Stackelberg Game-Based Resource Allocation with Blockchain for Cold-Chain Logistics System

Cold-chain logistics system(CCLS)plays the role of collecting and managing the logistics data of frozen food.However,there always exist problems of information loss,data tampering,and privacy leakage in traditional centralized systems,which influence frozen food security and people’s health.The centralized management form impedes the development of the cold-chain logistics industry and weakens logistics data availability.This paper first introduces a distributed CCLS based on blockchain technology to solve the centralized management problem.This system aggregates the production base,storage,transport,detection,processing,and consumer to form a cold-chain logistics union.The blockchain ledger guarantees that the logistics data cannot be tampered with and establishes a traceability mechanism for food safety incidents.Meanwhile,to improve the value of logistics data,a Stackelberg game-based resource allocation model has been proposed between the logistics data resource provider and the consumer.The competition between resource price and volume balances the resource supplement and consumption.This model can help to achieve an optimal resource price when the Stackelberg game obtains Nash equilibrium.The two participants also can maximize their revenues with the optimal resource price and volume by utilizing the backward induction method.Then,the performance evaluations of transaction throughput and latency show that the proposed distributed CCLS is more secure and stable.The simulations about the variation trend of data price and amount,optimal benefits,and total benefits comparison of different forms show that the resource allocation model is more efficient and practical.Moreover,the blockchain-based CCLS and Stackelberg game-based resource allocation model also can promote the value of logistic data and improve social benefits.

Quantum Secure Undeniable Signature for Blockchain-Enabled Cold-Chain Logistics System

Data security and user privacy are two main security concerns in the cold-chain logistics system(CCLS).Many security issues exist in traditional CCLS,destroying data security and user privacy.The digital signature can provide data verification and identity authentication based on the mathematical difficulty problem for logistics data sharing in CCLS.This paper first established a blockchain-enabled cold-chain logistics system(BCCLS)based on union blockchain technology,which can provide secure data sharing among different logistics nodes and guarantee logistics data security with the untampered blockchain ledger.Meanwhile,a lattice-based undeniable signature scheme is designed to strengthen the security of logistics data and user privacy against quantum attacks.This scheme is based on the lattice assumption,which can provide anti-quantum security for BCCLS in the future quantum computer age.It also establishes the undeniable mechanism that guarantees that the actual signer cannot deny a valid signature.Then,security proof shows that this undeniable signature scheme is correct and safe,and an efficiency comparison shows that it is more efficient than other schemes in similar literature.The performance evaluations of transaction throughput and latency show that the proposed BCCLS is efficient and practical.This work can improve the security and efficiency of logistics data management and promote the reform and development of the logistics industry.

Optimization Model of Cold-Chain Logistics Network for Fresh Agricultural Products —Taking Guangdong Province as an Example

Cold-chain demand of fresh agricultural products is increasing in China, while network layout of cold-chain logistics is in disorder and its cost is huge. To address this problem, this paper casts an optimal model of cold-chain logistics network and tackles it with genetic algorithms. This optimal model takes running total cost of logistics network as the objective, and embeds a nonlinear mixed integer programming including two assignment issues. The model determines optimal layout and logistics management for pre-cooling stations and logistics center for fresh agricultural products. Our main contribution is to consider construction cost and operation cost of cold chain logistics simultaneously. Case study illustrates the effectiveness of the model.

The Construction of Cold-Chain Logistics Park of Agricultural Products in Sanshui from Two-stage Perspective

This paper firstly analyzed the operation model,market positioning,market demand forecast as well as market competition and challenges,park site selection,and transportation conditions for construction of the Cold-Chain Logistics Park of Agricultural Products in Sanshui.Then,it presented the overall planning scheme for construction of the Cold-Chain Logistics Park of Agricultural Products from a progressive two-stage perspective of overall planning and stage-by-stage implementation.The first stage mainly performs the function as a transaction platform of agricultural products and meanwhile provides customers with agricultural products storage and inspection services.The second stage adds value-added services such as distribution processing,modified atmosphere storage,freezing and refrigeration,market price information distribution,E-commerce of agricultural products and personalized services.It is expected to provide references and suggestions for the construction of the Cold-Chain Logistics Park of Agricultural Products.

