Transportation Research Part E-Logistics and Transportation Review最新文献_第4页

Supply chain Holdings: The “Fire Extinguisher” or the “Fuel Booster” for supply chain Risks? 供应链控股：供应链风险的“灭火器”还是“助推器”？

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-02-02 DOI: 10.1016/j.tre.2026.104703

Duo Wang, Yunge Hu, Yanxi Li

Based on relational theory, supply chain shareholding, as a novel feature of supply chains, has the potential to strengthen collaborative ties between upstream and downstream enterprises, effectively mitigating supply chain risks and acting as a “fire extinguisher.” Conversely, it may also intensify interdependencies among firms, making risk transmission within the supply network more likely, thereby functioning as a “fuel booster” for supply chain risks. This study reveals that supply chain holdings play a pivotal “fire extinguisher” role in corporate supply chain risk management, with such effects primarily driven by customer holdings. Specifically, supply chain holdings operate through three principal mechanisms: information transmission facilitation, business stability enhancement, and capital provision within supply chain networks. Heterogeneity analysis further demonstrates that the risk-alleviating effects are particularly pronounced under conditions of substantial supply chain information frictions, elevated external environmental risks, heightened financing constraints, diminished external bargaining power, or weakened shareholder control power. Moreover, the risk-mitigating effect of supply chain holdings persists even under unforeseen risk scenarios. This research not only expands the understanding of the economic consequences of supply chain holding from the perspective of supply chain risk management but also provides an important theoretical foundation for enterprises to effectively prevent supply chain risks and achieve high-quality development.

基于关系理论，供应链股份制作为供应链的一种新特征，具有加强上下游企业协作联系的潜力，可以有效降低供应链风险，起到“灭火器”的作用。相反，它也可能加强企业之间的相互依赖，使风险更有可能在供应网络内传递，从而成为供应链风险的“燃料助推器”。本研究发现，供应链持有量在企业供应链风险管理中起着关键的“灭火器”作用，而这种作用主要是由客户持有量驱动的。具体而言，供应链控股通过三种主要机制运作：促进信息传递、增强业务稳定性和在供应链网络内提供资本。异质性分析进一步表明，在供应链信息摩擦严重、外部环境风险升高、融资约束加剧、外部议价能力减弱或股东控制权减弱的情况下，风险缓解效果尤为显著。此外，即使在不可预见的风险情景下，供应链持有的风险缓解效果仍然存在。本研究不仅从供应链风险管理的角度拓展了对供应链控股经济后果的认识，也为企业有效防范供应链风险，实现高质量发展提供了重要的理论基础。

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引用次数: 0

The logistics vehicle charging station location selection and routing problem with partial recharging and shared fleets 部分充电和共享车队的物流车辆充电站选址与路径问题

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-02-02 DOI: 10.1016/j.tre.2026.104723

Yong Wang , Shiqi Zhang , Jing Liu , Yuanhan Wei , Haizhong Wang

Growing global concern over environmental protection and climate change has led governments worldwide to promote electric vehicles to support carbon neutrality goals. However, limited charging infrastructure, particularly for urban logistics, remains a major barrier to the adoption of electric vehicles for delivery services. This study examines the logistics vehicle charging station location selection and routing problem with partial recharging and shared fleets. An electric vehicle charging model and a nonlinear energy consumption model are formulated to better represent real-world energy use and charging behavior. A bi-objective optimization model is proposed to minimize total operating costs and the required number of vehicles. To solve the model, a hybrid algorithm combining 3D k-means clustering and an improved multi-objective particle swarm optimization (IMOPSO) is developed. The 3D k-means clustering groups spatiotemporal customer data to support periodic resource allocation. The IMOPSO incorporates an enhanced update mechanism and elite selection to improve solution quality and convergence speed. In addition, a resource sharing strategy and a charging station insertion method are applied to further optimize vehicle deployment and station selection. The performance of IMOPSO is evaluated against the CPLEX solver, an improved non-dominated sorting genetic algorithm II, a flexible variable neighborhood search algorithm, and a multi-objective genetic algorithm with simulated annealing. A real-world case study in Chongqing City, China, assesses the proposed approach under sensitivity analysis of model parameters, five recharging levels, multiple resource sharing scenarios, and different collaboration modes. The results indicate that the proposed method supports efficient planning of urban delivery systems and charging infrastructure, contributing to a greener and more cost-effective logistics network.

