouse logistics systems, serving as the cornerstone of efficient material handling. Their growing importance highlights their vital role in enhancing the functionality and effectiveness of intelligent warehouses in today’s industries. These material handling systems encompass three key aspects of decision-making: task-to-AGV assignment, AGV path planning, and the scheduling of arrival and departure times for each AGV at various stations. While extensive research has focused on these elements independently, integrated studies addressing the problem comprehensively remain relatively rare. This study proposes a co-optimization problem for task allocation and global path planning for multiple AGVs in intelligent warehouse systems. It effectively integrates dispatching, conflict-free routing, and scheduling of these AGVs. We formulate the problem as a mixed-integer linear programming (MILP) model to minimize the delay time for all tasks and the operational time for all AGVs. Given that this problem is NP-hard, solving the MILP model efficiently for realistic-scale instances is challenging. To tackle the complexities involved, we developed a tailored branch-and-price (BP) algorithm specifically designed for small- to medium-scale problems, complemented by an efficient heuristic algorithm tailored for larger-scale challenges. Enhancements to the BP algorithm’s performance were achieved by incorporating several acceleration techniques that cater to the specific characteristics of our problem. Our experimental results reveal three key findings: (i) the BP algorithm effectively addresses the problem, (ii) the heuristic serves as a viable standalone solution for large-scale scenarios, while also providing high-quality initial solutions for the BP algorithm promptly, and (iii) the introduced acceleration methods significantly reduce the computational time required by the BP algorithm. Overall, our paper presents a robust and tailored approach to AGV material handling systems, providing valuable insights for warehouse operators and supporting their decision-making processes.

自动导引车（agv）是现代智能仓库物流系统的重要组成部分，是高效物料处理的基石。它们日益增长的重要性凸显了它们在增强当今工业智能仓库的功能和有效性方面的重要作用。这些物料处理系统包括决策的三个关键方面：任务到AGV分配，AGV路径规划，以及每个AGV在各个站点的到达和离开时间调度。虽然广泛的研究分别关注这些因素，但全面解决问题的综合研究仍然相对较少。研究了智能仓库系统中多agv任务分配和全局路径规划的协同优化问题。它有效地集成了这些agv的调度、无冲突路由和调度。我们将问题表述为混合整数线性规划（MILP）模型，以最小化所有任务的延迟时间和所有agv的操作时间。考虑到这个问题是np困难的，为实际规模的实例有效地解决MILP模型是具有挑战性的。为了解决所涉及的复杂性，我们开发了一种专门为中小型问题设计的分支和价格（BP）算法，并辅以一种为大规模挑战量身定制的高效启发式算法。BP算法的性能增强是通过结合几种加速技术来实现的，这些加速技术迎合了我们问题的特定特征。我们的实验结果揭示了三个关键发现：(i) BP算法有效地解决了问题；（ii）启发式算法可以作为大规模场景的可行独立解决方案，同时也可以快速为BP算法提供高质量的初始解；（iii）引入的加速方法显着减少了BP算法所需的计算时间。总的来说，我们的论文提出了一个强大的和量身定制的AGV材料处理系统的方法，为仓库运营商提供了有价值的见解，并支持他们的决策过程。

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引用次数: 0

Unveiling network vulnerability under multiple area-covering disruption scenarios: A scenario-enumeration-free model and empirical insights into targeted protection 揭示多个覆盖区域的中断场景下的网络漏洞：无场景枚举模型和针对目标保护的经验见解

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-12-11 DOI: 10.1016/j.tre.2025.104559

