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

A p-Robust Location-Allocation model for Resilience-Oriented collaborative emergency response network in urban agglomerations 面向弹性的城市群协同应急响应网络的p鲁棒定位-分配模型

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-21 DOI: 10.1016/j.tre.2026.104698

Laijun Zhao , Weijie Xie , Huiyong Li , Changzhi Wu , Shuo Sun , Pingle Yang , Lixin Zhou

Disasters that can occur unexpectedly pose significant threats to human life, health, and property. When such events take place in urban agglomerations, their impact is likely to become more complex. In the present study, we focus on the emergency facility location-allocation problem and explore regional collaboration strategies to effectively address the challenges posed by urban agglomerations. We develop a collaborative emergency response network design framework and propose a collaborative emergency facility location-allocation model for the problem. Given the intrinsic relationships among emergency operations, the model integrates the planning of facility location, victim evacuation, casualty transfer, and medical supply allocation. Moreover, given the uncertainty in the number of casualties, we employ a p-robust optimization model. The model, which formulates with bi-objectives of cost and resilience, is solved using an augmented ε-constraint method and applied to a case in the demonstration zone of green and integrated ecological development of the Yangtze River Delta. Our simulation results reveal that, compared to the existing territorial priority strategy, the regional emergency collaboration strategy increases network resilience by 19.51% and reduces emergency response time by 1.26 h. In addition, we conduct sensitivity analyses on various parameters and provide managerial insights to improve emergency operations in urban agglomerations.

可能意外发生的灾害对人类的生命、健康和财产构成重大威胁。当这类事件发生在城市群时，其影响可能会变得更加复杂。在本研究中，我们着眼于应急设施的选址问题，探索区域协作策略，以有效应对城市群带来的挑战。针对这一问题，建立了协同应急响应网络设计框架，并提出了协同应急设施配置模型。考虑到应急行动之间的内在联系，该模型集成了设施选址、受害者疏散、伤员转移和医疗物资分配的规划。此外，考虑到伤亡人数的不确定性，我们采用了p-鲁棒优化模型。该模型以成本和弹性为双目标，采用增强型ε约束方法求解，并以长三角绿色生态综合发展示范区为例进行了实例分析。仿真结果表明，与现有的区域优先策略相比，区域应急协同策略使网络弹性提高了19.51%，应急响应时间缩短了1.26 h。此外，我们对各参数进行了敏感性分析，为改善城市群的应急操作提供了管理见解。

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引用次数: 0

Integrating six feeder modes with the metro system: Insights from on-demand and pooled services 与地铁系统集成六种馈线模式：从按需和共享服务的见解

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-20 DOI: 10.1016/j.tre.2025.104659

Linchuan Yang

Understanding travel patterns of feeder modes for metro systems is crucial for addressing first-mile challenges and advancing sustainable urban mobility. Existing research predominantly examines traditional transit modes (e.g., buses) and emerging on-demand transport services (e.g., ride-hailing) separately, with limited comparative analysis between the two. Furthermore, most studies do not distinguish between solo trips and pooled trips, leading to potential misestimation of the impact of each trip type. Drawing on multi-source data from Shenzhen, this study analyzes the access patterns of six feeder modes (i.e., solo ride-hailing, ride-pooling, solo taxis, taxi-pooling, buses, and free-floating bike-sharing) and their integration with the metro system. We employ the eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP) models to evaluate the impacts of these feeder modes on metro ridership, and analyze how on-demand transport services fill gaps in the metro-bus network based on the coverage extension ratio and travel time ratio. Our findings reveal: (1) Solo taxis represent the fastest feeder mode; (2) As access distance increases, the cost advantage of ride-hailing diminishes, while the speed advantage of taxis becomes more pronounced; (3) Ride-pooling contributes to increased metro usage in non-central areas; (4) On-demand transport services can effectively address gaps in the metro-bus network. This study provides policy implications for optimizing transportation resource allocation and enhancing first-mile connectivity for metro systems.

