TOWARDS REAL-TIME CUSTOMIZED MANAGEMENT OF SUPPLY AND DEMAND CHAINS

Our focus herein is on developing an effective taxonomy for the simultaneous and real-timemanagement of supply and demand chains.More specifically,the taxonomy is developed in terms ofits underpinning components and its research foci.From a components perspective,we first considerthe value chain of supplier,manufacturer,assembler,retailer,and customer,and then develop aconsistent set of definitions for supply and demand chains based on the location of the customer orderpenetration point.From a research perspective,we classify the methods that are employed in themanagement of these chains,based on whether supply and/or demand are flexible or fixed.Interestingly,our taxonomy highlights a very critical research area at which both supply and demandare flexible,thus manageable.Simultaneous management of supply and demand chains sets the stagefor mass customization which is concerned with meeting the needs of an individualized customermarket.Simultaneous and real-time management of supply and demand chains set the stage forreal-time mass customization(e.g.,wherein a tailor first laser scans an individual's upper torso andthen delivers a uniquely fitted jacket within a reasonable period,while the individual is waiting).Thebenefits of real-time mass customization can not be over-stated as products and services becomeindistinguishable and are co-produced in real-time,resulting in an overwhelming economicadvantage.

Prediction on Cold Chain Logistics Demand of Urban Residents in Jiangsu Province during the Twelfth Five-Year Plan Period——Based on Estimates of GM(1,1) Model

This paper takes the total yield of products that need refrigerated transport as the impact factors of transport aggregate of cold chain logistics,such as meat,aquatic products,quick-frozen noodle,fruits,vegetables,dairy,and medicine.Through selecting the consumption data of urban residents on transported products via cold chain in Jiangsu Province from 2005 to 2000 as sample,this paper establishes grey prediction model GM(1,1) of cold chain logistics demand and uses DPS7.05 software for test,to predict the cold chain logistics demand of urban residents in Jiangsu Province during the Twelfth Five-Year Plan period.The results show that in the period 2010-2015,the cold chain logistics demand of urban residents in Jiangsu Province is 1 151.589 1,1 185.136 6,1 219.661 3,1 255.191 8,1 291.757 3,1 329.388 1 t respectively;in the period 2005-2010,the cold chain logistics demand of urban residents in Jiangsu Province increases at annual growth rate of 3.9%;in the period 2011-2015,the growth rate declines to some extent,increasing slowly at rate of 2.9%.

Supply Chain Network Equilibrium with Revenue Sharing Contract under Demand Disruptions

Contract is a common and effective mechanism for supply chain coordination,which has been studied extensively in recent years.For a supply chain network model,contracts can be used to coordinate it because it is too ideal to obtain the network equilibrium state in practical market competition.In order to achieve equilibrium,we introduce revenue sharing contract into a supply chain network equilibrium model with random demand in this paper.Then,we investigate the influence on this network equilibrium state from demand disruptions caused by unexpected emergencies.When demand disruptions happen,the supply chain network equilibrium state will be broken and change to a new one,so the decision makers need to adjust the contract parameters to achieve the new coordinated state through bargaining.Finally,a numerical example with a sudden demand increase as a result of emergent event is provided for illustrative purposes.

Supply Chain Demand Forecast Based on SSA-XGBoost Model

Supply chain management usually faces problems such as high empty rate of transportation, unreasonable inventory management, and large material consumption caused by inaccurate market demand forecasts. To solve these problems, using artificial intelligence and big data technology to achieve market demand forecasting and intelligent decision-making is becoming a strategic technology trend of supply chain management in the future. Firstly, this paper makes a visual analysis of the historical data of the Stock Keeping Unit (SKU);Then, the characteristic factors affecting the future demand are constructed from the storage level, product level, historical usage of SKU, etc;Finally, a supply chain demand forecasting algorithm based on SSA-XGBoost model has proposed around three aspects of feature engineering, parameter optimization and model integration, and is compared with other machine learning models. The experiment shows that the forecasting result of SSA-XGBoost forecasting model is highly consistent with the actual value, so it is of practical significance to adopt this forecasting model to solve the supply chain demand forecasting problem.