Junze Yang , Xiangdong Xu , Seungkyu Ryu

Multiple area-covering disruptions in transportation networks refer to events involving simultaneous failure or closure of several areas (e.g., flooding), which can cause broader impacts than link or node disruptions, with effects not simply additive from individual area failures. This study addresses the challenges in analyzing such disruptions, which include handling randomness in their occurrence locations and impact ranges, and dealing with the combinatorial complexity of multiple disruption scenarios. In particular, based on the observed hierarchical state dependencies among disrupted areas, links, paths, origin–destination (OD) pairs, and the overall network, we propose a vulnerability analysis model that obviates the need for brute-force enumeration of all potential disruption scenarios. Methodologically, compared with widely-adopted bi-level programming models for multiple-link disruptions, the proposed model is directly formulated as a single-level mixed-integer linear programming, thereby offering better computational tractability due to its compact model structure. The model also exhibits remarkable flexibility, as it allows specifications of diverse network performance indicators and can model various types of disruption scenarios. Two specific models considering network connectivity and route redundancy are expounded and solved using a customized Benders decomposition method. Case studies involving the Sioux Falls and Winnipeg networks demonstrate the effectiveness and features of the models. Results show that increasing the number of disrupted areas has a diminishing marginal effect on network performance. Moreover, shared critical areas that consistently constitute critical area combinations across various multiple area-covering disruption scenarios warrant targeted protection, as their disruption can increase the risk of extreme combinatorial failure scenarios.

交通网络中的多区域覆盖中断是指涉及多个区域同时失效或关闭的事件（例如，洪水），其影响可能比链路或节点中断更广泛，其影响不仅仅是单个区域故障的叠加。本研究解决了分析此类中断的挑战，包括处理其发生位置和影响范围的随机性，以及处理多种中断场景的组合复杂性。特别是，基于观察到的中断区域、链路、路径、起点-目的地（OD）对和整个网络之间的分层状态依赖关系，我们提出了一个漏洞分析模型，该模型避免了对所有潜在中断场景进行暴力枚举的需要。在方法上，与广泛采用的多链路中断双级规划模型相比，该模型直接表述为单级混合整数线性规划，由于模型结构紧凑，具有更好的计算可追溯性。该模型还显示出显著的灵活性，因为它允许多种网络性能指标的规格，并可以模拟各种类型的中断场景。阐述了考虑网络连通性和路由冗余的两种具体模型，并采用定制的Benders分解方法进行求解。涉及苏福尔斯和温尼伯网络的案例研究证明了模型的有效性和特点。结果表明，干扰区域数量的增加对网络性能的边际效应逐渐减小。此外，共享的关键区域在不同的多区域覆盖的中断场景中始终构成关键区域组合，需要有针对性的保护，因为它们的中断会增加极端组合故障场景的风险。

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引用次数: 0

Towards Web3- and metaverse-enabled decentralisation of electric vehicle battery closed-loop supply chains: insights from advanced text mining techniques 面向Web3和metaverse的电动汽车电池闭环供应链的去中心化：来自高级文本挖掘技术的见解

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-12-10 DOI: 10.1016/j.tre.2025.104583

Quang Huy Duong , Carlos F.A. Arranz , Mao Xu , Li Zhou , Wenxian Sun

The rapid transition to electric vehicles has intensified challenges in electric vehicle battery (EVB) closed-loop supply chains (CLSC), particularly regarding material traceability, supply chain transparency, and recycling efficiency. While decentralised technologies, particularly Web3 and Metaverse, offer promising solutions, their integration into EVB CLSC remains fragmented and insufficiently examined. We introduce an Operational Decentralisation Framework enabling a systematic analysis of centralised operations and a critical evaluation of decentralised alternatives as transformational forces. By adopting a holistic perspective, the framework equips firms with strategic guidance for transitioning from centralised structures to decentralised ecosystems. We analyse 588 academic articles and 1,168 industry documents through two advanced text mining techniques – Dynamic Latent Dirichlet Allocation and Burst Detection. Web3 and metaverse can potentially reconfigure the design, manufacturing, end-of-life diagnostics, procurement, waste management, load balancing, capacity planning, inventory management and service operations of two key areas: (1) EVB CLSC operations and (2) EVB circular energy/grid operations. We also found that while blockchain and digital twins show established applications, Web3 and Metaverse applications face significant barriers, including scalability, technology complexity, and expertise gaps, despite their great potentials. Therefore, we propose four visionary models integrating Web3, Metaverse, and AI technologies that have the potential to overcome existing barriers and enable transformative decentralisation. Extending the TOE framework, the study contributes to the theory by developing an integrated framework for evaluating decentralised technology adoption in EVB CLSCs. For practitioners, we provide actionable insights and pathways for technology implementation across different CLSC stages and guidance for addressing key adoption barriers.