了解地铁系统支线模式的出行模式对于解决第一英里挑战和推进可持续城市交通至关重要。现有的研究主要分别考察了传统的交通方式（如公共汽车）和新兴的按需交通服务（如叫车服务），两者之间的比较分析有限。此外，大多数研究没有区分单独旅行和集体旅行，导致对每种旅行类型影响的潜在错误估计。本研究利用深圳的多源数据，分析了六种接驳模式（即单人网约车、拼车、单人出租车、拼车、公交车和自由浮动共享单车）的接入模式及其与地铁系统的融合。本文采用极限梯度增强（XGBoost）和SHapley加性解释（SHAP）模型评估了这些接驳模式对地铁客流量的影响，并基于覆盖延伸比和行程时间比分析了按需运输服务如何填补地铁公交网络的空白。研究结果表明：(1)单人出租车是最快的馈线模式；(2)随着出行距离的增加，网约车的成本优势逐渐减弱，而出租车的速度优势越来越明显；(3)拼车有助于增加非中心地区的地铁使用率；(4)按需交通服务可以有效解决地铁公交网络的缺口。该研究为优化交通资源配置和提高地铁系统第一英里连通性提供了政策启示。

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引用次数: 0

ASB-TDM: Towards flexible and user-friendly transportation demand management in polycentric metropolitan areas ASB-TDM：在多中心的大都市地区实现灵活和用户友好的交通需求管理

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-20 DOI: 10.1016/j.tre.2025.104652

Zhanbo Sun , Huimin Tang , Baichuan Zhu , Qinxu Li , Xuting Wang , Rui Ma

This paper proposes a novel, flexible and user-friendly approach, namely, attraction site-based transportation demand management (ASB-TDM) to alleviate road congestion and improve social welfare in trip-making, where both pull and push strategies are imposed on attraction sites in polycentric metropolitan areas. Under the ASB-TDM, attraction sites - as the objects under government regulation - are charged for causing excessive congestion at traffic hotspots or subsidized to attract consumers and balance network traffic. The impacts of ASB-TDM can be partially transferred to the travelers. There is a game between the government, attraction sites and travelers. Government, as the leader, aims to maximize social welfare, while the attraction sites pursue maximizing their own profits, and travelers choose the destination and path accordingly so as to maximize individual trip-making utilities. A tri-level programming model is established to study the game, which is then solved using a meta-heuristic solution approach integrating method of successive algorithm, diagonalization algorithm, and elitism-based genetic algorithm. Experiments were conducted based on a four-node network, the Nguyen-Dupuis network, and the Sioux Falls Network. Numerical results indicate that the oligopolistic competition among attraction sites can lead to improved social welfare and alleviated traffic congestion due to the dispersion effects of attraction sites in polycentric metropolitan areas, as the induced travel demand is diverted to underutilized areas (e.g., subcenters). The ASB-TDM scheme with government participation further enhances these benefits by optimizing the competitive dynamics through strategic subsidies and charges, leading to superior outcomes compared to the pure market-driven approach.

本文提出了一种新颖、灵活且用户友好的方法，即基于景点的交通需求管理（ASB-TDM），该方法在多中心大都市地区的景点站点上实施拉和推策略，以缓解道路拥堵和提高出行社会福利。根据ASB-TDM，景点——作为政府监管的对象——在交通热点造成过度拥堵时要收费，或者为吸引消费者和平衡网络流量而提供补贴。ASB-TDM的影响可以部分转移到出行者身上。政府、景点和游客之间存在一种博弈。政府作为领导者的目标是社会福利最大化，景点追求自身利益最大化，游客选择目的地和路径以实现个人出行效用最大化。建立了一个三层规划模型来研究该博弈，然后采用逐次算法、对角化算法和基于精英的遗传算法相结合的元启发式求解方法对该博弈进行求解。实验是基于四节点网络、Nguyen-Dupuis网络和Sioux Falls网络进行的。结果表明，在多中心都市圈中，由于景点的分散效应，吸引的旅游需求被转移到未充分利用的区域（如副中心），因此，景点之间的寡头竞争可以改善社会福利，缓解交通拥堵。政府参与的ASB-TDM方案通过战略性补贴和收费优化竞争动态，进一步提高了这些效益，与纯市场驱动的方法相比，产生了更好的结果。