Return Contract of Supply Chain with Fuzzy Continuous Demand

In a two-stage supply chain composed of one supplier and one retailer,the supply chain coordination mechanism in a fuzzy continuous demand environment is researched.A positive triangular fuzzy number is used to model the external market demand.Using the method of fuzzy cut sets theory,both fuzzy decentralized and centralized decision-making processes are analyzed,and another model of fuzzy return contract is proposed to help coordinate such supply chain.It is shown that in fuzzy environment there exists a unique solution of the retailer＇s optimal order quantity,the double marginalization problem can be solved by providing different tactics for wholesale pricing and return pricing,and the fuzzy expected profit of each actor can be expected to improve in the return contract.Finally,a numerical example is given to illustrate the models and the solution-seeking process.

智慧健康养老产业的现实需求与发展进路

智慧健康养老产业高质量发展是深入实施健康中国战略和积极应对人口老龄化国家战略的重要内容。基于智慧健康养老产业的供需分析框架,分析智慧健康养老产业的现实需求、供给现状,发现智慧健康养老产业供给不平衡、不充分,产业链环节衔接不当,智慧健康养老产品的数字鸿沟难以跨越,智慧健康养老服务的专业人才匮乏,政府和市场的协同合作机制不健全等。据此提出以需定供,提升产业供给质量;整合优势,构建稳定高效产业链;智享养老,推进数字无障碍建设;人才为本,夯实高素质专业队伍;协同发力,推动有效市场和有为政府更好结合等。

质量基础设施服务平台研究与实践经验分享

本文以湖北省市场监管局整合“基础性服务、拓展性服务、融合性服务、政务性服务”四类资源构建“一站式”质量基础设施服务平台为实际应用案例进行研究,采用面向需求导向的方法,厘清企业、服务站、技术机构和市场监管部门的逻辑关系,梳理一站式平台的定位,助企纾困,为企业提供“零距离”的“一站式”质量基础设施服务,进一步拓展质量技术资源服务一张网的建设。提出基于价值链方法,分阶段有序构建“一站式”服务平台,线上线下一体化运营,监管与服务融合发展,统筹推进“智慧服务一张网”建设,解决中小企业质量服务“三难找”、质量技术机构“小散弱”等问题,助力中小企业提质增效,促进国内外大循环健康有序发展。

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。

基于报童模型的供应链网络均衡决策研究

在不确定性需求下构建了基于报童模型的两层供应链网络,供应链网络是由原料供应商、产品生产商和需求市场构成。针对不确定性需求引入报童模型到供应链网络均衡模型中,用于供应链网络中厂商的产量和价格决策。模型构建了基于报童模型的变分不等式来表达供应链网络在不确定性需求下的均衡条件。最后,通过数值案例给出了需求均匀分布下,方差对于产品价格、原料供应商产品流量的影响分析。

“双循环”促进利用外资“稳中提质”的效应评估

受日趋复杂和严峻的外部环境变化冲击以及内部传统低成本优势不断丧失的影响,近年来,中国利用外资虽面临挑战,但与全球对外直接投资下滑相比却成功实现了“逆势上扬”,其根本逻辑在于“双循环”能够形成吸引外资的新优势。具体而言,超大本土市场规模优势下的产业配套能力提升和消费需求规模的扩大、更高开放水平下的国际循环畅通以及二者的相互作用,高度契合了全球价值链分工条件下跨国公司布局全球生产网络,尤其是布局高端生产环节和阶段的现实需求,在利用外资上即表现为“稳中提质”。在创新性地对国内国际双循环进行定量和有效测度的基础上,进一步开展的计量检验结果证实了上述理论预期的正确性,即“双循环”能够显著促进利用外资“稳中提质”,并且主要通过更加畅通的国内循环和国际循环及其二者相互促进的机制发挥作用。在经济全球化新形势下和中国迈入高质量发展新阶段后,为充分发挥外资在现代化建设中的作用,中国应加快构建新发展格局,依托超大本土市场规模优势,在实施扩大内需战略、加快国内市场一体化和制度创新的同时积极参与全球生产网络和价值链分工体系,以形成利用外资“稳中提质”的新优势。

