Transportation Research Part E-Logistics and Transportation Review最新文献_第8页

A multi-channel retail store location model considering customer retry purchasing patterns 考虑顾客重试购买模式的多渠道零售商店选址模型

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-04-01 Epub Date: 2026-01-17 DOI: 10.1016/j.tre.2026.104674

Lifen Yun , Runfeng Yu , Hongqiang Fan , Yuanjie Tang , Xun Weng

The rapid growth of e-commerce has driven retailers to establish multiple retail channels to enhance service quality for their customers. Despite retailers’ efforts to serve customers, services may not always be available due to various reasons. In such cases, customers often retry their purchases through their preferred channel. This behavior, along with the complexities of multi-channel retailing, complicates both the structure and costs of last-mile network design. To optimize store locations and costs, this paper proposes a mixed-integer programming (MIP) model for tactical store location planning, considering customer retry purchasing patterns and three channels: ship from store (SFS), buy online and pick up in store (BOPS), and offline shopping (OS). Given that the problem is NP-hard in the strong sense, we develop an iterative two-phase Lagrangian relaxation and granular tabu search heuristic (LR-GTS) to tackle large-scale instances. In each iteration, the LR operator decomposes the model and produces high-quality location schemes, while the GTS operator improves the vehicle routing in the SFS channel. Numerical results demonstrate that our heuristic exhibits strong performance in solving large-scale problems involving 600 customers. Additionally, we apply our model to real-world cases, offering valuable managerial insights derived from the sensitivity analysis results.

电子商务的快速发展促使零售商建立多种零售渠道，以提高对客户的服务质量。尽管零售商努力为顾客服务，但由于各种原因，服务可能并不总是可用的。在这种情况下，顾客通常会通过他们喜欢的渠道重新购买。这种行为，加上多渠道零售的复杂性，使最后一英里网络设计的结构和成本都变得复杂。为了优化商店位置和成本，本文提出了一种混合整数规划（MIP）模型，用于战术商店位置规划，考虑了客户重试购买模式和三个渠道：从商店发货（SFS），在线购买和在商店取货（BOPS）和离线购物（OS）。考虑到该问题在强意义上是np困难的，我们开发了一种迭代的两阶段拉格朗日松弛和颗粒禁忌搜索启发式（LR-GTS）来处理大规模实例。在每次迭代中，LR算子分解模型并生成高质量的定位方案，而GTS算子则改进SFS通道中的车辆路线。数值结果表明，我们的启发式算法在解决涉及600个客户的大规模问题时表现出很强的性能。此外，我们将我们的模型应用于实际案例，从敏感性分析结果中提供有价值的管理见解。

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引用次数: 0

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 : 2026-04-01 Epub 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

Service network design for electric vehicles with combined battery swapping and recharging 混合换电池充电的电动汽车服务网络设计

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-04-01 Epub Date: 2026-01-09 DOI: 10.1016/j.tre.2026.104668

Xudong Diao , Meng Qiu

Incorporating both battery swapping and recharging strategies within electric vehicle (EV) service networks provides a flexible means of mitigating range limitations. While jointly optimizing these strategies poses significant modeling and computational challenges, it also yields valuable insights into their relative operational performance. We develop an optimization framework that jointly determines service network design, EV routing decisions, and the scheduling of recharging and battery swapping operations, while respecting capacity constraints on both activities. This study establishes a unified mixed-integer programming framework for EV service network design that integrates the two replenishment strategies under system-wide capacity limitations. To handle large-scale instances efficiently, we employ a column generation scheme, in which the pricing subproblem is solved using a bidirectional labeling algorithm supported by tailored dominance rules and problem-specific resource extension functions. In addition, a dedicated heuristic is designed to construct high-quality integer solutions. Computational experiments based on real-world case studies show that when both strategies are available, battery swapping tends to outperform recharging due to its shorter service time, highlighting the scalability and practical relevance of the proposed approach.

