To address uncertain demand during the pandemic, hospitals have utilized supply chain strategies by coordinating their available medical service capacity laterally. In this coordination, hospitals either request medical service capacity from external sources or mobilize part of their own capacity to support other hospitals, which influences the latter's capacity decisions. Optimizing these lateral coordination strategies and addressing challenges such as oversupply and inequity are critical issues in collaborative hospital responses. This paper examines how hospitals adjust their medical service capacity and transshipment capacity through proactive and reactive policies under the leveraging scheme of the Integrated County Healthcare Consortium (ICHC). We find that ICHC strategy decisions are influenced not only by demand size and the gap between hospitals but also by demand fluctuations. Additionally, even if hospitals engage in lateral coordination, their roles - either as a receiver or a source - are affected by both demand uncertainty and the ICHC's leveraging scheme. Regarding equity, we identify a hump-shaped relationship between the leveraging scheme of the ICHC, the quantity of service capacity transshipped, and equity. We propose a more balanced solution where the ICHC sets a scheme that allows the receiving hospital to dominate coordination decisions, thus benefiting both economic outcomes and equity.

This study addresses the challenge of enhancing viability of an interconnected supply chain network, particularly in the context of low-probability high-impact events that recur unpredictably. We re-examine the viability from the views of agility, resilience, and sustainability, and propose a novel hybrid approach which integrates dynamic network data and multi-echelon interaction. Diverging from traditional static approaches, we introduce a dynamic decision-making framework that strategically maintains long-term survival by coordination between timely response actions and the risk of overreaction. A data-driven hidden Markov model is built to update the risk forecasting via dynamic network data. A Bayesian network game theoretical model is developed to support collaborative risk mitigating via the multi-echelon interaction. The main findings are as follows. In the short term, we encourage enterprises to engage in collaborative risk mitigating to significantly increase the likelihood of reaching a consensus on achieving a more cost-efficient level of risk mitigation, marked by an intriguing interplay between weakened individual fairness and the tendency to mitigate network-wide risk more economically. In the long term, we advocate building a data-driven, structure-dynamic, and interaction-focused risk response timing system to enable the network to adapt to changes swiftly and achieve desired viable levels efficiently.

Online consumers prioritise swift and dependable deliveries but are also concerned about the environmental repercussions of e-commerce, such as carbon emissions and packaging waste. E-commerce firms, therefore, grapple with balancing short promised delivery times (PDT) and environmental sustainability in a competitive landscape. Through a game-theoretic lens, this study delves into the logistics choices of two rival e-commerce firms. These firms can either manage their own logistics or outsource to third-party logistics providers (TPLs) that have a green edge due to advanced eco-friendly technologies. Our findings reveal that if the e-commerce firms compete on demand, their logistics strategies depend on the TPLs’ levels of green technology readiness. Conversely, intense PDT competition can diminish the TPLs’ benefits, prompting e-commerce firms to handle logistics in-house. Regarding environmental sustainability, the outcomes depend on whether demand or PDT competition drives the firms’ choices. Notably, if both firms compete on PDT, the most sustainable outcome remains elusive. Our conclusions remain consistent even when tested further by model extensions.

针对电网物资供应链战略运营转型中面临的问题,基于供应链控制塔理论,首先,从数据治理到运营体系、从多跨场景到全局可视、从内部管控到外部协同,提出"双中台数治、两中心协作"的电网物资供应链数字控制塔模式.其次,面向运营分析决策、资源优化配置、风险监控预警、数据资产应用与应急调配指挥等供应链综合运营,开发大数据分析模型和智能决策工具,实现"数据业务双轮驱动、内外专业多跨协同"运营数智转型.最后,介绍了浙江电力宁波公司在废旧资产处置协同管控上的应用实践,表明了供应链数字控制塔模式对于电网物资供应链战略运营数智转型具有重要价值.

Low-carbon logistics is an emerging and sustainable development industry in the era of a low-carbon economy. The end-to-end deep reinforcement learning (DRL) method with an encoder-decoder framework has been proven effective for solving logistics problems. However, in most cases, the recurrent neural networks (RNN) and attention mechanisms are used in encoders and decoders, which may result in the long-distance dependence problem and the neglect of the correlation between query vectors. To surround this problem, we propose an improved transformer model (TAOA) with both multi-head attention mechanism (MHA) and attention to attention mechanism (AOA), and apply it to solve the low-carbon multi-depot vehicle routing problem (MDVRP). In this model, the MHA and AOA are implemented to solve the probability of route nodes in the encoder and decoder. The MHA is used to process different parts of the input sequence, which can be calculated in parallel, and the AOA is used to deal with the deficiency problem of correlation between query results and query vectors in the MHA. The actor-critic framework based on strategy gradient is constructed to train model parameters. The 2opt operator is further used to optimize the resulting routes. Finally, extensive numerical studies are carried out to verify the effectiveness and operation efficiency of the proposed TAOA, and the results show that the proposed TAOA performs better in solving the MDVRP than the traditional transformer model (Kools), genetic algorithm (GA), and Google OR-Tools (Ortools).