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引用次数: 0

Strategic bundling of information products: Managing consumer group tastes and product versions 信息产品的战略捆绑：管理消费者群体的口味和产品版本

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-20 DOI: 10.1016/j.tre.2026.104691

Mingjun Li , Sandun C. Perera , Xiang Ji

Bundling strategies are widely used in the information product market. Unlike physical products, information products typically have limited marginal costs, offer multiple versions, and differ in functionality rather than purely in quality. Motivated by the widespread use of bundling in retail and digital platforms, this study explores how firms can optimize bundling strategies for information products, taking into account varying consumer group tastes and quality differentiation between product versions. We consider a monopolistic firm that produces both a physical product and an information product, deciding on the version to offer as well as its bundling and pricing strategy. In addition to individual-level valuation heterogeneity, we also account for consumers’ group-level tastes toward information products, which influence both individual valuations and the perceived quality of different versions. Our findings reveal that bundling serves not only as a tool for price discrimination but also enables firms to effectively manage heterogeneous group preferences. Specifically, bundling is optimal when shared quality is either very low or very high, and firms may strategically choose between the basic and premium versions depending on consumer heterogeneity. Interestingly, under certain market conditions, bundling can function as a substitute for traditional versioning strategies. Moreover, the taste gap and the quality gap driven by group taste significantly impact a firm’s versioning and bundling strategies. These findings provide managerial insights into how firms can optimize pricing and product offerings in digital markets.

捆绑销售策略在信息产品市场中被广泛应用。与实体产品不同，信息产品通常具有有限的边际成本，提供多个版本，并且在功能上有所不同，而不仅仅是在质量上。由于捆绑销售在零售和数字平台上的广泛使用，本研究探讨了企业如何优化信息产品的捆绑销售策略，同时考虑到不同消费者群体的口味和产品版本之间的质量差异。我们考虑一家既生产实物产品又生产信息产品的垄断企业，决定提供的产品版本以及捆绑和定价策略。除了个人层面的评估异质性外，我们还考虑了消费者群体层面对信息产品的品味，这既影响了个人评估，也影响了不同版本的感知质量。我们的研究结果表明，捆绑销售不仅可以作为价格歧视的工具，而且可以使企业有效地管理异质性群体偏好。具体来说，当共享质量非常低或非常高时，捆绑销售是最优的，公司可能会根据消费者的异质性在基本版本和高级版本之间进行战略性选择。有趣的是，在某些市场条件下，捆绑可以作为传统版本控制策略的替代品。此外，由群体品味驱动的品味差距和质量差距显著影响了公司的版本控制和捆绑策略。这些发现为企业如何在数字市场中优化定价和产品提供了管理见解。

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引用次数: 0

Operational modes and market structures selection in the on-demand ride-hailing platform considering matching-induced utility uncertainty 考虑匹配效用不确定性的网约车平台运营模式与市场结构选择

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-20 DOI: 10.1016/j.tre.2026.104682

Feng Lin , Ran Xu , Xianglong Lin , Jizhou Lu

In on-demand ride-hailing platforms, participants face matching-induced utility uncertainty, a distinct phenomenon where participants cannot predict whether they will be successfully matched with counterparts. This uncertainty creates gaps between participants’ expected and realized utility, thus significantly influencing how platforms should optimize their pricing strategies to shape participants’ choices and market outcomes. To address this challenge, this paper constructs a theoretical framework of an on-demand platform ecosystem consisting of a ride-hailing platform (RP) and its upstream contract manufacturer (CM). We investigate how both parties strategically make pricing decisions to influence market structure formation and determine the optimal operational mode selection between business-to-customer (B2C) and peer-to-peer (P2P). Our comprehensive analysis reveals several key insights: 1) Regarding market structure formation, high service investment consistently leads to balanced structures across various commission rates in both operational modes. However, as service investment declines, the two modes diverge significantly: P2P mode invariably tends towards buyer markets regardless of commission rates, while B2C mode results in buyer markets only when commission rates exceed certain thresholds 2) When the platform supply chain achieves market balance, the CM exhibits a quality-profit inflection phenomenon, benefiting from increased service investment only when it surpasses a critical threshold. Below this threshold, profits paradoxically decrease as service investment improves due to intensified pricing competition at lower quality levels. 3) The RP selects the P2P mode exclusively when both service investment and commission rates are simultaneously high, otherwise strategically shifting to the B2C mode to access multiple revenue streams and reduce dependence on commission income alone. 4) The analysis extends to incorporate participant risk preferences and endogenous service investment decisions, which not only validates the core findings but also reveals how behavioral factors and strategic quality investments interact to shape market structures.

