Transportation Research Part E-Logistics and Transportation Review最新文献_第7页

Dynamic truck-drone cooperative delivery of emergency supplies considering secondary disasters 考虑次生灾害的卡车-无人机动态协同运送应急物资

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-11-30 DOI: 10.1016/j.tre.2025.104543

Yong Shi , Keyi Zhang , Jian Zhang , Miao Chen , Junhao Yang , Haixiang Guo

There has been a high incidence of sudden-onset natural disasters worldwide in the recent years. The dispatch of emergency supplies is a key aspect of post disaster relief. Many natural disasters induce secondary disasters and other damages. During rescue operations, roads are often found to be damaged and impassable; nonetheless, secondary disasters often cause the demand for emergency supplies to evolve dynamically. Previous studies have mostly focused on static vehicle-routing problems, which fail to simulate the dynamic changes at the affected sites, realistically. This study considers the dynamic distribution of emergency supplies using a hybrid fleet of trucks and drones. A mixed-integer programming model is constructed by allowing the carrier vehicles to depart from the distribution center multiple times with the dual objectives of minimizing both the road risk and total waiting time for supplies at the affected sites. Because this problem is an NP-hard problem, this study designs a biobjective optimization algorithm that incorporates the nondominated sorting genetic algorithm-II (NSGA-II) and Q-learning (QLNSGA-II). The results of computational experiments show that, for small-scale instances, the solutions of QLNSGA-II are very close to the exact solutions obtained using the ϵ-constraint method. For large-scale instances, the solutions of QLNSGA-II outperform those of the NSGA-II algorithm and the hybrid algorithm of NSGA-II and random neighborhood search in some performance metrics, such as the hypervolume and inverted generational distance. Finally, this paper presents a geological disaster event that occurred in Zigui County, Hubei Province, in China, as a case study to show how the proposed model works. This study offers a practical framework to guide decision-making while scheduling emergency-supply deliveries.

近年来，突发性自然灾害在世界范围内高发。紧急物资的运送是灾后救援的一个重要方面。许多自然灾害都会引发次生灾害和其他损害。在救援行动中，道路经常被破坏，无法通行；然而，次生灾害往往导致对应急物资的需求发生动态变化。以往的研究大多集中在静态车辆路径问题上，无法真实地模拟受影响地点的动态变化。这项研究考虑了使用卡车和无人机混合车队的应急物资的动态分配。通过允许运输车辆多次离开配送中心，以最小化受影响站点的道路风险和总等待时间为双重目标，构建了混合整数规划模型。由于该问题属于np困难问题，本研究设计了一种结合非支配排序遗传算法- ii （NSGA-II）和q -学习（QLNSGA-II）的双目标优化算法。计算实验结果表明，对于小尺度实例，QLNSGA-II的解与ϵ-constraint方法得到的精确解非常接近。对于大规模实例，QLNSGA-II解决方案在一些性能指标上优于NSGA-II算法以及NSGA-II与随机邻域搜索的混合算法，如超大体积和倒代距离。最后，以发生在湖北省秭归县的一起地质灾害事件为例，说明了该模型的有效性。本研究提供了一个实用的框架来指导应急物资交付计划的决策。

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引用次数: 0

Accessorial value-added services in inland river port: Self-operating or outsourcing? 内河港口辅助增值服务：自营还是外包？

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-11-29 DOI: 10.1016/j.tre.2025.104580

Lijun Jiang , Zhi-Chun Li , Xiaowen Fu

This paper addresses the investment decision issues of accessorial value-added services in an inland river port. We present a vertical structural model that considers the interactions among shippers, port operator, government, and outsourcee (if any). Using this model, we analyze the effects of the accessorial value-added services in an inland river port on the stakeholders’ behavior, port profitability and social welfare. We identify the critical conditions that the port operator would like to provide the value-added processing services via self-operating or outsourcing. We also determine the optimal subsidy policy of the government for introducing such services. The results show that: (i) the introduction of value-added processing services leads to a decrease in the price of regular services but an increase in the associated cargo volume; (ii) when potential market size and government subsidy are low, the port operator tends to outsource but not self-operate the processing services; and (iii) the government subsidy plays a critical role in the decision on the operating mode of port processing services, and a reasonable subsidy can achieve a “win-win-win” outcome for the shippers, port operator (including outsourcee, if any), and the society. This paper provides an important and useful methodology for modeling the game behavior among stakeholders and for design and evaluation of port operator’s operational strategies and government’s regulatory policies in the inland river system.

