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logistics回归模型的山洪泥石流风险评估

山洪泥石流作为一种常见的自然灾害,其突发性和破坏性给人类社会的生产生活带来了巨大的威胁。在全球气候变暖的背景下,山洪泥石流的发生频率和破坏力呈现增加趋势。通过采用有序logistics回归模型,对四川省北川羌族自治县地区山洪泥石流危险性进行了定量化评估,选取流域切割密度、流域相对高差、主沟长度、50年一遇泥石流规模等多个关键因素,构建了logistics回归模型进行危险性评估。根据模型结果发现,主沟长度和50年一遇规模的影响最为显著。本文不仅对山洪泥石流风险进行了较为精确的定量化评估,同时也为防治措施的制定提供了科学依据。

普外科术中低体温发生情况Logistics回归分析及预测模型构建

目的探讨普外科术中低体温发生的风险因素,构建并验证术中低体温发生的风险预测模型。方法选取2020年12月至2022年12月在本院接受普外科手术的117例患者作为观察对象。收集患者临床资料,根据患者术中是否发生低体温将其分为发生低体温组(A组)和未发生低体温组(B组)。Logistic回归分析影响患者普外科术中发生低体温的危险因素,并建立风险预测模型,受试者工作特征曲线(ROC)检测该模型的预测效能。结果117例患者中发生低体温31例(26.49%),未发生低体温86例(73.50%)。两组患者在年龄、体重指数、手术方式、ASA分级、术中输液量、手术室温、手术时间等方面比较,差异具有统计学意义(P<0.05)。Logistic回归分析结果显示,年龄≥65岁、术中输液量≥1000 mL、麻醉时间≥4 h、手术室温<23℃是普外科术中发生低体温的危险因素(P<0.05)。独立危险因素纳入Logistic回归分析并建立预测模型,模型预测概率P=1/[1+e(-1.020+0.874)×(年龄)+1.114×(术中输液量)+1.556×(手术室温)+1.453×(麻醉时间)]。ROC曲线检验该模型预测效能,结果显示ROC曲线下面积(AUC)=0.754(P<0.05);Hosmer-Lemeshow拟合优度检验显示,χ^(2)=1.001,P=0.998。结论患者年龄、术中输液量、麻醉时间、手术室温是普外科患者术中发生低体温的独立危险因素,Logistic风险预测模型拟合效度好,具有较高预测价值。

Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

Drone logistics is a novel method of distribution that will become prevalent.The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption,resulting in cost savings for the company’s transportation operations.Logistics firms must discern the ideal location for establishing a logistics hub,which is challenging due to the simplicity of existing models and the intricate delivery factors.To simulate the drone logistics environment,this study presents a new mathematical model.The model not only retains the aspects of the current models,but also considers the degree of transportation difficulty from the logistics hub to the village,the capacity of drones for transportation,and the distribution of logistics hub locations.Moreover,this paper proposes an improved particle swarm optimization(PSO)algorithm which is a diversity-based hybrid PSO(DHPSO)algorithm to solve this model.In DHPSO,the Gaussian random walk can enhance global search in the model space,while the bubble-net attacking strategy can speed convergence.Besides,Archimedes spiral strategy is employed to overcome the local optima trap in the model and improve the exploitation of the algorithm.DHPSO maintains a balance between exploration and exploitation while better defining the distribution of logistics hub locations Numerical experiments show that the newly proposed model always achieves better locations than the current model.Comparing DHPSO with other state-of-the-art intelligent algorithms,the efficiency of the scheme can be improved by 42.58%.This means that logistics companies can reduce distribution costs and consumers can enjoy a more enjoyable shopping experience by using DHPSO’s location selection.All the results show the location of the drone logistics hub is solved by DHPSO effectively.

A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog Elimination Framework

The diversity of data sources resulted in seeking effective manipulation and dissemination.The challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of computing.One of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search task.This research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO performance.On the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain performance.The proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant features.To confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve Bayes.Moreover,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different datasets.The proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.

Potential of Applying Artificial Intelligence to Hot Metal Logistics Management

The steel industry,known for its complexity and the need to reduce CO_(2)emissions,is adopting advanced digitalization tools to move towards a more sustainable,integrated,and agile operating model.Digital twins with artificial intelligence-based optimization and scheduling models can improve decision-making in logistics,refractory maintenance,and energy efficiency.By incorporating advanced AI algorithms into this decision support system,the hot metal route scenarios can be evaluated,resulting in minimized hot metal temperature losses and increased scrap utilization.This paper integrated digital twins with reinforcement learning algorithms to investigate the logistics of torpedoes and hot metal ladles.It considered important input parameters such as the ladles and torpedoes'thermal state and location,refractory thickness,hot metal volume and temperature,and crane availability.By incorporating advanced AI algorithms into this decision support system,energy-efficient scenarios can be evaluated,increasing scrap utilization and resulting in a possible reduction of 15°C in hot metal temperature losses.