考虑电力物资需求计划的管理特性及其对实物储备补库阈值优化的影响,提出一种基于需求提报前延的实物储备补库阈值优化方法.首先,考虑物资需求计划提报各阶段物资需求的核定,将其作为对物资储备阈值数量的修正;其次,考虑电力建设项目物资需求水平与季节间的波次关系,借鉴关联规则分析方法和加权移动平均法,从历史订单中发现有关电力建设项目物资需求与季节的关联规则,获取月度储备系数;再次,考虑需求的季节分布,获取初始物资储备阈值,继而考虑物资需求计划提报前延,通过各阶段的需求修正获得实物储备补库阈值优化结果.实践应用表明,该方法能以较小的储备金额占用取得理想的储备保障作用,同时有效地提升了电力企业电力建设项目实物库存储备的精度和有效性.

在考虑食品质量链风险演变受多质量风险参量影响且各质量风险参量传递具有异构网络特性的基础上,基于食品生产工艺网络,以GERT单元与质量风险参量流表征各质量风险参量传递网络拓扑结构,引入层间交互邻接矩阵,构建食品质量链风险传播多层耦合网络模型.以质量风险参量和阈值区间的关系来表征质量风险的演化,用SIS模型模拟质量风险的传递,设计质量管理策略与风险参量评估指标开展食品质量链的质量风险控制与防范分析.研究结果表明本文所提方法能有效的反映食品质量链风险参量演变为食品质量风险的过程.同时,基于相关质量风险参量对应的质量管理改进和举措,如食品企业生产关键工艺的创新和改良,政府对食品生产过程的质量管制强化,可有效降低相关质量问题发生的概率,进而提高食品质量水平.

This paper studies the resilience of logistics network against node failures in the context of express industry owing to disruption in the network. By considering the flow capacity between the nodes and the impact of each node's failure, we propose a load redistribution mechanism in the presence of cascading failures which is akin to a criticality-based resilience assessment or stress testing the supply chain. To further investigate the impact of the node/nodes failure, we simulate and propose algorithms for two cascading failure scenarios, illustrating the different adjustment schemes for resilience improving strategies. A sensitivity analysis with managerial insights is also performed to investigate the effect of the adjustment schemes on the criticality of the nodes and the resilience of the express logistics network.

近年来,易腐食品质量安全问题引起了广泛关注.在易腐食品生产过程中开展适当的质量改进活动,是解决易腐食品质量安全问题的有效途径.然而,不同的质量改进活动决策需要不同的成本,并会产生不同的质量改进结果.本文拟从易腐食品生产过程的视角下寻找质量改进与成本消耗的平衡点,并找出关键的质量改进环节.考虑到易腐食品质量演变的动态属性和随机属性,本文提出了一种结合图示评审技术(GERT)和贝叶斯方法的方法,通过GERT来把握质量演变的不确定性,通过贝叶斯方法来评估质量和成本在质量改进活动决策后的动态变化.以乳制品为研究对象,本文构建了一个双目标优化模型以同时追求乳制品质量水平最大化和成本最小化,并用模糊目标规划方法求解该模型.算例分析验证了模型的有效性,并且探讨了质量和成本的权衡关系,最终找到了乳制品生产过程中的关键环节.

通过梳理电力物资仓储管理的多场景特点,结合电力物资出入库作业中人工经验的落后性,以及电力物资出入库策略管理与应用中的不足,提出一种基于"属性-规则-策略"组合的面向复杂仓储场景的电力物资出入库策略管理方案.首先设计了复杂仓储场景下的出入库优化策略管理方案及其策略设计逻辑,其次归纳了货位存放、物料存放和出入库策略等三类属性参数,并定义出入库规则与复杂场景规则组合设置,最后进行了出入库策略管理优化与开发实现.

通过梳理电力物资需求预测中存在的真实需求和计划需求、物资出库量和真实需求的不一致,以及电力物资需求的内外部影响问题,提出基于影响因素多维融合与贝叶斯概率更新的电力物资需求预测方法.首先分析了电力物资需求的内外部影响因素及其筛选,并按其对需求预测的影响程度进行权重赋值;其次设计了影响因素多维融合与贝叶斯概率更新的电力物资需求预测框架,介绍了贝叶斯概率更新的需求预测流程步骤;最后以温州市10kv配网项目的电力电缆需求预测为例进行算例说明.应用算例表明该方法能有效反映需求因素对电力物资需求变动的影响,符合电力物资需求特性,且具有很强的拓展性.

针对国网物流体系建设中工作思路、业务模式和技术装备等面临的挑战,结合国网战略目标和现代智慧供应链体系建设需要,首先通过对电网现代智慧供应链数字物流体系概念与内涵的界定,基于系统工程理论,提出涵盖物资要素、资源要素、主体要素、技术要素和信息要素的双螺旋模型,并从实体属性和数字属性两个层面对各要素进行分析;其次基于国网数字物流战略发展上的需求变化,分析数字物流体系构建要素演化内涵,提炼电网现代智慧供应链数字物流体系构建模式;最后结合浙江省电力公司嘉兴云海仓库数字物流体系构建的创新实践,表明了所提出的电网现代智慧供应链数字物流体系构建要素模型及其演化,可为电网现代智慧供应链数字物流体系构建提供理论分析依据及其管理实践提供创新方向指导.