本文研究了内河港口辅助增值服务的投资决策问题。我们提出了一个垂直结构模型，考虑了托运人、港口运营商、政府和外包商（如果有的话）之间的相互作用。利用该模型分析了内河港口辅助增值服务对利益相关者行为、港口盈利能力和社会福利的影响。我们确定港口运营商希望通过自营或外包方式提供增值加工服务的关键条件。我们还确定了政府引入此类服务的最优补贴政策。结果表明：(1)加价加工服务的引入导致常规服务价格下降，但相关货运量增加；（ii）当潜在市场规模和政府补贴较低时，港口经营者倾向于外包而不是自营加工服务；（三）政府补贴在港口加工服务经营模式的决策中起着至关重要的作用，合理的补贴可以实现托运人、港口经营人（包括外包企业）和社会的“三赢”。本文为内陆河水系中利益相关者博弈行为的建模、港口经营者经营策略的设计和评估以及政府监管政策的制定提供了一种重要而有用的方法。

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引用次数: 0

Dynamic multimodal transport planning with drones for emergency logistics: Mathematical model and heuristic algorithm 基于无人机的应急物流动态多式联运规划：数学模型与启发式算法

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-11-27 DOI: 10.1016/j.tre.2025.104558

Yimeng Zhang , Shuyang Zhu , Kaiyu Pu , Hang Cui , Mi Gan , Xiaobo Liu , Ruixue Ai

Dynamic multimodal transport planning is vital for enhancing flexibility and responsiveness in emergency logistics. We propose a dynamic planning approach that integrates drones into the multimodal system with trains, trucks, and aircraft, introducing dual-role drones that can be transported as cargo and later operate as carriers. A Mixed Integer Programming (MIP) model, optimized via a rolling horizon approach, supports real-time route planning. Given the problem’s complexity, we develop an Adaptive Large Neighborhood Search (ALNS) algorithm with problem-specific operators. The model accounts for mode coordination, routing constraints, and cargo heterogeneity. It dynamically replans routes under disruptions such as road damage, considering mode availability and delivery requirements. Numerical experiments are conducted based on a real disaster scenario. A comparison with an exact method shows improved computational efficiency and solution quality. Further comparisons with a drone-free and static approach highlight gains in service rate and disruption resilience. We also examine the impact of cargo heterogeneity. These results, across instances from 5 to 400 orders, provide practical insights for optimizing drone deployment, transport mode selection, and cargo management in disaster response.

动态多式联运规划对于提高应急物流的灵活性和响应能力至关重要。我们提出了一种动态规划方法，将无人机与火车、卡车和飞机集成到多式联运系统中，引入双重角色无人机，既可以作为货物运输，也可以作为载体运营。混合整数规划（MIP）模型，通过滚动地平线方法优化，支持实时路由规划。考虑到问题的复杂性，我们开发了一种带有问题特定算子的自适应大邻域搜索（ALNS）算法。该模型考虑了模式协调、路由约束和货物异构性。考虑到模式的可用性和交付要求，它在道路损坏等中断情况下动态地重新规划路线。在真实灾害场景下进行了数值实验。与精确方法的比较表明，计算效率和解的质量得到了提高。与无无人机和静态方法的进一步比较突出了服务率和中断恢复能力的提高。我们还研究了货物异质性的影响。这些结果涵盖了从5到400个订单的实例，为优化无人机部署、运输模式选择和灾难响应中的货物管理提供了实用的见解。

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引用次数: 0

A distributionally robust chance constraint model to demand-responsive skip planning problem 需求响应跳跃规划问题的分布鲁棒机会约束模型

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-11-26 DOI: 10.1016/j.tre.2025.104444

Zhiqi Shao , Ze Wang , Michael G H Bell , D. Glenn Geers , Junbin Gao

The increasing complexity of construction and demolition waste management presents significant logistical challenges, particularly in urban environments where skip logistics play a pivotal role. This paper develops a distributionally robust optimization framework to address the intricate task of multi-period scheduling and operational constraints in skip logistics, a domain where existing methods fall short. The proposed model incorporates chance-constrained formulations to explicitly handle travel-time uncertainties while acknowledging broader system variabilities including demand fluctuations and policy restrictions. Beyond theoretical contributions, we address practical implementation challenges including computational scalability and data integration requirements. Using a comprehensive dataset from Sydney, Australia, the framework’s practical applicability is demonstrated through rigorous performance evaluations, showcasing its ability to reduce violation frequencies while maintaining operational efficiency across diverse configurations. The findings not only advance the research in skip logistics optimization but also provide actionable insights for policymakers and practitioners, while suggesting promising extensions toward multi-objective optimization and dynamic replanning capabilities for sustainable and resilient construction and demolition waste management practices.