ISO/TC 344 on innovative logistics set up in Qingdao

The 2024 International Standardization Conference on Logistics,the first of its kind in China,was held by China Federation of Logistics&Purchasing(CFLP)on May 29 in Qingdao,Shandong province,where ISO/TC 344,Innovative logistics,was officially set up.ISO President Sung Hwan Cho sent a congratulatory message via video.He Liming,Chair of CFLP,Zhao Shengcun,Deputy Mayor of Qingdao,officers from Standards Innovative Management Department of SAMR,and relevant leaders attended and addressed the meeting.Over 400 attendees participated in the conference,including representatives from the ISO Central Secretariat,members of ISO/TC 344,members of Asia-Pacific Logistics Federation(APLF),and representatives from national departments,industrial associations,research institutions,and logistics enterprises.ISO/TC 344 is responsible for the standardization of services,technological application,and management in the field of logistics.Its secretariat is held by China,the domestic counterpart of which is CFLP.

The heterogeneous impact of China-Europe railway express on the efficiency of logistics industry in node cities

Purpose-The spatiotemporal compression effect of China-Europe Railway Express(CR-Express)can reduce the filow costs of resources between China's node cities.Additionally,it can break through the limitations of low-added-value marine products,significantly impacting the logistics industry efficiency.However,there are few literature verifying and analyzing its heterogeneity.This study explores the impact of CR-Express on the efficiency of logistics industry in node cities and analyzes the heterogeneity.Design/methodology/approach-First,this study uses panel data to measure the efficiency of node city logistics industry.Secondiy,this study discusses the impact of the opening of CR-Express on the efficiency of logistics industry in node cities based on the multi-period differential model.Finally,according to the node city difference,the sample city experimental group is grouped for heterogeneity analysis.Findings-The results show that CR-Express can promote the urban logistics industry efficiency,with an average effect of 4.55%.According to the urban characteristics classification,the heterogeneity analysis shows that the efficiency improvement effect of logistics industry in inland cities is more obvious.The improvement effect of node cities and central cities in central and western China is stronger,especially in the sample of megacities and type I big cities.Compared with non-value chain industrial products,the CR-Express has significant promotion effects on the logistics efficiency of the cities where main goods are value chain products.Originality/value-Under the background of double cycle development,this paper can provide a scientific basis for the investment benefit evaluation of CR-Express construction and the follow-up route planning.

基于文本挖掘和二元Logistics回归的生物医药行业上市公司财务预警研究

本研究论文主要探讨了基于文本挖掘和二元logistics回归的生物医药行业上市公司财务预警研究。通过分析生物医药行业上市公司的财务数据和管理层讨论与分析(MD&A)文本,利用二元logistics回归模型和文本挖掘技术,研究构建了一套财务预警模型,以预测企业是否可能发生财务危机。研究选取了现金比率、现金流量负债比率、资产负债率、净资产收益率、营业毛利率、息税前营业利润率、总资产增长率、营业收入增长率、资本保值增率、每股经营活动产生的净流量增长率等财务指标,以及基于MD&A文本信息构建的语调指标作为模型的关键预警指标。这些指标涵盖了企业的多个财务维度,旨在全面评估公司的财务健康状况。模型在非ST公司的判断准确率达到了87.50%,在ST公司的判断准确率为80.00%,整体准确率为85.29%,显示了该模型对于早期识别财务风险具有一定的有效性。

Research on Smart Logistics Development Based on Blockchain Technology

Blockchain technology has been incorporated into the field of next-generation information infrastructure in China and is experiencing rapid development.Utilizing blockchain and other emerging technologies to develop intelligent logistics is essential for logistics enterprises to reduce costs,enhance efficiency,and improve quality.By analyzing and summarizing the issues within the development of China’s logistics industry,this paper discusses its growth from three perspectives:policy,technology,and industry.

Automobile Transportation Logistics Supply Chain Management Strategy

To enhance the management level and quality of the automobile transportation logistics supply chain and promote innovation and development in automobile transportation logistics enterprises,it is essential to strengthen the construction of the automobile transportation logistics supply chain management model.This can be achieved through the gradual improvement of the automobile transportation logistics management process,ensuring that the management of the automobile transportation logistics supply chain proceeds in an orderly manner.The aim is to improve automobile transportation and logistics service levels while meeting the changing market supply needs.This will enable automobile transportation and logistics enterprises to maintain steady economic benefits and enhance their core competitiveness in the market.Therefore,this paper has conducted a comprehensive exploration and research on managing the automobile transportation logistics supply chain.Corresponding management strategies are proposed as a starting point to achieve the aforementioned goals.