针对产品替代情形下低碳供应链协调问题,考虑零售商利他行为偏好,建立完全自利型和零售商利他型决策模型,探讨零售商利他偏好、消费者对产品碳减排量的敏感度和替代产品价格敏感度对决策变量及协调性的影响.结果表明,利他型零售商在一定范围内通过降低单位低碳产品的利润来提高产品销量,提升消费者环境质量的敏感度,实现低碳供应链良性循环,消费者对产品碳减排量的敏感度越高,供应链整体利润越大.

Several logistics problems involving disaster relief have attracted growing research interest in the recent decade. A commonality among these problems is that demand-supply incongruence is always observed in post-disaster logistics operations due to the limited relief supplies and the randomly increasing relief demands. In such situations, the decision maker fails to meet the total relief demands simultaneously. This study employs a novel decision-making framework, where the traditional disaster relief logistics actions (e.g., vehicles routing and relief allocation) are replaced by periodic, sequential actions involving demand point location and assignment. A sequential approach allows the decision maker, in the face of every demand-point, to decide whether to locate and assign it to relief suppliers immediately or later, which sequentially influences the decision in the next period. A dynamic optimization model is built and solved by using particle swarm optimization algorithm. The results of a case study indicate the advantages of the sequential approach. (C) 2020 Elsevier Inc. All rights reserved.

针对国网现代智慧供应链"智能采购"业务链,构建对电力物资采购计划申报在管理模式、业务流程与技术手段的创新诉求,提出一种基于贯通"设计提-专业审-物资核"全线上业务流程的物资需求计划智慧申报模式,并对其进行系统开发实现.首先,分析了电力物资采购计划管理痛点及现有的需求计划申报流程;其次,立足现代智慧供应链系统智慧申报功能建设,归纳了智慧申报模式的功能需求,并进行了模式要点和业务流程设计;最后,提出了智慧申报系统的建设方案,并进行了系统开发实现与实践应用成效分析.

"双一流"建设为省属高校学科建设与发展创造了新的机遇,省属高校可借此机会缩短自身与部属重点大学在部分学科上的差距.本研究以管理科学与工程学科(以下简称管工学科)为例,基于青塔"学科云数据平台"的学科指标数据,分析省属高校与部属高校及管工一流学科高校的差距,并采用聚类分析与多维尺度分析法,探讨省属高校管工学科发展的特点与趋势.研究发现,省属高校管工学科因发展水平差异被分为两大类,即:各方面发展均较差的高校和在某些方面有优势的高校,前者的学科评估排名下滑严重,而后者则能维持或提升.师资队伍与平台建设是省属高校普遍存在的短板,但东部沿海发达地区部分高校因在奖励与资源投入上有充足的经费保障,却在这两个方面有优势;管工学科发展历史悠久的传统高校学科发展优势更多体现在人才培养、社会服务与学科声誉等方面.省属高校应根据自身特点,因地制宜地制定管工学科发展策略,不断提升学科发展水平.

本文提出了一种基于质量链视角的食品质量管理新范式.首先,论证了食品质量演变具有多主体、多阶段、不确定的复杂系统特征.其次,构建了一个基于GERT和复杂网络双网整合的食品质量链网络.该网络由质量环节层级和影响要素层级两部分构成,其中质量环节层级对应食品质量演变过程,由GERT网络来表示;影响要素层级对应质量影响要素与质量环节层级之间的连接以及质量影响要素内部的连接,由复杂网络来表示.在此基础上,进一步提出了食品质量管理新范式.通过搭建双网融合、整体优化的食品生态网络架构,形成双网联动、技术主导的食品质量演变过程,继而实现双网协同、多方共治的食品质量协同控制,最后达成双网更新、数据驱动的食品安全风险管理.

结合现有研究结果,面向在线学习模式下的课外读物推荐,通过文献研究和问卷调查,围绕在线学习能力的显性和隐性两维度,基于层次分析模型构建了物流专业大学生专业学习能力评价指标体系,并以物流专业大学生为例分析了在线学习模式下的用户专业学习能力,并从指标体系的完善以及研究方法等方面为提高课外学习成效及能力的相关研究提出了相关建议.

通过梳理业扩配套项目物资供应中实物储备实施中存在备货准确性偏低、供需联动不到位和需求分析的精度和物资供应的柔性有待进一步提高等问题,提出基于业扩配套项目需求画像的实物储备库存清单化管理的工作模式.首先设计了业扩配套项目需求标签和基于模糊C均值算法的项目聚类,其次论述该工作模式下业扩配套项目物资需求画像的技术方法,并在此基础上提出基于业扩配套项目物资需求结构分析的储备清单优化,最后结合余杭公司实践情况对该方法进行论证.实践表明该方法能有效提高业扩配套项目实物储备库存管理的有效性,进而支持个性化客户服务.