日益复杂的建筑和拆除废物管理提出了重大的物流挑战，特别是在城市环境中，跳跃物流发挥着关键作用。本文开发了一个分布式鲁棒优化框架，以解决多周期调度和操作约束的复杂任务，这是现有方法的不足之处。所提出的模型包含机会约束公式，以明确处理旅行时间的不确定性，同时承认包括需求波动和政策限制在内的更广泛的系统可变性。除了理论贡献之外，我们还解决了包括计算可扩展性和数据集成要求在内的实际实现挑战。使用来自澳大利亚悉尼的综合数据集，通过严格的性能评估证明了该框架的实用性，展示了其在保持不同配置的操作效率的同时降低违规频率的能力。研究结果不仅推动了箕斗物流优化的研究，而且为决策者和实践者提供了可操作的见解，同时为可持续和弹性的建筑和拆除废物管理实践提供了多目标优化和动态重新规划能力的有希望的扩展。

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引用次数: 0

Understanding agricultural supply chain resilience in developing countries: A Short-Chain framework 理解发展中国家农业供应链弹性：一个短链框架

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-11-26 DOI: 10.1016/j.tre.2025.104564

Minqian Yuan , Haiqing Hu , Meng Xue , Jingyu Li

Given the multiple challenges posed by climate shocks, food security pressures, and systemic disruptions, building resilient agricultural supply chains (ASCs) has become a critical priority. This need is particularly urgent in developing countries, as ASCs in these contexts are typically fragmented and weakly integrated. To address this, we propose a “Short-Chain” framework aimed at advancing differentiated resilience approaches. Drawing on survey data from 627 Chinese ASC firms, we construct two analytical scenarios and evaluate them using machine learning methods. The results indicate that, due to loose connections among the production, processing, and marketing stages, ASCs function as systems composed of several semi-independent sub-chains. These sub-chains exhibit differing resilience requirements, making segment-specific resilience approaches necessary. This study introduces a new perspective for analyzing ASC resilience in developing countries, therefore offers theoretical guidance for managers in designing tailored resilience strategies.

考虑到气候冲击、粮食安全压力和系统性中断带来的多重挑战，建设有韧性的农业供应链已成为一个关键的优先事项。这一需求在发展中国家尤为迫切，因为在这些情况下，ASCs通常是零散的，整合程度较弱。为了解决这个问题，我们提出了一个旨在推进差异化弹性方法的“短链”框架。根据627家中国ASC公司的调查数据，我们构建了两个分析场景，并使用机器学习方法对它们进行了评估。结果表明，由于生产、加工和销售阶段之间的松散联系，ASCs是由几个半独立的子链组成的系统。这些子链表现出不同的弹性需求，使得特定于片段的弹性方法成为必要。本研究为分析发展中国家的ASC弹性提供了一个新的视角，从而为管理者设计针对性的弹性策略提供理论指导。

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引用次数: 0

Blockchain traceability valuation for perishable agricultural products: Balancing economic benefit and social impact 易腐农产品可追溯性评估：平衡经济效益和社会影响

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-11-25 DOI: 10.1016/j.tre.2025.104546

Qing Li , Khaled Hadj-Hamou , Yacine Rekik

The adoption of blockchain-enabled traceability systems in agricultural supply chains offers farmers a means to reduce demand uncertainty. However, downstream retailers gain full visibility into product freshness, enabling selective purchases that may inadvertently increase food waste. This study evaluates the impact of such a traceability system by analyzing agricultural supply chain transactions under two scenarios: with and without blockchain implementation. By comparing order quantities and farmer profits in both cases, we find that blockchain adoption can enhance product sales because the smart contract effect. We also find that blockchain adoption can either amplify the bullwhip effect when circulation time is short or mitigate it when circulation time is long. The interaction between the bullwhip effect and the smart contract effect impacts the farmer’s profit. The farmer achieves higher profits using the blockchain-enabled traceability system if the smart contract effect outweighs the bullwhip effect. Furthermore, adoption costs play a crucial role in determining feasibility. Beyond economic implications, blockchain-enabled traceability systems also influence social outcomes, particularly in reducing food waste. Our analysis reveals four possible outcomes based on economic benefits and social impact: (i) win-win (higher profits and reduced waste), (ii) win-lose (higher profits but increased waste), (iii) lose-win (lower profits but reduced waste), and (iv) lose-lose (lower profits and increased waste). The likelihood of each outcome is strongly dependent on product shelf life—longer shelf life increases the probability of a win-lose scenario, while shorter shelf life raises the likelihood of a lose-win outcome. Win-win and lose-lose scenarios remain the least probable.