Research on the Challenges of Cold-chain Logistics and the Combination Ways with Logistics O2O Operation

In this paper, we conduct research on challenges of cold-chain logistics and combination ways with logistics O2O operation. Because of the cold chain logistics to the high requirement of the equipment, technology as caused the high cost of cold chain logistics. In the overall cost of China’s logistics is on the high side, under the condition of low profi t, many enterprises to enter and don’t have much interest in the field of cold chain logistics. So-called cold chain logistics is frozen food in the production, storage, transportation, sales, remain the regulations to the consumption of each link in the cold chain environment, to ensure the food quality, reduce loss of food and system engineering. Under this basis, we propose the O2O based logistics pattern that will solve the issues well.

基于无线网络的农产品冷链物流温度监测系统研究

介绍了农产品冷链物流温度监控的必要性,根据系统总体需求分析、总体架构、整体功能和硬件方案设计了监控系统,并基于GPRS网络和ZigBee无线网络设计了系统的硬件部分,从而实现了整个监测系统的目标。试验结果表明:系统可以实时显示冷链温箱内部温度,且能对异常温度进行报警,具有可行性和准确性。

数字孪生赋能预制菜冷链发展的研究进展

疫情、宅经济助推预制菜所代表的“便捷化餐饮”新消费潮流。数字技术催生新的情景应用和价值创造,推动要素、流程和组织管理的创新,赋能产业升级。该研究分析我国预制菜冷链供应链中存在的产地预冷缺乏、信息要素不流通问题,比如冷链配套设施不足、冷链操作不规范、最后一公里配送及销售损耗。数字孪生模型可模拟和预测预制菜在冷链过程中的质量变化,引入物联网和区块链等技术后可实现产品的运输监控和追踪溯源。该研究提出利用数字孪生技术搭建预制菜的数字化冷链追踪溯源系统,实施预制菜冷链供应链的供应链、数字链、信任链和利益链的“链条化”发展,尝试探索一条适合我国预制菜发展的数字化道路,助力预制菜与冷链供应链的数字化转型和产业发展。

解决农产品配送“断链”的光伏冷链小车设计

在现有普通农用电动货运三轮车的基础上,通过增加1.3m^(3)保温车厢、600Wp太阳能电池板、4块12V100Ah蓄电池、110W直流压缩机等设备,先计算车厢从35℃降至-10℃所需要的冷量,再综合验证组件与蓄电池满足小车一天的制冷与行驶需求。通过精确的系统匹配及智能温度控制,改造成太阳能智能冷链物流小车,很好的解决了现在冷链物流配送中“最后一公里”空缺的问题,经过测试达到设计要求。本车可直接开到田间地头,有方便快捷、耐用、不付电费、造价低等优势,是现代农业物流冷链运输必不可少的中转设备,实现了农村鲜活农产品采摘−物流中心−用户的无缝对接。

价格竞争、保鲜努力与农产品电商冷链物流模式演化

科学合理的冷链物流模式是确保农产品电商价格、新鲜度竞争力的关键。针对涉及两农产品电商、电商自营冷链物流和第三方冷链物流商的供应链,构建两电商竞争、第三方冷链物流商主导的Stackelberg博弈模型及两电商冷链物流模式选择的演化博弈模型,并通过仿真揭示交叉价格弹性、新鲜度需求弹性、自营和第三方保鲜投入成本系数对演化路径的影响。研究表明:若交叉价格弹性、新鲜度需求弹性和第三方保鲜投入成本系数分别增大,自营冷链物流为演化稳定策略,电商倾向自营冷链物流。若自营保鲜投入成本系数增大,第三方冷链物流为演化稳定策略,电商倾向与第三方冷链物流商合作。

基于云模型的“一带一路”沿线省份国际冷链物流发展水平评价研究

在全球消费需求日益扩大的背景下,冷链产品进出口量剧增,为冷链物流提供新的发展机遇。为研究区域间国际冷链物流发展水平差异,考虑营商环境和地理因素,构建国际冷链物流发展水平评价指标体系,运用熵权-云模型对国际冷链物流发展水平进行评价,以“一带一路”沿线省份为例进行实证分析。结果表明:71%的省份国际冷链物流发展水平处于中上水平。在营商环境、基础设施和地理环境方面存在发展差异,其中进出口总额、冷藏车数、国际联系强度和对外开放水平是影响发展的主要因素。空间上,沿海省份国际冷链物流发展水平高于内陆省份,北部地区呈现“一核一副,周边聚集”的特征,东南沿海地区呈带状分布,西北地区呈现“中部低,两端高”的特征。