在电动汽车（EV）服务网络中结合电池交换和充电策略提供了一种灵活的缓解里程限制的方法。虽然联合优化这些策略会带来重大的建模和计算挑战，但它也会对它们的相对操作性能产生有价值的见解。我们开发了一个优化框架，共同确定服务网络设计、电动汽车路线决策以及充电和电池交换操作的调度，同时尊重这两项活动的容量约束。本文建立了一个统一的混合整数规划框架，用于电动汽车服务网络设计，该框架在全系统容量限制下集成了两种补充策略。为了有效地处理大规模实例，我们采用了一种列生成方案，其中定价子问题使用由定制的优势规则和问题特定的资源扩展函数支持的双向标记算法来解决。此外，还设计了一个专门的启发式算法来构造高质量的整数解。基于实际案例研究的计算实验表明，当两种策略都可用时，电池交换往往优于充电，因为其使用时间更短，突出了所提出方法的可扩展性和实际相关性。

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引用次数: 0

What if rebalancing fleets could adapt? A two-stage stochastic model for dynamic bike redistribution 如果重新平衡的船队能够适应呢？自行车动态再分配的两阶段随机模型

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-04-01 Epub Date: 2026-01-15 DOI: 10.1016/j.tre.2025.104640

Mohammadreza Eslamipirharati , Maryam Motamedi , John Doucette , Nooshin Salari

Bike-sharing systems are an important mode of transportation, enabling individuals to rent bikes for short trips and return them to any station throughout the city. However, the dynamic nature of user arrivals at each station leads to imbalances between bike supply and demand, resulting in unsatisfied users. An essential challenge lies in efficiently deploying and scheduling rebalancing vehicles for bike redistribution, as these decisions have a considerable effect on the efficiency of the system. To tackle this challenge, we propose a dynamic rebalancing model that integrates tactical and operational decisions within a single optimization framework. Unlike approaches that treat these decisions separately, our model captures the interaction between the two: in the first stage, it determines how many vehicles should be deployed over the planning horizon (tactical decision), and in the second stage, it assigns stations to dynamic rebalancing groups and allocates vehicles to these groups in response to demand realizations (operational decisions). To address the computational challenge, we propose two approaches: an Improved Integer L-shaped decomposition algorithm and a heuristic that combines machine learning with an early stopping criterion to estimate the second-stage cost function. Moreover, we generate forecasts of rental and return demand and incorporate them into the optimization model to enhance decision-making under demand uncertainty. Our numerical results show that the proposed heuristic is highly effective in minimizing the unsatisfied demand while reducing the computational costs efficiently.

自行车共享系统是一种重要的交通方式，使个人可以租用自行车进行短途旅行，并将其归还到城市的任何一个站点。然而，用户到达每个站点的动态特性导致自行车供需不平衡，导致用户不满意。一个重要的挑战在于有效地部署和调度再平衡车辆进行自行车再分配，因为这些决策对系统的效率有相当大的影响。为了应对这一挑战，我们提出了一个动态再平衡模型，该模型将战术和操作决策集成在一个单一的优化框架中。与单独处理这些决策的方法不同，我们的模型捕获了两者之间的相互作用：在第一阶段，它确定在规划范围内应该部署多少车辆（战术决策），在第二阶段，它将站点分配给动态再平衡组，并根据需求实现将车辆分配给这些组（操作决策）。为了解决计算上的挑战，我们提出了两种方法：一种改进的整数l形分解算法和一种启发式算法，该算法将机器学习与早期停止准则相结合，以估计第二阶段的成本函数。在此基础上，对租金和收益需求进行预测，并将其纳入优化模型，以增强需求不确定性下的决策能力。数值结果表明，所提出的启发式算法在最小化未满足需求的同时有效地降低了计算成本。

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引用次数: 0

Integrated and shared charging optimization of electric buses and shared micromobility incorporating solar photovoltaic 基于太阳能光伏的电动公交车集成共享充电优化与共享微出行

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-04-01 Epub Date: 2026-01-28 DOI: 10.1016/j.tre.2026.104709