在农业供应链中采用区块链可追溯系统为农民提供了一种减少需求不确定性的手段。然而，下游零售商可以充分了解产品的新鲜度，从而实现选择性购买，这可能会无意中增加食物浪费。本研究通过分析有和没有区块链实施两种情况下的农业供应链交易，评估了这种可追溯系统的影响。通过比较两种情况下的订单量和农民利润，我们发现由于智能合约效应，区块链的采用可以提高产品销量。我们还发现，当循环时间较短时，采用区块链可以放大牛鞭效应，而当循环时间较长时，则可以减轻牛鞭效应。牛鞭效应和智能合约效应的相互作用影响农民的利润。如果智能合约效应超过牛鞭效应，农民就可以使用支持区块链的可追溯系统获得更高的利润。此外，采用费用在确定可行性方面起着至关重要的作用。除了经济影响，支持区块链的可追溯系统还会影响社会结果，特别是在减少食物浪费方面。我们的分析揭示了基于经济效益和社会影响的四种可能的结果：(i)双赢（利润更高，浪费减少），（ii）双赢（利润更高，浪费增加），（iii）双赢（利润更低，浪费减少），（iv）双输（利润更低，浪费增加）。每个结果的可能性是强烈依赖于产品货架终身保质期一输一赢的场景的概率增加,而较短的货架寿命提高损己利人的可能性的结果。双赢和双输的情况仍然是最不可能的。

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引用次数: 0

Sustainability in organic and non-organic agricultural supply chain: an integrated planning-pricing model with demand dynamics and hybrid metaheuristic optimization 有机和非有机农业供应链的可持续性：一个具有需求动态和混合元启发式优化的综合规划定价模型

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-11-25 DOI: 10.1016/j.tre.2025.104545

Faraz Salehi , Mehdi A. Kamran , S.M.J. Mirzapour Al-E-Hashem , Hamed Mohammadi

The growing importance of Environmental, Social, and Governance (ESG) concerns in sustainable food systems has increased attention on organic agriculture. As demand for organic products rises, supply chain decisions such as pricing, inventory management, and advertising have become more complex and interdependent. This study presents a multi-objective mathematical model designed to support integrated decision-making within a sustainable supply chain that includes both organic and non-organic agricultural products. The model considers a centralized, forward-moving supply chain structured across three tiers: production centers, distribution centers, and retailers. It incorporates demand dynamics linked to both sales price and advertising, capturing how consumer preferences shift over time and how local advertising influences product substitution during shortages. The model is formulated as a mixed-integer linear programming problem with three main objectives: maximizing total profit, minimizing environmental impact, and enhancing social benefits through healthier consumption. For small problem sizes, an exact epsilon-constraint method is used. For larger cases, we introduce a hybrid metaheuristic called MOPSBBO, which combines Particle Swarm Optimization (PSO) with Biogeography-Based Optimization (BBO). Numerical results validate the model’s performance and highlight key insights. Strategic pricing increases both sales and profitability, while a combination of media and environmental advertising raises demand for organic products. Local advertising also encourages consumers to substitute non-organic products with organic ones during shortages, promoting sustainable choices and improving supply chain outcomes.

环境、社会和治理（ESG）在可持续粮食系统中的重要性日益增加，这增加了人们对有机农业的关注。随着对有机产品需求的增加，诸如定价、库存管理和广告等供应链决策变得更加复杂和相互依赖。本研究提出了一个多目标数学模型，旨在支持包括有机和非有机农产品在内的可持续供应链中的综合决策。该模型考虑了一个集中的、向前发展的供应链，它横跨三个层次：生产中心、配送中心和零售商。它结合了与销售价格和广告相关的需求动态，捕捉了消费者偏好如何随着时间的推移而变化，以及当地广告如何影响短缺期间的产品替代。该模型是一个混合整数线性规划问题，有三个主要目标：总利润最大化，环境影响最小化，通过健康消费提高社会效益。对于小问题，使用精确的约束方法。在更大的情况下，我们引入了一种混合元启发式算法，称为MOPSBBO，它结合了粒子群优化（PSO）和基于生物地理的优化（BBO）。数值结果验证了模型的性能，并突出了关键的见解。策略性定价提高了销售额和盈利能力，而媒体和环保广告的结合提高了对有机产品的需求。当地广告还鼓励消费者在短缺期间用有机产品替代非有机产品，促进可持续选择并改善供应链结果。