全球对环境保护和气候变化的日益关注，促使世界各国政府推广电动汽车，以支持碳中和目标。然而，有限的充电基础设施，特别是城市物流，仍然是采用电动汽车交付服务的主要障碍。本文研究了部分充电站和共享车辆的物流车辆充电站选址与路径问题。为了更好地反映现实世界的能源使用和充电行为，建立了电动汽车充电模型和非线性能耗模型。提出了一种以总运行成本和所需车辆数量最小为目标的双目标优化模型。为了求解该模型，提出了一种结合三维k均值聚类和改进多目标粒子群优化（IMOPSO）的混合算法。3D k-means聚类对客户的时空数据进行分组，以支持周期性的资源分配。IMOPSO集成了增强的更新机制和精英选择，以提高解的质量和收敛速度。此外，采用资源共享策略和充电站插入方法，进一步优化车辆部署和充电站选择。针对CPLEX解算器、改进的非支配排序遗传算法II、柔性可变邻域搜索算法和模拟退火多目标遗传算法对IMOPSO的性能进行了评价。以重庆市为例，在模型参数敏感性分析、五种充电水平、多种资源共享场景和不同协作模式下，对该方法进行了评估。结果表明，该方法支持城市运输系统和充电基础设施的有效规划，有助于建立更绿色、更具成本效益的物流网络。

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引用次数: 0

PortMiner: Unsupervised data mining for functional areas extraction in port areas PortMiner：用于港口区域功能区域提取的无监督数据挖掘

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-02-02 DOI: 10.1016/j.tre.2026.104715

Huimin Qiang , Wenlong Niu , Xiaodong Peng , Huanhuan Li , Zaili Yang

Accurate extraction of functional areas in port waters is essential for enhancing port operational oversight, optimizing vessel scheduling, and supporting maritime safety. However, existing approaches often rely on supervised learning, extensive parameter tuning, and labeled datasets, limiting their scalability, adaptability, and operational efficiency. To address these gaps, this study proposes PortMiner, a novel unsupervised data mining framework that systematically extracts functional areas from raw vessel trajectory data without requiring manual annotations. The framework introduces a Spatio-Temporal Adaptive Sliding Windows (STASW) method to detect stop behaviors dynamically, using self-adaptive parameters derived directly from the data. Trajectories are first encoded into geohash-based sequential grids, enabling efficient detection of stop and port inbound/outbound behaviors. Functional zones such as berths, anchorages, and navigational channels are then delineated through multi-level spatial aggregation and connectivity-based clustering. Experimental results on benchmark datasets show that STASW achieves 98.83% accuracy, outperforming state-of-the-art deep learning methods, while significantly reducing computational time and cost. Validation against official nautical charts confirms PortMiner’s high fidelity in identifying port-functional structures. The extracted results are also made publicly accessible via an interactive platform (https://portminer.netlify.app/), offering practical insights for intelligent port operation and maritime logistics planning.