基于logistics回归分析的互助养老意愿影响因素研究

人口老龄化是我国今后较长一个时期的基本国情。为探究安徽省某市城镇居民参加社区互助养老服务的意愿影响因素,本文从个人、家庭、社会三个层面出发,构建互助养老服务意愿判别模型。结果显示,性别、婚姻状况、子女融洽程度、社区邻里关系等因素通过卡方检验。由二元logistics回归模型可知,家庭因素和社会支持因素影响居民参加互助养老意愿。因此,本文提出要加强互助养老服务的宣传,形成社会、社区和家庭的三合一互助养老体系。

基于多元logistics回归法探究绿色食品消费行为影响因素研究

绿色食品消费是实现双碳目标的重要途径之一。选择环保、健康的绿色食品,减少过度包装与消费,不仅降低碳排放,更呵护我们的环境。此举契合我国绿色发展战略,助力经济社会可持续发展。因此,倡导并推广绿色食品消费,对实现2030碳达峰、2060碳中和至关重要。成都市作为中国西南经济文化重镇,绿色食品发展成绩斐然。然而,挑战依旧严峻,消费者认知度低、产品质量参差不齐。深度研究成都市绿色食品市场至关重要,不仅增进消费者和企业了解,更为行业可持续发展提供新策略。本次调研深入成都市,通过问卷和实地调查收集消费者绿色食品购买行为数据。成功回收1246份有效问卷,回收率高达95.2%。数据经检验显示问卷设计合理,为分析提供了可靠依据。采用多元logistics回归模型,深入分析了个人特征、绿色食品认知、低碳发展认知及网络舆情感知等因素对绿色食品消费行为及频率的影响。

Development status and prospect of cold chain logistics of fruits,vegetables,and agricultural products based on intelligent technology

The cold chain in the production area of fruits and vegetables is the primary link to reduce product loss and improve product quality,but it is also a weak link.With the application of big data technology in cold chain logistics,intelligent devices,and technologies have become important carriers for improving the efficiency of cold chain logistics in fruit and vegetable production areas,extending the shelf life of fruits and vegetables,and reducing fruit and vegetable losses.They have many advantages in fruit and vegetable pre-cooling,sorting and packaging,testing,warehousing,transportation,and other aspects.This article summarizes the rapidly developing and widely used intelligent technologies at home and abroad in recent years,including automated guided vehicle intelligent handling based on electromagnetic or optical technology,intelligent sorting based on sensors,electronic optics,and other technologies,intelligent detection based on computer vision technology,intelligent transportation based on perspective imaging technology,etc.It analyses and studies the innovative research and achievements of various scholars in applying intelligent technology in fruit and vegetable cold chain storage,sorting,detection,transportation,and other links,and improves the efficiency of fruit and vegetable cold chain logistics.However,applying intelligent technology in fruit and vegetable cold chain logistics also faces many problems.The challenges of high cost,difficulty in technological integration,and talent shortages have limited the development of intelligent technology in the field of fruit and vegetable cold chains.To solve the current problems,it is proposed that costs be controlled through independent research and development,technological innovation,and other means to lower the entry threshold for small enterprises.Strengthen integrating intelligent technology and cold chain logistics systems to improve data security and system compatibility.At the same time,the government should introduce relevant policies,provide necessary financial support,and establish talent training mechanisms.Accelerate the development and improvement of intelligent technology standards in the field of cold chain logistics.Through technological innovation,cost control,talent cultivation,and policy guidance,we aim to promote the upgrading of the agricultural industry and provide ideas for improving the quality and efficiency of fruit and vegetable cold chain logistics.

基于逐步Logistics回归的高铁列车上座率影响因素分析

分析高铁列车上座率的影响因素,对于优化列车运行方案及提高铁路公司经济效益均具有重要意义。以京沪高铁2015年11月份的上座率数据为例,构建了基于逐步Logistics回归的高铁列车上座率影响因素分析框架;运用逐步回归策略筛选出对列车上座率有显著影响的因素;再应用Logistic回归模型分析了列车上座率与其影响因素之间的定量关系;最后分别采用Wald统计量和HL指标检验回归系数的显著性和模型的拟合优度。研究结果表明:列车跨线与否、列车类型、列车始发时间、列车终到时间和票价是影响影响京沪高铁列车上座率的主要因素。

105例不孕症患者子宫输卵管造影结果影响因素的Logistic回归分析

目的探讨不孕症患者子宫输卵管造影结果发生异常的影响因素。方法选取2021年1月至2023年5月在湖南中医药大学第二附属医院妇科门诊就诊并接受X线子宫输卵管造影(X-ray hysterosalpingography,X-HSG)检查的105例不孕症患者,收集患者临床资料包括年龄、月经周期、不孕症类型、支原体感染史、衣原体感染史、淋病奈瑟球菌感染史、盆腔炎相关病史、输卵管相关病史等,并填写《中医体质调查问卷表》,采用Logistic回归方程分析不孕症患者X-HSG结果的影响因素。结果X-HSG结果异常与盆腔炎相关病史、输卵管相关病史、年龄、气郁质及湿热质呈正相关(P<0.05),与不孕症类型、月经周期规律与否无相关性(P>0.05)。多因素Logistic回归分析结果显示:不孕症类型、月经周期、气郁质、湿热质是HSG发生异常的危险因素(OR>1),年龄、盆腔炎相关病史、输卵管相关病史是HSG发生异常的保护因素(OR<1)。结论适龄生育、减少盆腔炎相关病史、减少输卵管相关病史、调畅情志、忌食肥甘厚味对于减少输卵管病理损伤引起的不孕症至关重要。