在按需叫车平台中，参与者面临着匹配引发的效用不确定性，这是一种独特的现象，参与者无法预测他们是否会成功地与对手匹配。这种不确定性造成了参与者预期效用和实际效用之间的差距，从而显著影响了平台应该如何优化其定价策略，从而塑造参与者的选择和市场结果。为了解决这一挑战，本文构建了一个由网约车平台（RP）及其上游合同制造商（CM）组成的按需平台生态系统的理论框架。我们研究了双方如何战略性地做出定价决策来影响市场结构的形成，并确定了B2C和P2P之间的最佳运营模式选择。我们的综合分析揭示了几个关键的见解：1)在市场结构形成方面，高服务投资始终导致两种运营模式下不同佣金率的结构平衡。然而，随着服务投资的下降，两种模式出现了明显的分歧：P2P模式无论佣金率如何都必然倾向于买方市场，而B2C模式只有在佣金率超过一定阈值时才会出现买方市场。2)当平台供应链达到市场平衡时，CM表现出质量-利润的拐点现象，只有当服务投资超过一个临界阈值时，CM才会受益于服务投资的增加。低于这个门槛，利润反而会随着服务投资的增加而减少，这是由于在较低质量水平上加剧了价格竞争。3)当服务投资和佣金率同时较高时，RP只选择P2P模式，否则战略性地转向B2C模式，以获取多种收入流，减少对佣金收入的依赖。4)将参与者风险偏好和内生服务投资决策纳入分析，不仅验证了核心结论，而且揭示了行为因素和战略质量投资如何相互作用影响市场结构。

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引用次数: 0

Balancing service quality and riders’ welfare in on-demand delivery order dispatching: an integrated rolling horizon and differentiated incentive approach 按需配送订单调度中服务质量与乘客福利的平衡：综合滚动地平线与差异化激励方法

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-19 DOI: 10.1016/j.tre.2026.104685

Fuyu Cao , Yichen Qin , Hongtao Hu , Xuting Sun , Kam K.H. Ng

As on-demand food delivery plays an important role in daily service, it also poses significant challenges in developing real-time optimization solutions. Overwhelming customer orders require real-time rider dispatch and route scheduling dynamically, while meal preparation delays disrupt the scheduled routing plan of riders. The resulting delivery lateness incurs penalties to riders. To balance delivery service quality and riders’ welfare, this paper proposes an order exchange mechanism which enables riders to return the delayed orders back to the platform. The platform then identifies potential riders willing to undertake the returned orders with differentiated incentives. Four mixed integer linear programming (MILP) models are formulated to capture the sequential interactive decisions of the platform and riders. A dynamic order returning and dispatching method is designed and embedded with the rolling horizon approach, managing both the returned orders and the newly arriving orders adaptively. Meanwhile, aimed at balancing riders’ individual welfare, we introduce an equity metric and establish a bi-objective order dispatching model, subsequently employing the ε-constraint approach with a linearization technique. A tailored Artificial Bee Colony (ABC) algorithm solves instances based on a new town in Shanghai Megacity, China. Numerical experiments demonstrate that the order exchange mechanism enhances scheduling flexibility and ensures welfare equity. Interestingly, incorporating equity considerations reveals that generous pricing strategies paradoxically improve the overall system efficiency and ultimately reduce the total operational costs. Policy recommendations based on these findings are provided for on-demand delivery service platforms to strategically manage their riders and delivery orders.