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引用次数: 0

Leveraging the passenger and freight spatiotemporal flow to optimize metro passenger-freight mixed transportation: a new mode for urban logistics systems 利用客货时空流优化地铁客货混合运输：城市物流系统新模式

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-11-24 DOI: 10.1016/j.tre.2025.104560

Xiaobing Ding , Jian Gang Jin , Hanchuan Pan , Xuelin Wang , Yingying Hu , Gan Shi

To address the continuously growing urban logistics demand in megacities and alleviate traffic congestion in core urban areas, metro passenger-cargo mixed transportation, as a new transportation mode, shows great application prospects. First, a spatiotemporal-dependent estimation model for the remaining cargo transport capacity of trains was constructed based on the passenger flow across network sections. Second, logistics business outlets were clustered using GIS data and subway network layouts to determine cargo loading/unloading stations. Third, a spatiotemporal freight demand forecasting model was developed using historical OD (Origin-Destination) flow data. Subsequently, with hourly granularity, optimization models for train operation plans were formulated under three modes: passenger-cargo co-compartment, passenger-cargo co-train with separate compartments, and dedicated freight trains, leveraging the estimated remaining cargo capacity and predicted demand along the routes. Finally, an empirical analysis of Shanghai Metro Line 9 and SF Express revealed the following outcomes: the utilization rate of trains’ remaining freight capacity increased by 17.57%, daily revenue for the metro operator rose by 458,350 yuan, SF Express reduced its transportation costs by 229,175 yuan, urban traffic congestion was alleviated, and CO₂ emissions decreased. The research findings can promote the efficient integration of passenger and freight flows using the remaining capacity of metro trains, reduce logistics costs for enterprises, and mitigate urban congestion and environmental pollution.

为满足特大城市不断增长的城市物流需求，缓解核心城区交通拥堵，地铁客货混合运输作为一种新型的运输方式，具有广阔的应用前景。首先，建立了基于路网各段客流的列车剩余货物运输能力时空依赖估计模型；其次，利用GIS数据和地铁网络布局对物流业务网点进行聚集，确定货物装卸站。第三，利用历史OD（始发目的地）流数据建立了货运需求的时空预测模型。随后，以小时为粒度，利用估计的剩余货物运力和预测的沿线需求，建立了客货共车厢、客货分车厢、货运专列三种模式下的列车运行计划优化模型。最后，以上海地铁9号线和顺丰速运为例进行实证分析，结果表明：列车剩余运力利用率提高17.57%，地铁运营商日收益增加458350元，顺丰速运降低运输成本229175元，缓解了城市交通拥堵，减少了二氧化碳排放。研究结果可以促进地铁列车剩余运力的客货流高效整合，降低企业物流成本，缓解城市拥堵和环境污染。

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引用次数: 0

Innovative business model for private charging pile sharing operation and its vehicle-to-grid energy management 私人充电桩共享运营的创新商业模式及其车对网能源管理

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-11-24 DOI: 10.1016/j.tre.2025.104544

Zhaosheng Yao , Xinyue Ren , Wai Kin (Victor) Chan , Fengwei Jia , Hongli Zhu , Yinliang Xu , Qiuwei Wu

The optimization of private charging pile sharing mode operation and the intelligent interaction between electric vehicles and the energy system are crucial. Its social benefits include improving resource utilization and complementing existing charging networks. However, several practical challenges constrain the efficient operation of this innovative business model, namely the private charging pile sharing mode. This paper focuses on the operation of private charging pile sharing mode and its vehicle-to-grid energy management, which encompasses multiple dimensions of the characteristics of innovative business models, the integration of emerging technologies and the complex interactions. Moreover, this paper constructs a multi-objective optimization model that incorporates key elements of uncertain information, decarbonization management, and demand response strategies, and analyzes their potential impacts. Meanwhile, intelligent dispatching and matching mechanisms are used to improve the utilization of private charging resources, balance supply and demand, and effectively manage energy flows. The numerical analysis using real data demonstrates the feasibility and potential of the operational optimization of innovative business models, and verifies the enhancement of multiple economic and environmental gains, such as alleviating the shortage of public charging facilities, reducing charging costs, and improving decarbonization management capabilities.