向电动汽车的快速过渡加剧了电动汽车电池闭环供应链（CLSC）的挑战，特别是在材料可追溯性、供应链透明度和回收效率方面。虽然去中心化技术，特别是Web3和Metaverse，提供了很有前途的解决方案，但它们与EVB CLSC的整合仍然是碎片化的，而且没有得到充分的研究。我们引入了一个操作分散框架，能够对集中操作进行系统分析，并对作为变革力量的分散替代方案进行批判性评估。通过采用整体视角，该框架为企业从集中式结构向分散式生态系统过渡提供了战略指导。我们通过两种先进的文本挖掘技术——动态潜在狄利克雷分配和突发检测，分析了588篇学术文章和1168份行业文件。Web3和metaverse可以重新配置两个关键领域的设计、制造、寿命终止诊断、采购、废物管理、负载平衡、容量规划、库存管理和服务运营：(1)EVB CLSC运营和(2)EVB循环能源/电网运营。我们还发现，虽然区块链和数字双胞胎显示了已建立的应用程序，但Web3和元宇宙应用程序面临重大障碍，包括可扩展性、技术复杂性和专业知识差距，尽管它们具有巨大的潜力。因此，我们提出了四个有远见的模型，集成了Web3、Metaverse和人工智能技术，这些技术有可能克服现有的障碍，实现变革性的去中心化。该研究扩展了TOE框架，通过开发一个评估EVB CLSCs采用分散技术的综合框架，为该理论做出了贡献。对于从业者，我们为跨不同CLSC阶段的技术实现提供可操作的见解和途径，并为解决关键的采用障碍提供指导。

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引用次数: 0

Classification of the freight trip purpose of heavy trucks using trajectory data and waybill data 利用轨道数据和运单数据对重型卡车的货运目的进行分类

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-12-08 DOI: 10.1016/j.tre.2025.104584

Zhiwei Yin , Bin Jia , Xiao-Yong Yan , Yitao Yang , Hao Ji , Ziyou Gao

Heavy trucks are pivotal to large-scale freight logistics, but their operations generate substantial negative externalities, such as increased accident risks and inefficient resource use. A fundamental yet unresolved challenge in characterizing heavy truck trip patterns is the comprehensive classification of freight trip purposes through the analysis of extensive freight-related data. Overcoming this challenge is essential for enhancing safety outcomes and advancing freight system optimization. Previous studies have primarily focused on three trip types: loading, unloading, and returning to base. However, a fourth type, termed unloading-loading, where partial or full unloading is followed by reloading at the same stop, has yet to be considered despite its fundamental importance in characterizing heavy truck trip patterns. To bridge this gap, we begin by classifying freight trip purposes into these four types according to whether a truck carries commodities across two consecutive trips. We then propose a rule-based model to identify freight origins, destinations and trip purposes from large-scale freight data. Recognizing limitations in waybill data, we supplement this approach with a machine learning model. Finally, we extract heavy truck trip activity chains and reveal their underlying diversity and heterogeneity. Our results have wide applications, such as the analysis of heavy truck freight transportation efficiency and the development of a freight trip distribution model.

重型卡车是大规模货运物流的关键，但它们的运行产生了大量的负面外部性，例如事故风险增加和资源利用效率低下。描述重型卡车出行模式的一个基本但尚未解决的挑战是，通过分析大量与货运有关的数据，对货运出行目的进行全面分类。克服这一挑战对于提高安全成果和推进货运系统优化至关重要。以前的研究主要集中在三种行程类型：装载、卸载和返回基地。然而，第四种类型，称为卸载-装载，部分或全部卸载后，在同一站重新装载，尽管它在表征重型卡车行程模式方面具有根本重要性，但尚未考虑。为了弥补这一差距，我们首先根据卡车是否在连续两次旅行中运载商品，将货运旅行目的分为这四种类型。然后，我们提出了一个基于规则的模型，从大规模货运数据中识别货运来源、目的地和旅行目的。认识到运单数据的局限性，我们用机器学习模型补充了这种方法。最后，我们提取了重型卡车出行活动链，揭示了其潜在的多样性和异质性。本文的研究成果在重卡货运效率分析、货运行程分布模型的建立等方面具有广泛的应用价值。

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引用次数: 0