Xiaohan Liu , Arsalan Najafi , Sheng Jin , Hua Wang , Xiaolei Ma , Kun Gao

Public transport electrification contributes to the net-zero goal in the transport sector. However, high-power bus charging during peak hours places additional strain on the grid, while under-utilization of charging infrastructure limits its potential economic and social benefits. This study focuses on these challenges through integrated and shared optimization of battery electric buses (BEB) and shared micromobility systems (SMS) incorporating solar photovoltaic. We present a bi-level mixed-integer linear programming model (B-MILM) to jointly optimize BEB charging infrastructure, BEB charging schedules, solar PV installed capacity, and SMS charging schedule. The B-MILM is solved using a value-function-based exact approach. We derive a group of inequalities based on the problem characteristics to reduce solution time. A large-scale case study in Gothenburg, Sweden, demonstrates that solar photovoltaic and shared charging services yield annual cost savings 110% - 120% above investment costs for public transit agencies, even when the service fee revenue is excluded. Charging dispatching costs for e-scooter operators are reduced by up to 54%, and daily BEB charging grid loads decrease by 3% to 34% across seasons. The greenhouse emissions from electricity consumption of BEBs and e-scooters are reduced by 3%. The results offer new insights for sustainable charging and energy infrastructure planning and management for electric public transit.

公共交通电气化有助于实现交通部门的净零目标。然而，高峰时段的大功率公交车充电给电网带来了额外的压力，充电基础设施的利用率不足限制了其潜在的经济效益和社会效益。本研究通过集成和共享优化电池电动公交车（BEB）和包含太阳能光伏的共享微移动系统（SMS）来关注这些挑战。我们提出了一个双层混合整数线性规划模型（B-MILM）来共同优化BEB充电基础设施、BEB充电计划、太阳能光伏装机容量和SMS充电计划。B-MILM采用基于值函数的精确方法求解。为了缩短求解时间，我们根据问题的特征导出了一组不等式。瑞典哥德堡的一项大规模案例研究表明，即使不包括服务费收入，太阳能光伏和共享充电服务每年也能比公共交通机构的投资成本节省110% - 120%。电动滑板车运营商的充电调度成本降低了54%，电动滑板车充电电网的日负荷在不同季节减少了3%至34%。电动自行车和电动滑板车的电力消耗温室气体排放量减少了3%。研究结果为电动公共交通的可持续充电和能源基础设施规划和管理提供了新的见解。

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引用次数: 0

Dynamic pricing strategies based on Consumers’ psychology during product-harm crises 产品危害危机中基于消费者心理的动态定价策略

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-04-01 Epub Date: 2026-01-28 DOI: 10.1016/j.tre.2026.104705

Kaifu Li, Deqing Ma, Jinsong Hu, Xue Wang

Product-harm crises happen unexpectedly, triggering product recalls and altering consumer psychology, posing significant challenges to brands. This paper examines a monopoly brand selling a single product, identifying three crisis scenarios: no crisis, severe crisis, and mild crisis. Incorporating the crisis’s long-term effect, consumers’ price mapping psychology (PMP), and their vigilance to the crisis, we explore the dynamic pricing strategy for a far-sighted brand manager. The results suggest that in the absence of a crisis, the brand manager, weighing against consumers’ PMP and the law of demand (LOD), sets price based on the product’s basic quality. Regardless of whether the product survives the crisis, a risk premium will always be charged before a crisis to cushion recall costs. After the crisis, price drops, but demand may soften as consumers grow intolerant of implicated products and require products with superior basic quality. Thus, the crisis and its long-term effects inevitably harm both the supply and demand sides. Although the negative impact cannot be eliminated by dynamic pricing strategies, the brand can benefit from greater market share and minimize profit loss rates by leveraging consumers’ PMP and laxity. Interestingly, despite being exploited, consumers benefit from increased utility and consumer surplus. Notably, the hazard myopia of a brand manager is only more beneficial when the crisis arrives later. Brands confronted with crises must reduce production costs or be priced out of the market. By capitalizing on recalled products’ salvage value, the brand will lower the risk premium due to eased recall cost pressures.