私人充电桩共享模式运行的优化以及电动汽车与能源系统的智能交互至关重要。它的社会效益包括提高资源利用率和补充现有的收费网络。然而，这种创新的商业模式，即私人充电桩共享模式，其高效运行受到一些现实挑战的制约。本文以私人充电桩共享模式的运行及其车对网能源管理为研究重点，涉及创新商业模式特征、新兴技术融合、复杂互动等多个维度。构建了包含不确定信息、脱碳管理和需求响应策略等关键要素的多目标优化模型，并分析了其潜在影响。同时，通过智能调度与匹配机制，提高私人充电资源利用率，实现供需平衡，有效管理能量流。通过实际数据的数值分析，论证了创新商业模式运营优化的可行性和潜力，验证了缓解公共充电设施短缺、降低充电成本、提高脱碳管理能力等多重经济和环境效益的提升。

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引用次数: 0

A hierarchical decision framework for dynamic operation of mobile charging stations 移动充电站动态运行的分层决策框架

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2025-11-24 DOI: 10.1016/j.tre.2025.104553

Yiming Yan , Qingyun Tian , Ziyuan Sun , Rong Cao , David Z.W. Wang

The growing adoption of electric vehicles (EVs) has led to increasing demand for flexible and responsive charging services in urban areas. To address spatiotemporal imbalance between charging supply and EV demand, this study investigates the real-time operation of mobile charging stations (MCSs), a promising solution that leverages portable chargers to meet spatiotemporally distributed charging demand. We propose a two-layer online decision framework that integrates reinforcement learning (RL) with exact optimization to jointly address upper-level deployment of the MCS and lower-level charging service scheduling decisions. In the upper layer, a deep Q-network (DQN) learns an adaptive dispatching policy to determine the next deployment location of the MCS based on real-time system states. In the lower layer, an exact optimization solver computes the optimal charging schedule by jointly selecting which EVs to charge, assigning them to ports, and determining the service duration at each stop. The proposed framework follows an event-driven paradigm and enables closed-loop coordination between hierarchical decision layers. Numerical experiments on both synthetic and realistic settings validate the proposed framework. In small-scale tests, the RL policy achieves 24.5 % higher cumulative rewards than the strongest greedy baseline, with greater improvements over queue-based, static, and random heuristics. In a realistic case study with 20 candidate facilities and spatiotemporally heterogeneous demand, it improves cumulative rewards by 11.2 % over the strongest baseline under practical operational constraints. The findings are robust to variations in the number of ports, dwell time, and demand scale; moreover, in a multi-MCS setting the RL policy also outperforms the strongest baseline. These results highlight the effectiveness, scalability, and practical value of the proposed hierarchical framework for dynamic EV charging operations.

电动汽车（ev）的日益普及导致城市地区对灵活和响应式充电服务的需求不断增加。为了解决充电供应与电动汽车需求之间的时空不平衡问题，本研究探讨了移动充电站（MCSs）的实时运行，这是一种利用便携式充电器满足时空分布充电需求的有前途的解决方案。我们提出了一个两层在线决策框架，该框架将强化学习（RL）与精确优化相结合，共同解决MCS的上层部署和低层收费服务调度决策。在上层，深度q网络（deep Q-network， DQN）学习自适应调度策略，根据系统实时状态确定MCS的下一个部署位置。在下层，精确优化求解器通过联合选择充电的电动汽车，将其分配到端口，并确定每个站点的服务时间来计算最优充电计划。提出的框架遵循事件驱动的范式，并支持分层决策层之间的闭环协调。在综合和现实环境下的数值实验验证了所提出的框架。在小规模测试中，RL策略获得的累积奖励比最强贪婪基线高24.5%，比基于队列的、静态的和随机的启发式方法有更大的改进。在一个包含20个候选设施和时空异质性需求的现实案例研究中，在实际操作约束下，它比最强基线提高了11.2%的累积回报。研究结果对于港口数量、停留时间和需求规模的变化是稳健的；此外，在多mcs设置中，RL策略也优于最强基线。这些结果突出了所提出的电动汽车动态充电分层框架的有效性、可扩展性和实用价值。

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