准确提取港口水域功能区，对加强港口运营监管、优化船舶调度、保障海上安全具有重要意义。然而，现有的方法通常依赖于监督学习、广泛的参数调优和标记数据集，限制了它们的可扩展性、适应性和操作效率。为了解决这些问题，本研究提出了PortMiner，这是一种新的无监督数据挖掘框架，可以系统地从原始船舶轨迹数据中提取功能区域，而无需手动注释。该框架引入了一种时空自适应滑动窗口（STASW）方法，使用直接从数据中获得的自适应参数来动态检测停车行为。轨迹首先被编码到基于geohash的顺序网格中，从而能够有效地检测停止和端口入站/出站行为。然后通过多层次的空间聚集和基于连通性的聚类来划定泊位、锚地和航道等功能区。在基准数据集上的实验结果表明，STASW的准确率达到98.83%，优于当前最先进的深度学习方法，同时显著减少了计算时间和成本。对官方海图的验证证实了PortMiner在识别港口功能结构方面的高保真度。提取的结果也可通过互动平台（https://portminer.netlify.app/）公开访问，为智能港口运营和海上物流规划提供实用见解。

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引用次数: 0

Balancing flex and non-flex labor to reliably meet on-demand capacity 平衡柔性和非柔性劳动力，可靠地满足按需容量

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-02-02 DOI: 10.1016/j.tre.2026.104696

Ramon Auad, Thomas Fillebeen, Roman Levkin, Arkajit Rakshit, Martin Savelsbergh

The 21st century workforce is increasingly characterized by more flexible labor models, particularly in e-commerce and supply chain operations. While previous research has focused mostly on last-mile, on-the-road settings, we focus on under-the-roof (UTR) environments, which present unique challenges due to their complex, varied tasks requiring training and experience. Our study addresses the need to better understand how a blended UTR workforce balances factors like structural efficiency and labor flexibility in complex logistics management. We present an optimization framework for determining an effective workforce composition of flexible and non-flexible associates in UTR environments. We validate insights from the optimization framework through an empirical study that increased flexible staffing at Amazon delivery stations. Our analysis includes measuring differences in productivity learning curves and examining impact on efficiency and the associate experience. Key findings reveal that while flexible associates take longer to achieve full proficiency, especially for complex tasks, these effects diminish over time. Importantly, a blended workforce improves structural staffing efficiency and makes it easier to accommodate demand shocks. We estimate that the upper bound of the efficiency improvement to be around 4%. Our research highlights the benefits of strategic workforce planning in the face of increasing demand volatility and a need for operational agility.

21世纪的劳动力日益以更加灵活的劳动模式为特征，特别是在电子商务和供应链运营方面。虽然之前的研究主要集中在最后一英里的道路上，但我们关注的是室内（UTR）环境，由于其复杂多样的任务需要培训和经验，因此面临着独特的挑战。我们的研究解决了更好地理解混合UTR劳动力在复杂物流管理中如何平衡结构效率和劳动力灵活性等因素的需求。我们提出了一个优化框架，以确定在UTR环境中灵活和非灵活的合作伙伴的有效劳动力组成。我们通过一项实证研究验证了优化框架的见解，该研究增加了亚马逊配送站的灵活人员配置。我们的分析包括测量生产率学习曲线的差异，并检查对效率和员工经验的影响。主要研究结果显示，虽然灵活的员工需要更长的时间才能完全精通，尤其是在复杂的任务上，但这些影响会随着时间的推移而减弱。重要的是，混合劳动力提高了结构性人员配置效率，使适应需求冲击变得更容易。我们估计效率提高的上限约为4%。我们的研究强调了在面对日益增加的需求波动和对操作敏捷性的需求时，战略性劳动力规划的好处。

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引用次数: 0

Integrated optimization of berth allocation and green energy bunkering for vessels 船舶泊位分配与绿色能源加注集成优化

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-02-02 DOI: 10.1016/j.tre.2026.104694

Tingsong Wang , Yuhang Zhou , Zheng Xing

Optimizing port operational efficiency is essential for sustainable maritime logistics. However, traditional methods that address berth allocation or bunkering scheduling separately often produce suboptimal results due to their interdependencies, leading to low port turnaround efficiency. To address this, this paper proposes an integrated problem that jointly considers berth allocation, bunkering mode selection, and bunkering scheduling. The problem is formulated as a mixed-integer programming (MIP) model to minimize system costs, including vessel delay, berth deviation, and bunkering vessel operating costs under practical constraints. Then, an enhanced adaptive large neighborhood search (ALNS) algorithm with specialized operators and perturbation mechanisms is developed to solve it. Computational experiments demonstrate that the proposed algorithm performs well, and the model significantly reduces total costs compared with the two-step solution approach, especially under elevated port operational loads. Sensitivity analyses reveal how the numbers of berths and bunkering vessels jointly influence overall performance, offering practical insights for improving operational coordination and promoting sustainable port management.