随需外卖在日常服务中扮演着重要的角色，同时也给实时优化解决方案的开发带来了巨大的挑战。大量的客户订单需要实时的骑手调度和动态的路线调度，而饭菜准备的延迟打乱了骑手预定的路线计划。由此导致的送货延误会对乘客造成处罚。为了平衡配送服务质量和乘客福利，本文提出了一种订单交换机制，使乘客能够将延迟的订单返回到平台。然后，该平台通过差异化的激励措施，识别愿意接受退回订单的潜在骑手。建立了四个混合整数线性规划（MILP）模型，以捕获平台和乘客的顺序交互决策。设计了一种动态订单返回与调度方法，并嵌入滚动地平线方法，对返回的订单和新到达的订单进行自适应管理。同时，以平衡乘客个人福利为目标，引入公平度量，建立双目标订单调度模型，并采用线性化的ε约束方法。一种量身定制的人工蜂群（ABC）算法解决了基于中国上海特大城市新城镇的实例。数值实验表明，订单交换机制提高了调度灵活性，保证了福利公平性。有趣的是，考虑到公平因素，慷慨的定价策略反而提高了整个系统的效率，并最终降低了总运营成本。根据这些发现，为按需配送服务平台提供了政策建议，以战略性地管理其骑手和配送订单。

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引用次数: 0

Pareto optimal regulatory strategies for coupled ridesourcing and taxi markets with impatient passengers 有不耐烦乘客的拼车和出租车市场的帕累托最优监管策略

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-19 DOI: 10.1016/j.tre.2026.104677

Xiaohan Zhou , Shaopeng Zhong , Hai Yang , Yunhai Gong , Xiantao Xiao , Yu Jiang

This study develops a multi-objective bi-level programming model to identify the Pareto optimal combined regulatory strategy that simultaneously accounts for passengers, taxi drivers, ridesourcing vehicle (RSV) drivers, and the transportation network company (TNC). The upper level determines four regulatory controls, including the RSV fleet cap, taxi fare rate, government-guided RSV fare rate, and TNC wage rate floor, while the lower level obtains the steady-state market performance, which is formulated as a fixed-point problem and approximated through iterative agent-based simulations. To solve the model, a multi-objective Bayesian optimization algorithm is developed. Based on the DiDi dataset collected from Hangzhou City in 2018, our experiments demonstrate that no regulatory strategy can simultaneously benefit all stakeholders. If the government considers maximizing vehicle utilization as a secondary criterion, then it should decrease the RSV fleet cap, impose higher fare rates, and allow the TNC to pay lower wages, compared with the benchmark scenario. Furthermore, it is recommended that the government should avoid regulations that primarily favor passengers or the TNC, as our results reveal that such policies could harm other stakeholders and reduce vehicle utilization by up to 11.6%. Finally, if passengers’ impatience is overlooked, taxi drivers may lose 23.3% of potential profits.

本研究建立了一个多目标双层规划模型，以确定同时考虑乘客、出租车司机、拼车司机和运输网络公司的帕累托最优组合监管策略。上层确定四种监管控制，包括RSV车队上限、出租车收费标准、政府引导的RSV收费标准和跨国公司最低工资标准，下层获得稳态市场绩效，将其表述为一个不动点问题，并通过基于迭代智能体的模拟进行近似。为了求解该模型，提出了一种多目标贝叶斯优化算法。基于2018年杭州市的滴滴数据集，我们的实验表明，没有一种监管策略可以同时使所有利益相关者受益。如果政府考虑将车辆利用率最大化作为次要标准，那么它应该降低RSV车队上限，征收更高的票价，并允许TNC支付较低的工资，与基准情景相比。此外，建议政府应避免主要有利于乘客或跨国公司的法规，因为我们的研究结果表明，此类政策可能会损害其他利益相关者，并减少高达11.6%的车辆利用率。最后，如果忽视乘客的不耐烦，出租车司机可能会损失23.3%的潜在利润。