用于农产品冷链物流需求预测的GRA-WHO-TCN组合模型

[目的/意义]为了解决冷链物流需求预测在数字化转型中存在特征提取不充分、数据非线性程度高和算法易陷入局部最优等问题,提出一种结合灰色关联分析(Grey Relational Analysis,GRA)、野马优化算法(Wild Horse Optimizer,WHO)和时序卷积网络(Temporal Convolutional Networks,TCN)的组合预测模型,旨在解决需求预测精度不高的问题,以实现农产品供应链智能化管理。[方法]首先运用GRA对农产品冷链物流相关指标进行关联度筛选;其次采用TCN充分考虑农产品供应链中社会经济数据及物流信息中的时序性特征,并使用WHO对TCN模型超参数进行寻优;最后运用优化的GRA-WHO-TCN模型对浙江省冷链物流需求进行预测。[结果和讨论]采用WHO的时序算法TCN模型能够有效提取多维度数据的时序特征和空间特征,具备较好的拟合效果。与GRALSTM、GRA-TCN和GRA-WHO-LSTM模型相比,GRA-WHO-TCN冷链物流需求预测模型具有较低的均方根误差值(11.3)和有效的相关系数(0.95),且预测2016—2020年浙江省农产品冷链物流需求量分别为2980、3046、2487、2645和2799万吨,能够实现对冷链物流需求较高的预测精度。[结论]提出的GRA-WHO-TCN模型具备良好的优化和预测能力,能够为数字经济背景下农产品供应链物资流、信息流发展提供科学预测依据和实际参考价值。

非冷链商品配送路径优化研究--以京东配送为例

如何有效降低商品配送成本是物流企业的关注重点,学界已就带时间窗的商品配送路径优化算法展开了相关研究,但相关算法还存在着过早陷入局部最优或无法收敛的问题。由此提出一种改进的变邻域遗传搜索算法(VNS-GA),以非冷链商品配送为研究对象,构造起求解物流配送车辆路径规划的数学模型。首先,以配送成本和缺货惩罚成本的最小化作为实现目标,构建了包括车辆使用成本、配送运输成本和时间窗口惩罚成本的配送路径优化模型;其次,运用变邻域遗传优化算法来实现多目标物流配送路径的优化;最后,以京东某北京配送中心的物流配送为例,运用MATLAB软件对VNS-GA算法模型的科学性及有效性进行仿真验证。经实证,VNS-GA算法与传统算法相比具有更好的全局和局部搜索能力。研究期望为配送车辆调度与配送路径规划提供更优的路径选择模型,从而降低物流配送成本和减少便利店因缺货造成的损失。

生鲜农产品冷链仓储物流效率影响因素研究

由于生鲜农产品贮存期短、容易腐烂、变质等特点,对贮藏的温度、卫生状况有较高的要求,传统的物流方式不能保证生鲜农产品在一定的低温下贮存、运输。文章以A省为研究对象,根据对该省生鲜农产品生产现状、交通运输基础设施建设的分析,以数据包络分析方法探讨影响生鲜农产品冷链仓储物流效率的相关因素,并提出完善冷链物流基础设施建设、强化冷链仓储物流的信息系统、强化对冷链仓储物流专业人才加强培养、积极推动第三方冷链仓储物流企业发展、加强冷链仓储物流体系的标准化建设五项措施。

低碳多因素视角下的冷链配送路径优化

全球变暖问题日益凸显,如何减少冷链配送环节中的二氧化碳排放成为当今物流领域研究的重点和难点,文章考虑到冷链物流配送过程中产生的一系列成本和影响冷链物流配送环节中的二氧化碳排放,配送点软硬时间窗,配送道路实况等因素,并整合了我国现行碳排放权交易政策,从根本出发分析了目前我国低碳冷链物流的配送路径,构建了以配送环节总成本最小为目标的数学分析模型,最后通过设计方案以及算法模型拟合得到最优结果。从运行结果看出,采用较改进的遗传算法可以在一个周期内降低冷链物流配送的总成本,以此证明了提出的模型和改进算法的有效性。