优化港口运营效率对可持续的海上物流至关重要。然而，传统的泊位分配和加油调度方法由于相互依赖，往往产生次优结果，导致港口周转效率较低。针对这一问题，本文提出了一个综合考虑泊位分配、加油方式选择和加油调度的综合问题。该问题被表述为一个混合整数规划（MIP）模型，以最小化系统成本，包括实际约束下的船舶延误、泊位偏差和加油船运营成本。在此基础上，提出了一种带有特殊算子和微扰机制的增强自适应大邻域搜索（ALNS）算法。计算实验表明，该算法性能良好，与两步求解方法相比，该模型显著降低了总成本，特别是在港口作业负荷升高的情况下。敏感性分析揭示了泊位和加油船的数量如何共同影响整体绩效，为改善运营协调和促进可持续港口管理提供了实际见解。

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引用次数: 0

Enabling the multi-LR ability of drones in the multi-visit truck-drone routing problem with pickup and delivery 在多访问卡车-无人机取货和送货路线问题中实现无人机的多lr能力

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-31 DOI: 10.1016/j.tre.2026.104678

Sepehr Pasha, S.Mehdi Sajadifar

The use of drones alongside trucks for parcel delivery has received considerable research attention, further stimulated by advancements in drone capacity and range that enhance operational viability relative to traditional methods. In this paper, we address a variant of the combined truck-drone routing problem, entailing multiple trucks collaborating with drones to meet the pickup and delivery demands of customers. In the proposed problem, drone energy consumption depends on the carried load; drones may serve multiple customers per flight, and each truck can launch and retrieve its drone multiple times at each customer node (multi-LR) to enhance overall utilization. We propose a mixed-integer linear programming model to minimize total cost, enhanced with problem-specific cuts, which are demonstrated through extensive computational experiments to effectively reduce runtime. The model includes flexible features that allow it to handle diverse operational constraints, such as restrictions on the number of flights performed and high-traffic areas. Given the complexity of the model, we develop an adapted algorithm from the literature, incorporating significant modifications along with a new acceleration strategy. The approach combines a maximum payload method in the first stage with an improved simulated annealing algorithm using problem-specific neighborhood operators in the second stage. Although our findings show that the multi-LR feature increases the number of flights performed, both the model and the adapted algorithm demonstrate its cost efficiency, achieving average transportation cost reductions of 14.51% compared to the system without multi-LR and 45.62% compared to the traditional truck-only system.

与卡车一起使用无人机进行包裹递送已经受到了相当多的研究关注，无人机容量和范围的进步进一步刺激了相对于传统方法的操作可行性。在本文中，我们解决了卡车-无人机联合路线问题的一个变体，需要多辆卡车与无人机合作来满足客户的取货和交付需求。在本文提出的问题中，无人机的能耗取决于所携带的载荷；无人机每次飞行可以服务多个客户，每辆卡车可以在每个客户节点（multi-LR）多次发射和取回无人机，以提高整体利用率。我们提出了一种混合整数线性规划模型，以最小化总成本，并通过大量的计算实验证明了该模型可以有效地减少运行时间。该模型包括灵活的功能，使其能够处理各种操作约束，例如对执行的航班数量和高流量区域的限制。考虑到模型的复杂性，我们从文献中开发了一种自适应算法，并结合了重大修改以及新的加速策略。该方法结合了第一阶段的最大有效载荷方法和第二阶段使用特定问题邻域算子的改进模拟退火算法。虽然我们的研究结果表明，多重lr特征增加了执行的航班数量，但模型和适应的算法都证明了其成本效率，与没有多重lr的系统相比，平均运输成本降低了14.51%，与传统的卡车系统相比，平均运输成本降低了45.62%。