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引用次数: 0

Optimizing hub networks for truck platooning under uncertainty in cost savings 在成本节约不确定的情况下，优化卡车队列的枢纽网络

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-19 DOI: 10.1016/j.tre.2026.104692

Elif Zeynep Serper , Sibel A. Alumur

Platooning offers significant potential cost benefits for truckload transportation by utilizing vehicle-to-vehicle communication and automation through the formation and dissolution of platoons at hubs. This paper addresses optimization of platooning hub networks for transporting truckloads of commodities from their origins to destinations within the promised delivery times. Deterministic and stochastic optimization models are developed to design these networks with a minimum total cost, where each truckload of a commodity can be transported either directly along its shortest path from origin to destination or routed via platooning through hubs. The stochastic model incorporates uncertainty associated with the potential cost savings due to platooning. The Sample Average Approximation method is employed to solve the stochastic model. Using real-world data involving 1253 commodities across 39 U.S. cities, the computational analysis demonstrates significant cost savings and delivery performance improvements through platooning. On average, even under the highest hub operating costs, the proposed model achieves a 7.97% reduction in overall costs compared to the direct-shipment-only scenario, with the best-case improvement reaching 15.89%. Additionally, the platoon-enabled network significantly improves delivery performance, increasing the share of shipments delivered within one day by up to 42% compared to the direct-shipment-only case. Furthermore, the results demonstrate the stochastic model’s ability to adapt to cost uncertainties, making it a valuable tool for changing logistics environments.

通过在枢纽形成和解散队列，利用车对车的通信和自动化，队列为卡车运输提供了巨大的潜在成本效益。本文讨论了在承诺的交货时间内将货物从原产地运输到目的地的队列枢纽网络的优化问题。开发了确定性和随机优化模型，以最小的总成本设计这些网络，其中每辆卡车的商品可以直接沿着从起点到目的地的最短路径运输，也可以通过集线器进行队列运输。随机模型包含了不确定性与潜在的成本节约有关。采用样本平均逼近法求解随机模型。使用涉及39个 美国的1253种商品的真实数据在城市中，计算分析表明，通过队列化可以显著节省成本并提高交付性能。平均而言，即使在最高的枢纽运营成本下，与仅直接发货的情况相比，所提出的模型也能实现7.97%的总成本降低，最佳情况下的改进达到15.89%。此外，该网络显著提高了交付性能，与直接交付相比，一天内交付的货物份额提高了42%。此外，结果表明，随机模型的能力，以适应成本的不确定性，使其成为一个有价值的工具，为不断变化的物流环境。

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引用次数: 0

Freeports under the lens: securing container supply chains with a risk-based inspection framework 镜头下的自由港：用基于风险的检查框架保护集装箱供应链

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-19 DOI: 10.1016/j.tre.2025.104658

Xinrui Liang , Shiqi Fan , Huanhuan Li , Floris Goerlandt , Zaili Yang

Freeports that attract illegal activities may become vulnerable without effective measures to ensure a safe and secure Maritime Container Supply Chain (MCSC) involving them. Developing a holistic risk-based inspection framework is essential to address illicit trade challenges in freeports without the need to significantly compromise operational efficiency in a globalized trading environment. However, the existing literature is limited in addressing the uncertainty in container risk levels for establishing inspection priorities and in considering the unique features of freeports. To close these gaps, this study develops a novel framework based on a hybrid two-stage decision-making approach for the optimal container inspection solution, focusing on high-risk containers within the context of Freeport-Centric Supply Chains. The first stage employs a hybrid Decision-Making Trial and Evaluation Laboratory and Bayesian Network (DEMATEL-BN) model to assess container risk levels, accounting for interdependent vulnerabilities across MCSC nodes. The findings identify the most critical risk nodes within the MCSC, including consolidation centers and loading ports. Furthermore, it measures the risk levels of containers based on both severity and likelihood metrics, which serve as key inputs for determining inspection rates in the second stage, distinguishing the approach by effectively addressing uncertainties often overlooked in existing container inspection frameworks. This approach makes new contributions to enhancing the security of freeports and various MCSCs by enabling targeted risk mitigation, optimizing inspection strategies, and balancing security with trade flow efficiency.