广东省水产预制菜冷链物流需求分析及预测

为预测广东省水产预制菜冷链物流的市场需求,从区域经济发展水平、市场供需水平、交通运输水平、冷链技术水平4个方面构建水产预制菜冷链物流需求评价指标,采用灰色关联分析法研究影响水产预制菜冷链物流需求变化的主要因素,分别采用灰色模型(grey model,GM)中的一阶一元微分方程GM(1,1)与长短时记忆(long short-term memory,LSTM)神经网络对比分析2015—2021年广东省水产预制菜冷链物流需求。结果表明:影响广东省水产预制菜冷链物流需求发展的主要影响因素为货物周转量和冷链冷藏水平;GM(1,1)、LSTM神经网络预测结果的平均相对误差分别为2.68%、0.22%,后者的预测准确度明显优于前者;采用LSTM神经网络预测2022—2024年广东省水产预制菜冷链物流需求,广东省水产预制菜需求呈上升趋势,预计2024年将达到509.09万t。广东省应立足冷链基础设施建设,确保贮藏、运输过程中水产预制菜温度稳定,加强水产预制菜食品监督,保证食品质量安全,不断促进水产预制菜冷链产业的发展。

多周期农产品废弃物供应链网络均衡模型构建

目的研究农产品废弃物可持续利用问题,既实现供应链整体利润最优,又减轻对环境的污染。方法在随机需求的背景下,考虑生产合作社对零售商的不同激励度,分析生产合作社、零售商、需求市场的最优状态,利用变分不等式建立相应的多周期供应链网络均衡模型。结果从多周期角度,实现了农产品废弃物供应链网络均衡利益最优化,可为合作社与零售商在较长时间达到一种均衡状态提供有效解决方案。结论既实现了多周期农产品废弃物的持续利用,又促进了循环经济的发展,同时还实现了供应链网络均衡、供应链整体利润最优和减轻环境污染等目标。

安徽省生鲜农产品冷链物流需求预测研究

生鲜农产品等冷链产品市场需求快速增长,冷链物流的供给无法满足人们的需求给生鲜农产品带来新的挑战.安徽省作为一个农产品丰富的地区,生鲜农产品的供应对于满足市场需求至关重要.收集了2001~2022年生鲜农产品产量数据,采用反向传播神经网络(Back Propagation Neural Network,BP神经网络)、长短时记忆(long short-term memory,LSTM)、粒子群算法优化的长短期记忆神经网络(Particle Swarm Optimization-Long Short-Term Memory,PSO-LSTM)三种模型进行训练和验证,通过三种模型的对比分析,三种模型相对误差分别为0.13%、0.06%、0.02%.结果表明,PSO-LSTM模型预测精度最高,拟合效果最好,能够有效预测未来四年安徽省生鲜农产品冷链物流需求,以应对不断增长的冷链物流需求压力.

数字技术对制造业全球价值链分工地位升级影响研究

随着数字技术进步及其在经济各领域的快速应用,其对产业全球价值链(GVC)地位升级的推动作用日益显著。基于OECD-TiVA联合发布TiVA数据库2006—2018年的数据,以64个经济体为研究样本,实证检验数字技术对制造业GVC分工地位升级的影响。研究结果显示:数字技术显著促进制造业GVC分工地位的升级;提高劳动生产率、优化人力资本结构以及刺激消费需求,是数字技术促进制造业GVC分工地位升级的作用机制。异质性分析表明:数字技术对于低互联网发展水平以及中低收入经济体GVC分工地位升级的促进作用更为明显。据此提出,增强数字技术对我国制造业GVC分工地位升级的促进作用,应大幅提升我国数字技术创新和应用能力;增强贸易规则话语权,推动“数字贸易”发展;加快培养数字技术人才,加速推动消费结构升级。

PI环境下考虑节点失效与动态需求的供应链网络韧性优化研究

在逆全球化、百年变局的大背景下,追求低成本精益化管理、零库存目标造成的供应链网络拉伸,使得供应链的局部脆弱性问题得以暴露,研究如何建立韧性供应链网络并进行优化变得至关重要。实物互联网(Physical Internet,PI)环境下的物流模式具有很强的开放性、全局性和协作性,文章结合实际供应链运转过程中存在的节点失效以及市场动态需求变化等问题,采用情景法对可能的影响因素进行描述,构建了PI环境下考虑节点应变能力的韧性供应链网络优化模型,并应用改进后的GA-BPSO算法对模型进行求解。通过实证算例证明了模型的可行性及算法的有效性,可以为企业进行韧性供应链优化提供科学决策参考。

基于BP神经网络的云南花卉物流需求预测

文章首先对云南花卉市场进行现状分析,在此基础上以近10年来云南花卉总产值为变量依据,来预测云南花卉的未来物流需求量情况。文章提出了可能会影响花卉物流需求量的8个因素,运用BP神经网络预测法并结合近10年的云南花卉总产值对未来3年的需求量进行预测。预测结果表明,未来几年,云南花卉市场对于物流的需求不降反增。而作为鲜活植物产品,花卉的运输又对冷链物流提出了更高的要求。因此,提高冷链物流的技术势在必行。