乡村振兴背景下农产品冷链物流基础设施建设路径研究

加快农产品冷链物流基础设施建设是推动农产品冷链物流高质量发展,促进乡村产业振兴的重要途径。农产品冷链物流基础设施对延长农产品货架期和销售半径、降低损失率、构建全程冷链物流体系具有重要作用。在乡村振兴背景下,中国农产品冷链物流基础设施建设日益完善,但仍然存在总量不足、结构及分布不均衡、冷链意识有待提高、技术应用不足、标准体系不完善、发展政策落实不到位、建设主体能力不强等问题,应当从扶持建设主体、加强布局规划、提升冷链物流意识、推进先进技术应用等方面进行完善。

时间窗约束下农产品物流配送路径优化研究

农产品需求量增加对物流配送提出较高挑战,基于此提出时间窗约束下农产品物流配送路径优化方法研究。依客户预期服务时间需求,取混合时间窗约束函数确定时间窗、物流配送车辆最大载重、配送路径长度与物流配送车辆约束条件,构建农产品物流配送路径优化模型;基于农产品物流配送需求改进传统遗传算法,求解构建模型,即获农产品物流配送路径优化结果。实验结果显示:相较生鲜农产品多车型冷链物流车辆路径优化,所提方法最优农产品物流配送路径获取迭代次数更少、配送路径长度更短、总成本更低,应用性能更佳。

基于区块链技术的农产品冷链物流追溯系统解决方案

文中针对农产品冷链物流“信息不对称”“产品溯源难”“质量监管难”等现实难题,将区块链技术的共享机制、智能合约、去中心化、非对称加密等特性合理应用到农产品冷链物流中,主要从构建原则、模式、需求、架构设计、流程、功能等方面,提出构建基于区块链技术的农产品冷链物流追溯系统的解决方案。

基于组合预测法的云南省生鲜农产品冷链物流需求预测

冷链物流需求预测是区域冷链物流基础设施规划的基础工作,建立合适的预测模型,较为准确地预测生鲜农产品冷链物流需求量具有重要的现实意义。该文章在单一预测模型的基础上,通过熵值法赋予灰色预测GM(1,1)、时间序列ARIMA法和二次平滑指数法三种单一预测模型权重建立组合预测模型,利用云南省2009—2020年六类生鲜农产品生产量数据对2021—2030年相关物流量进行预测,预测结果表明组合预测法的预测精度要优于三种单一预测方法。该研究选用组合预测模型预测云南省冷链物流需求量,结果显示云南省生鲜农产品冷链物流需求保持一定幅度的线性增长趋势,年均增长率将达到2.94%。通过冷链物流基础设施对比得到云南省冷链物流基础设施和其他省份存在较大差距,难以满足生鲜农产品冷链物流需求日益增长的速度。本文从云南省政府、企业和农民的角度,提出加速云南省冷链物流发展的对策建议。

预制菜冷链物流快递配送问题及其对策

预制菜产业发展环境越来越好,市场规模越来越大,对冷链物流服务的要求也越来越高。当前,预制菜产业存在成本高、品控难、损耗大、时效差等问题,要通过完善网络建设、增加设施设备投入、推动产业融合发展、提供一体化服务等举措,打造预制菜冷链快递物流新生态,增强预制菜供应链的韧性。

考虑碳排放的冷链物流配送路径优化

在考虑传统经济成本的基础上增加考虑配送过程中可能产出的碳排放,并将其以碳排放成本的形式融入到目标函数中,建立考虑碳排放的冷链物流配送模型。通过动态调整启发因子和自适应信息素挥发因子对传统蚁群算法进行优化,提出一种新的改进蚁群算法。通过算例,将考虑碳排放与不考虑碳排放、改进与未改进蚁群算法的情况进行对比。结果表明,该模型和算法具有较好的寻优和收敛能力,可提高冷链物流企业经济效益。