吸引非法活动的自由港如果没有有效的措施来确保安全可靠的海上集装箱供应链（MCSC），可能会变得脆弱。制定一个基于风险的整体检查框架对于解决自由港的非法贸易挑战至关重要，同时又不需要在全球化的贸易环境中大幅降低运营效率。然而，现有文献在解决集装箱风险水平的不确定性以确定检查优先级和考虑自由港的独特特征方面是有限的。为了缩小这些差距，本研究开发了一个基于混合两阶段决策方法的新框架，用于最佳集装箱检验解决方案，重点关注以自由港为中心的供应链背景下的高风险集装箱。第一阶段采用混合决策试验和评估实验室和贝叶斯网络（DEMATEL-BN）模型来评估容器风险水平，考虑MCSC节点之间的相互依赖漏洞。研究结果确定了MCSC内最关键的风险节点，包括整合中心和装载港口。此外，它根据严重性和可能性度量来度量容器的风险水平，这是确定第二阶段检查率的关键输入，通过有效地解决现有容器检查框架中经常被忽视的不确定性来区分方法。该方法通过有针对性地降低风险、优化检查策略、平衡安全和贸易流效率，为加强自由港和各种MCSCs的安全作出了新的贡献。

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引用次数: 0

An event-based model and hybrid genetic search algorithm for an inland multi-size container transportation problem 内陆多尺寸集装箱运输问题的事件模型和混合遗传搜索算法

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-01-17 DOI: 10.1016/j.tre.2025.104639

Meiyan Chi , Xiaoning Zhu , Baicheng Yan , Kris Braekers

This paper addresses a complex multi-size Container Drayage Problem (CDP) in the hinterland of a seaport, where a fleet of identical trucks is used to transport containers between customer locations, a container terminal, and a depot, and in which the repositioning of empty containers is also considered. Each truck can carry either one 40-ft container or two 20-ft containers simultaneously. The main target of the CDP is to determine the trucking schedule that satisfies all transport demands while minimizing the total cost. The problem is described using an event-based graph that considers capacity, pairing, precedence, and time-window constraints implicitly, based on which a compact Mixed-Integer Linear Programming (MILP) model is proposed. To reduce the model scale and enhance computational efficiency, we introduce tailored model enhancement methods to eliminate infeasible event nodes and arcs based on time window feasibility checks. The results of numerical experiments prove that the event-based model can solve small-scale instances effectively. For large-scale instances, we develop a Hybrid Genetic Search (HGS) algorithm that incorporates a Dynamic Programming (DP)-optimized enumeration method to handle multi-size container loading schemes and time-window constraints effeciently. Extensive computational experiments show that our proposed algorithm significantly outperforms the commercial solver CPLEX on large-scale instances, demonstrating its scalability for real-world applications.

本文解决了海港腹地复杂的多尺寸集装箱拖运问题（CDP），其中使用相同的卡车车队在客户位置，集装箱码头和仓库之间运输集装箱，并且还考虑了空集装箱的重新定位。每辆卡车可以同时装载一个40英尺的集装箱或两个20英尺的集装箱。CDP的主要目标是确定满足所有运输需求的卡车运输时间表，同时将总成本降至最低。利用隐式考虑容量、配对、优先级和时间窗约束的事件图来描述问题，在此基础上提出了紧凑的混合整数线性规划（MILP）模型。为了减小模型规模，提高计算效率，我们引入了基于时间窗可行性检查的模型增强方法，以消除不可行的事件节点和弧线。数值实验结果表明，基于事件的模型可以有效地求解小尺度实例。对于大规模实例，我们开发了一种混合遗传搜索（HGS）算法，该算法结合了动态规划（DP）优化的枚举方法来有效地处理多尺寸集装箱装载方案和时间窗约束。大量的计算实验表明，我们提出的算法在大规模实例上显著优于商业求解器CPLEX，证明了其在实际应用中的可扩展性。

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引用次数: 0