A closed-loop Supply Chain Network Equilibrium Model with Fuzzy Demand under Production Capacity Constraints and Price Rigidities

A closed-loop supply chain network equilibrium problem is examined,which consists of mutual competitive manufacturers with production capacity constraints and retailers with fuzzy market demands,mutual competitive collectors as well as a binding price ceiling of the commodities.By utilizing the credibility measure of fuzzy event,variational inequality and Lagrange dual theory,the optimum behaviors of manufactures,retailers,collectors and consumers are described.Therefore,the supply chain network equilibrium model is established.Numerical examples were given to illustrate the impact of production capacity constraints and price ceiling on the network equilibrium pattern.The results show that the shortage of commodities in consumer market will be more serious,the wholesale price of product and purchase price of waste products rise,the profits of retailers decrease,the profits of manufacturers and collectors increase as the government gradually reduce the binding price ceiling on competitive markets,and the trend will be more obvious in the existence of production capacity constraints at same time.

基于需求链的中欧班列开行方案优化

中欧班列是往来于中国与欧洲以及一带一路沿线各国的集装箱国际铁路联运班列,自开行以来,双方在“一带一路”的框架下展开了卓有成效的合作。从目前发展形势来看,货运服务将迎来更加广阔的前景,因此开行方案的编制尤为重要,开行方案编制通常以铁路运营方经济效益为出发点,很少考虑运营方与客户双方需求。在平衡铁路运营方和客户双方需求的基础上,提出基于需求链的中欧班列开行方案优化方法。开行方案编制分为两阶段实现,首先基于K短路原则生成备选集,得到初始中欧班列开行方案解集合,可有效提高模型求解效率;其次基于“一弧多服务多货流”网络来构建双层规划模型,并设计在粒子群算法中嵌入拉格朗日松弛算法进行求解,可有效简化复杂的原有模型。上层模型从铁路运营方角度出发,考虑货物运输时间、碳排放、能力限制等约束,以实现运输效益最大化;下层模型根据实际客户需求,拓展为允许货流拆分的物流服务选择模型。通过上下层模型交互体现供需双方的博弈行为,使需求链管理思想在中欧班列开行方案中得以运用。算例表明,货流允许拆分情况下,铁路运营方利润增加41.67%,充分证实了本模型的优越性。

需求信息不对称背景下双渠道供应链信息甄别模型

越来越多的制造商主动通过市场调研等途径来获取需求信息。特别是在双渠道供应链中,制造商通过直销渠道将产品销售给消费者,获得了大量销售数据,为其需求预测提供有力支撑。鉴于此,考虑制造商拥有私有需求信息的实际情况,构建由一个制造商和一个零售商组成的双渠道供应链,分别基于两部定价契约和质量激励契约来构建信息甄别模型,研究实现制造商需求信息共享的最优契约方案。进一步通过对比双渠道供应链成员的均衡决策和事前期望利润,讨论了两种契约方案的效率,以及需求信息不对称对双渠道供应链产生的影响。研究表明,制造商掌握私有需求信息不利于提高产品质量水平,但产品的批发价格小于信息对称时的批发价格。需求信息不对称下,制造商在获得保留利润的同时能够获得信息租金,而零售商也能够通过合理的契约方案设计,在一定条件下获得比信息对称时更高的事前期望利润。因此,满足一定条件,双渠道供应链的性能在需求信息不对称时相对于需求信息对称时更优。

基于居民出行模拟的电动汽车负荷时空分布预测

针对电动汽车充电负荷时空分布预测中的随机性、不确定性问题,文中提出一种结合出行链理论和实际地理信息的电动汽车充电负荷预测方法。基于路网融合及出行链理论,对电动汽车充电需求的时空特性建立模型,以此模拟用户的出行行为特性。同时,通过对目标区域的路网进行建模,按功能区进行划分,将出行链理论的用户行为特性与目标地理信息相结合,通过Floyd算法对电动汽车用户的出行路径进行规划设计,以预测电动汽车充电需求负荷。算例结果表明,所提出的模型能够基于实际地理信息,预测电动汽车充电负荷变化规律,分析不同功能区、不同行政区域下的电动汽车充电需求负荷特性。仿真结果验证了所提模型和方法的有效性。