产品危害危机突发，引发产品召回，改变消费者心理，给品牌带来重大挑战。本文以单一产品的垄断品牌为研究对象，确定了三种危机情景：无危机、严重危机和轻微危机。结合危机的长期影响、消费者的价格映射心理（PMP）和他们对危机的警惕性，我们探讨了一个有远见的品牌经理的动态定价策略。结果表明，在没有危机的情况下，品牌经理会权衡消费者的PMP和需求定律（LOD），根据产品的基本质量来定价。不管产品是否能在危机中幸存下来，在危机发生前总会收取风险溢价，以缓冲召回成本。危机过后，价格下降，但需求可能会减弱，因为消费者越来越不能容忍有问题的产品，并要求产品具有更高的基本质量。因此，这场危机及其长期影响不可避免地损害了供需双方。虽然负面影响不能通过动态定价策略消除，但品牌可以通过利用消费者的PMP和宽松性来获得更大的市场份额，并将利润损失率降至最低。有趣的是，尽管被剥削，消费者受益于效用的增加和消费者剩余。值得注意的是，品牌经理的风险短视只会在危机晚些时候到来时更有利。面临危机的品牌必须降低生产成本，否则就会被挤出市场。通过利用召回产品的残值，该品牌将降低因召回成本压力减轻而带来的风险溢价。

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引用次数: 0

Climate shock impacts on supply chains: the case of the truckload spot market 气候冲击对供应链的影响：以卡车现货市场为例

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-04-01 Epub Date: 2026-01-09 DOI: 10.1016/j.tre.2025.104609

Sara Hsu , Andrew Balthrop , Dan Pellathy , Travis Kulpa , Gonzalo Andrew Ferrada , Joshua Fu

Climate shocks increasingly disrupt supply chains, yet research has focused primarily on mitigation strategies (i.e., carbon reduction), leaving adaptation strategies comparatively understudied. We begin to fill this gap by studying how transportation managers within a supply chain respond to climate-related shocks, defined as a month in which a state’s exposure to extreme temperature or precipitation events rises significantly, measured by the custom University of Tennessee Climate Index (UTCI), which combines anomalies in high/low temperature and heavy precipitation with population exposure. Drawing on structured interviews with transportation managers, we uncover beliefs that shippers tend to be less demand-responsive in the short-term to climate-related shocks, often prioritizing the desire to move freight at any reasonable cost. Motor carriers, in contrast, are more sensitive to price. To test these qualitative assessments, we regress monthly state-level truckload spot market data from the contiguous 48 states on the UTCI in reduced-form two-way fixed effects specifications, finding that a one-standard-deviation increase in climate shocks increases freight prices by 1.9%, with minimal effects on freight volume, indicating that market adjustments occur primarily through price rather than quantity. We further estimate IV specifications based on three-stage least squares (3SLS) models to disentangle the net causal effects from the reduced form specification. Consistent with our interviews, we find motor carriers are more sensitive than shippers to climate shocks. The results have important implications, offering shippers, carriers, and brokers with concrete price-change benchmarks they can use to budget transportation spend, design contract–spot portfolios, and plan capacity during climate shocks.

气候冲击日益扰乱供应链，但研究主要集中在缓解战略（即碳减排）上，对适应战略的研究相对不足。我们开始通过研究供应链内的运输管理人员如何应对气候相关冲击来填补这一空白，气候冲击的定义是一个州暴露于极端温度或降水事件显著上升的一个月，由定制的田纳西大学气候指数（UTCI）测量，该指数将高/低温和强降水的异常与人口暴露相结合。通过对运输经理的结构化访谈，我们发现，托运人在短期内对气候相关冲击的需求反应往往较弱，往往优先考虑以任何合理的成本运输货物。相比之下，汽车运输公司对价格更为敏感。为了验证这些定性评估，我们以简化形式的双向固定效应规范对UTCI上连续48个州的月度州一级卡车现货市场数据进行回归，发现气候冲击增加一个标准差会使货运价格上涨1.9%，对货运量的影响最小，这表明市场调整主要通过价格而不是数量发生。我们基于三阶段最小二乘（3SLS）模型进一步估计IV规范，以从简化形式规范中分离出净因果效应。与我们的采访一致，我们发现汽车运输公司比托运人对气候冲击更敏感。研究结果具有重要意义，为托运人、承运人和经纪人提供了具体的价格变化基准，他们可以利用这些基准来预算运输支出，设计合同现货组合，并在气候冲击期间规划运力。