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引用次数: 0

Resilient service of shipping alliance under disruption risk 中断风险下航运联盟弹性服务研究

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-31 DOI: 10.1016/j.tre.2026.104713

Baozhuang Niu , Jianhua Zhang , Fengfeng Xie , Zhipeng Dai , Xiaomeng Guo

The shipping industry has increasingly faced transportation disruptions due to geopolitical tensions and regional shocks. In response, ocean shipping (OS) carriers have adopted resilience enhancement strategies to maintain service availability and operational continuity. While such strategies ensure carriers’ ability to sustain service provision during disruptions, they may also alter competitive dynamics within shipping alliances and weaken incentives for cooperation. This study develops an incentive-based model with two asymmetric OS carriers to examine the interplay among resilience enhancement, disruption risk, logistics service competition, and shipping alliance. We find that an inferior OS carrier’s resilience enhancement strategy may benefit (or surprisingly harm) itself when the shipping alliance’s dominant carrier cannot (can) effectively enhance the alliance service level to expand the market. Even though the inferior OS carrier’s resilience enhancement strategy may increase its own profitability, we reveal that the dominant carrier’s profitability can be impaired, hampering its incentive for alliance-based cooperation. Our work elucidates the role of resilient shipping service under an uncertain and co-opetitive environment.

由于地缘政治紧张局势和地区冲击，航运业越来越多地面临运输中断。为此，远洋运输（OS）承运人采取了弹性增强策略来保持服务可用性和运营连续性。虽然这种策略确保了承运人在中断期间维持服务供应的能力，但它们也可能改变航运联盟内部的竞争动态，削弱合作的动力。本研究以两家非对称营运商为对象，建立基于激励的模型，探讨弹性增强、中断风险、物流服务竞争与航运联盟之间的相互作用。我们发现，当航运联盟的优势承运人不能（或不能）有效地提高联盟服务水平以扩大市场时，劣势运营商的弹性增强策略可能会使其自身受益（或意外损害）。尽管劣势运营商的弹性增强策略可能会增加其自身的盈利能力，但我们发现优势运营商的盈利能力可能会受到损害，从而阻碍其基于联盟的合作动机。我们的研究阐明了弹性航运服务在不确定和合作竞争环境下的作用。

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引用次数: 0

Balancing coopetition in innovation-driven circular business models: the interplay of environmental welfare and competitive advantages 在创新驱动的循环商业模式中平衡合作：环境福利和竞争优势的相互作用

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-30 DOI: 10.1016/j.tre.2026.104721

Mohammad Ali Hassanabadi, S.Ali Torabi

Coopetitive and innovation-driven circular business models (CBMs) are increasingly being proposed to address growing economic and environmental challenges. However, many firms remain hesitant to embrace coopetition, and the adoption of coopetitive models across industries remains limited. This research, as the first attempt to provide a coopetitive and innovation-driven mathematical game-theoretic model in the context of CBMs, explores the potential for environmentally and economically viable innovations within CBMs and analyzes the strategic interactions between coopetitive firms under two distinct power structures. We investigate the conditions under which firms are willing to adopt a coopetition strategy and seek to answer the long-struggling question in the literature regarding the intensity of coopetition between rival firms. We also assess the environmental welfare outcomes of the model and introduce two distinct governmental interventions, each designed to achieve specific objectives. We further relax the power imbalance assumption and conduct a coopetition-based bargaining game between rivals. Our main findings demonstrate that (i) the right choice of power structure not only boosts innovation and environmental welfare within CBMs, it results in higher intensity of coopetition and willingness to collaborate with rivals; (ii) while the proposed supportive mechanisms can encourage firms to cooperate and enhance environmental welfare, they may accelerate the loss of firms’ competitive advantage and CBMs’ financial viability; and (iii) the right choice of supportive mechanism and assigned subsidies can reduce government’s financial burden and strengthen firms’ competitive advantage and environmental welfare. Finally, several managerial and policy implications are derived from the analytical and numerical analyses.

竞争和创新驱动的循环商业模式（CBMs）被越来越多地提出，以应对日益严峻的经济和环境挑战。然而，许多公司仍然对接受合作犹豫不决，跨行业采用合作模式仍然有限。本研究首次尝试在信任机制的背景下提供一个竞争和创新驱动的数学博弈论模型，探讨了信任机制中环境和经济上可行的创新潜力，并分析了两种不同权力结构下竞争企业之间的战略互动。我们调查了企业愿意采取合作战略的条件，并试图回答文献中关于竞争对手之间合作强度的长期困扰的问题。我们还评估了该模型的环境福利结果，并介绍了两种不同的政府干预措施，每种干预措施都旨在实现特定的目标。我们进一步放宽权力不平衡假设，在竞争对手之间进行基于合作的议价博弈。我们的主要研究结果表明：(1)正确的权力结构选择不仅促进了信任措施内部的创新和环境福利，而且导致了更高的合作强度和与竞争对手的合作意愿；(2)虽然建议的支持机制可以鼓励企业合作并提高环境福利，但它们可能加速企业竞争优势和信任措施财务可行性的丧失；(3)正确选择支持机制和分配补贴可以减轻政府财政负担，增强企业的竞争优势和环境福利。最后，从分析和数值分析中得出若干管理和政策影响。

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引用次数: 0

Digital twin-based dynamic co-scheduling with AGV energy management in sea-rail intermodal automated container terminals 基于数字孪生的海铁联运自动化集装箱码头AGV能量管理动态协同调度

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-28 DOI: 10.1016/j.tre.2026.104707

Jiaqi Li , Daofang Chang , Furong Wen , Ilkyeong Moon

To fully leverage the advantages of sea-rail intermodal transport, the automation upgrade of the railway center station (RCS) is essential for enabling seamless connectivity between the RCS and the terminal via automated guided vehicles (AGVs). This transformation introduces complex scheduling challenges for sea-rail intermodal automated container terminals (SRIACTs), including multi-directional container flows, coordination among diverse equipment, and AGV charging requirements with battery management. To address these challenges, this paper investigates the multi-equipment collaborative scheduling problem in SRIACTs with consideration of AGV charging. A mixed-integer programming model is formulated with sequencing, timing, and energy constraints, aiming to jointly minimize makespan and total charging time. To improve computational efficiency in large-scale cases, an improved genetic algorithm based on a decomposition-iteration framework is developed according to problem-specific features. Furthermore, to address operational uncertainties, a digital twin-based hybrid rescheduling framework is extended to enable real-time monitoring, disturbance detection, and rapid response to AGV status and battery levels, thereby enhancing system resilience and scheduling flexibility. Extensive numerical experiments are conducted to validate the effectiveness of the proposed algorithm and rescheduling framework. On this basis, comparative analyses are performed on bi-objective formulations and the flexible charging strategy. Additionally, sensitivity analyses examine the impacts of key factors, including objective weights, charging thresholds, rescheduling thresholds, and the number and layout of charging facilities. The findings provide valuable insights for terminal operators in formulating integrated scheduling strategies, optimizing AGV charging plans, and scientifically deploying charging infrastructure during the RCS automation process, thereby promoting sustainable and intelligent terminal operations.