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引用次数: 0

Enhanced column-and-constraint generation algorithm for robust logistics network design problem with capacity sharing 容量共享鲁棒物流网络设计问题的改进列约束生成算法

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-04-01 Epub Date: 2026-01-23 DOI: 10.1016/j.tre.2026.104699

Hongtao Hu , Kejian Jiang , Zhu Wang , Jia Shu

Achieving robustness has become an essential issue due to the significant volatility of the logistics networks. Current works prioritize the demand uncertainty, but not sufficiently consider the financial budget uncertainty in warehousing. This deficiency renders the collaborators with weak financial endurance intractable to maintain the scheme robustness, impairing the overall network resilience. Therefore, inspired by the Nash equilibrium, a logistics network design method focusing on capacity sharing is proposed. This method allows participants to share capacity in the distribution centers, improving resilience and reducing costs. Firstly, a two-stage robust model considering the uncertainty of demand and financial budget is established to minimize the operating costs of the logistics network. Then, the Nash equilibrium-based constraints are incorporated into the model to ensure a fair distribution of benefits and costs among participants. Subsequently, a two-stage method is designed with an enhanced column and constraint generation algorithm (C

&

CG) using optimal cut, and reverse Nash equilibrium-based constraints are proposed for the worst financial condition. The effectiveness of the algorithm and model is verified through a series of numerical benchmarks and sensitivity analysis for Nash equilibrium-based constraints, sharing restrictions, uncertainty of demand and financial budget. The results show that the proposed method is efficient and flexible when incorporating capacity sharing and highlighting the influence of the Nash equilibrium-based constraints. Finally, it presents that the Nash equilibrium-based constraints are more suitable for logistics networks through sharing alliances.

由于物流网络的显著波动性，实现稳健性已成为一个重要问题。目前的工作优先考虑需求的不确定性，但没有充分考虑仓储财务预算的不确定性。这使得财务承受能力较弱的协作者难以维持方案的鲁棒性，从而损害了整个网络的弹性。因此，受纳什均衡的启发，提出了一种以容量共享为中心的物流网络设计方法。这种方法允许参与者在配送中心共享容量，提高弹性并降低成本。首先，建立了考虑需求不确定性和财务预算不确定性的两阶段鲁棒模型，使物流网络的运营成本最小化。然后，在模型中引入基于纳什均衡的约束，以确保参与者之间的收益和成本公平分配。随后，设计了一种采用最优切割的增强型列约束生成算法（C&；CG）的两阶段方法，并针对最坏财务状况提出了基于反向纳什均衡的约束。通过对基于纳什均衡约束、共享约束、需求不确定性和财务预算的一系列数值基准和敏感性分析，验证了算法和模型的有效性。结果表明，该方法在考虑容量共享的同时，突出了纳什均衡约束的影响，具有较高的效率和灵活性。最后，提出了基于纳什均衡的约束更适用于共享联盟的物流网络。

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引用次数: 0

The efficacy of decentralized disaster relief resource allocation within communities: The role of community-based sharing captains 社区内分散救灾资源分配的有效性：社区共享队长的作用

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-04-01 Epub Date: 2026-01-23 DOI: 10.1016/j.tre.2026.104690

Olivia Wang , Zhengyang Li , Cynthia Chen

Motivated by numerous observations that neighbors want to help and be helped by each other, this study investigates the feasibility of a decentralized resource allocation strategy where sharing captains distribute disaster relief resources within their community. Here sharing captains are residents themselves who step up during a disaster and take on the role of sharing/distributing resources with/to their neighbors. Using data from two socioeconomically different communities in Seattle, we simulate and compare the efficacy of the proposed decentralized strategy and the status quo fixed-point distribution method that relies on residents to come and get resources on their own. Our findings reveal that the decentralized approach significantly reduces residents’ deprivation costs (a measure on residents’ suffering due to resource shortage) and reaches 100% resource coverage faster than the fixed-point distribution strategy. For both communities, our experiments suggest that an effective range of sharing captains is between 30 and 40. Though the success of the decentralized strategy lies fundamentally on residents’ willingness to share, a satisfactory outcome can be reached even when a substantial share of residents (40%) are unwilling to share with anybody. This is in contrast to only 3% and 7% of the residents in these two communities who are found to be unwilling to share with anybody. Furthermore, sharing captains’ own biases in distributing resources appear to have a marginal effect on the resource allocation outcomes. On selecting sharing captains, a comprehensive strategy considering multiple factors (sharing preferences, number of social ties, and civic engagement) shall be adopted.

基于邻居之间相互帮助和相互帮助的愿望，本研究探讨了一种分散资源分配策略的可行性，即共享船长在其社区内分配救灾资源。这里的“分享队长”指的是居民自己，他们在灾难发生时挺身而出，承担起与邻居分享/分配资源的角色。利用来自西雅图两个社会经济状况不同的社区的数据，我们模拟并比较了所提出的分散策略和现状的依靠居民自己来获取资源的定点分配方法的效果。研究结果表明，与定点分配策略相比，分散式分配策略显著降低了居民的剥夺成本（衡量居民因资源短缺而遭受的痛苦），并更快地达到100%的资源覆盖。我们的实验表明，对于这两个社区来说，有效的共享船长范围在30到40人之间。虽然分散化策略的成功从根本上取决于居民的分享意愿，但即使有相当一部分居民（40%）不愿与任何人分享，也能取得令人满意的结果。相比之下，这两个社区中只有3%和7%的居民不愿意与任何人分享。此外，分享船长在分配资源方面的偏见似乎对资源配置结果具有边际效应。在选择共享船长时，应考虑多种因素（共享偏好、社会关系数量、公民参与）的综合策略。

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引用次数: 0

Platelet inventory management in hospital networks: A reinforcement learning approach 医院网络血小板库存管理：一种强化学习方法

IF 8.8 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review

Pub Date : 2026-04-01 Epub Date: 2026-01-17 DOI: 10.1016/j.tre.2025.104629

Shahrzad Valizadeh , Babak Abbasi , Su Nguyen , Zahra Hosseinifard

This study proposes a reinforcement learning (RL)-based framework incorporating the Proximal Policy Optimization (PPO) algorithm to improve platelet inventory management. The proposed approach considers an inventory system with varying ordering intervals, incorporating ABO-Rh substitution decisions and hospital collaborations through transshipment. In this framework, transshipment is modeled as a fixed policy, reflecting real-world practices where blood units nearing expiration are proactively transferred from smaller local hospitals to larger hospitals, where they are more likely to be used in time. We extend our analysis by exploring several RL models, including Trust Region Policy Optimization (TRPO) and Soft Actor-Critic (SAC). The results show that PPO-Complete outperforms the other RL models, and all considered RL approaches outperform the base-stock strategy, which is commonly used in hospital platelet inventory management. The analyses indicate that lower transshipment costs, when coupled with effective substitution decisions, lead to a reduction in total cost and enable larger order sizes, thereby mitigating shortages.

本研究提出了一种基于强化学习（RL）的框架，结合近端策略优化（PPO）算法来改善血小板库存管理。提出的方法考虑了具有不同订货间隔的库存系统，包括ABO-Rh替代决策和通过转运的医院合作。在这个框架中，转运被建模为一种固定的政策，反映了现实世界的做法，即即将到期的血液单位主动从较小的当地医院转移到更有可能及时使用的大医院。我们通过探索几个RL模型来扩展我们的分析，包括信任域策略优化（TRPO）和软行为者批评家（SAC）。结果表明，PPO-Complete模型优于其他RL模型，并且所有RL方法都优于医院血小板库存管理中常用的基础库存策略。分析表明，较低的转运成本，加上有效的替代决策，导致总成本的降低，并使更大的订单规模，从而缓解短缺。

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引用次数: 0