为了充分利用海铁联运的优势，铁路中心站（RCS）的自动化升级对于通过自动引导车辆（agv）实现RCS与码头之间的无缝连接至关重要。这种转变为海铁联运自动化集装箱码头（SRIACTs）带来了复杂的调度挑战，包括多向集装箱流动、不同设备之间的协调以及AGV充电要求和电池管理。为了解决这些问题，本文研究了考虑AGV充电的SRIACTs多设备协同调度问题。以最大完工时间和总充电时间共同最小化为目标，建立了排序、时间和能量约束的混合整数规划模型。为了提高大规模情况下的计算效率，根据具体问题的特点，提出了一种基于分解迭代框架的改进遗传算法。此外，为了解决操作的不确定性，扩展了基于数字孪生的混合重调度框架，以实现实时监控、干扰检测和对AGV状态和电池水平的快速响应，从而增强了系统的弹性和调度灵活性。大量的数值实验验证了所提算法和重调度框架的有效性。在此基础上，对双目标配方和柔性收费策略进行了对比分析。此外，敏感性分析考察了关键因素的影响，包括客观权重、充电阈值、重新调度阈值以及充电设施的数量和布局。研究结果可为终端运营商在RCS自动化过程中制定综合调度策略、优化AGV充电计划、科学部署充电基础设施提供有价值的见解，从而促进终端的可持续和智能化运营。

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引用次数: 0

A new robust capacitated hub interdiction problem under ambiguous demand and its benders decomposition 一种新的模糊需求下鲁棒容量轮毂拦截问题及其弯曲点分解

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-28 DOI: 10.1016/j.tre.2026.104716

Meiyu Liu , Shanshan Gao , Naiqi Liu

In this paper, we study the capacitated hub interdiction problem on a multiple allocation hub-and-spoke network and formulate it as a bi-level optimization model. The rational attacker in the upper-level model interdicts a subset of hubs and maximizes the damage to the defender in the lower-level model. Given that hubs operate with limited capacity, an interdiction would lead to unfulfilled demand, thereby incurring additional penalty costs. In reality, however, demand in urban logistics transportation tends to exhibit significant variation due to its inherent non-stationarity and spatial correlation. Therefore, we model demand uncertainty to make robust hub location and routing decisions. Methodologically, a sub-Gaussian-based ambiguity set is constructed using statistical methods, which involves the family of all probability distributions consistent with known mean, variance and support information about demand. We develop a distributionally robust optimization model for our capacitated hub interdiction problem under the constructed ambiguity set, and then reformulate it as a mixed integer linear programming model, which facilitates us to design an accelerated Benders decomposition algorithm. In particular, we derive robust solutions with both a priori and a posteriori probability guarantees. Case study on the well-known CAB dataset demonstrates the advantages of our optimization method in balancing robustness and conservatism. Furthermore, computational results on the TR dataset illustrate that our proposed algorithm outperforms the CPLEX solver.

本文研究了多分配轮辐网络上的有容枢纽阻塞问题，并将其表述为双层优化模型。上层模型中的理性攻击者拦截集线器的一个子集，并使下层模型中的防御者的损失最大化。鉴于枢纽的运营能力有限，封锁将导致需求未得到满足，从而招致额外的惩罚成本。但在现实中，由于其固有的非平稳性和空间相关性，城市物流运输的需求往往表现出显著的变化。因此，我们对需求不确定性进行建模，以做出稳健的集线器位置和路由决策。在方法上，使用统计方法构建了基于亚高斯的模糊集，该模糊集涉及与已知的均值、方差和需求支持信息一致的所有概率分布族。在构造的模糊集下，建立了有容轮毂阻塞问题的分布鲁棒优化模型，并将其转化为混合整数线性规划模型，从而便于设计一种加速的Benders分解算法。特别地，我们得到了具有先验和后验概率保证的鲁棒解。以知名的CAB数据集为例，验证了该优化方法在平衡稳健性和保守性方面的优势。此外，在TR数据集上的计算结果表明，我们提出的算法优于CPLEX求解器。

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引用次数: 0