FROM MANUFACTURING SCHEDULING TO SUPPLY CHAIN COORDINATION:THE CONTROL OF COMPLEXITY AND UNCERTAINTY

With time-based competition and rapid technology advancements, effective manufacturing scheduling and supply chain coordination are critical to quickly respond to changing market conditions. These problems, however, are difficult in view of inherent complexity and various uncertainties involved. Based on a series of results by the authors, decomposition and coordination by using Lagrangian relaxation is identified in this paper as an effective way to control complexity and uncertainty. A manufacturing scheduling problem is first formulated within the job shop context with uncertain order arrivals, processing times, due dates, and part priorities as a separable optimization problem. A solution methodology that combines Lagrangian relaxation, stochastic dynamic programming, and heuristics is developed. Method improvements to effectively solve large problems are also highlighted. To extend manufacturing scheduling within a factory to coordinate autonomic members across chains of suppliers, a decentralized supply chain model is established in the second half of this paper. By relaxing cross-member constraints, the model is decomposed into member-wise subproblems, and a nested optimization structure is developed based on the job shop scheduling results. Coordination is performed through the iterative updating of cross-member prices without accessing other members' private information or intruding their decision-making authorities, either with or without a coordinator. Two examples are presented to demonstrate the effectiveness of the method. Future prospects to overcome problem inseparability and improve computing efficiency are then discussed.

A MEASURE OF SUPPLY CHAIN COMPLEXITY INCORPORATING VIRTUAL ARCS

Increased globalization, as well as the ability to have virtual supply chain partners, has had numerous effects on supply chains. While some of these effects are positive, making more resilient supply chains, there are also the negative effects of scale ~nd complexity, making these supply chains more challenging than ever to manage. Having a means to measure the complexity is crucial for today＇s managers to make more informed decisions. This measure must not only account for the number of arcs, but the amount of information and material carried on it, as well as incorporate the benefit that virtual arcs add to the network by increasing efficiency and reducing information, product and financial transfer costs and time. This research utilizes newer models in network clustering and complexity theory to make them applicable to supply chains and creates a new, practical approach to measuring supply chain complexity which can be easily implemented by practitioners.

Dynamic decision and its complex dynamics analysis of low-carbon supply chain considering risk-aversion under carbon tax policy

This study establishes a low-carbon supply chain game model under the centralized decision situation and the decentralized decision situation considering the manufacturer risk-aversion behavior, and discusses the influence of the manufacturer risk-aversion behavior on the optimal decision, profit, coordination, and complex dynamics of the supply chain. We find that comparing with the risk-neutral decentralized decision, the increase of manufacturer's risk tolerance attitude can narrow the gap between the supply chain profit and the centralized decision, but it will further reduce the carbon emission reduction level. The increase of risk tolerance of the manufacturer and carbon tax will narrow the stable region of the system. Under this situation, the manufacturer should carefully adjust parameters to prevent the system from losing stability,especially the adjustment parameters for carbon emission reduction level. When the system is in a chaotic state, the increase of carbon tax rate makes the system show more complex dynamic characteristics. Under the chaotic state, it is difficult for the manufacturer to make correct price decision and carbon emission reduction strategy for the next period, which damages its profit, but increases the profit of the retailer and the supply chain. Finally, the carbon emission reduction cost-sharing contract is proposed to improve the carbon emission reduction level and the supply chain efficiency, achieving Pareto improvement. The stability region of the system is larger than that in the centralized decision situation, but the increase of the cost sharing coefficient will reduce the stability of the system in the decentralized decision-making situation.

Supply chain management research directions for future development

With the rapid development of electronic commerce, supply chain management is facing more and more new challenges. Therefore, it is particularly important to study the development of clear direction of supply chain. However, the supply chain is composed of different interest subjects, each subject in order to achieve the maximization of their own interests and adopt different measures, is a complex, huge system, has brought the huge challenge to the supply chain management. In this paper, the research on Supply Chain Management in the current situation, characteristics and the modem supply chain management are summarized, and combined with new challenges of supply chain management to predict future research direction is the development of supply chain management, in order to make the supply chain management to the greatest extent satisfy the consumer e-commerce mode increasingly popular.

Supply Chain Finance Credit Risk Evaluation Method Based on Self-Adaption Weight

Credit risk is the core issue of supply chain finance. In the supply chain, problems happened in different enterprises can influent the whole to different degrees through transferring, thus statuses of all enterprises and their different influences should be considered when evaluating the supply chain’s credit risk. We examine the characters of supply chain network and complex network, use the local growing complex network to simulate the real supply chain, use cluster analysis to classify the company into several levels;Introducing each level’s self-adaption weight formula according to the company’s quantity and degrees of this level and use the weight to improve the credit evaluation method. The research results indicate that complex network can be used to simulate the supply chain. The credit risk evaluation (CRE) of an enterprise level with bigger note degrees has a greater weight in the supply chain system’s CRE, thus has greater effect on the whole chain. Considering different influences of different enterprise levels can improve credit risk evaluation method’s sensitivity.

Empirical topological investigation of practical supply chains based on complex networks

The industrial supply chain networks basically capture the circulation of social resource, dominating the stability and efficiency of the industrial system. In this paper, we provide an empirical study of the topology of smartphone supply chain network. The supply chain network is constructed using open online data. Our experimental results show that the smartphone supply chain network has small-world feature with scale-free degree distribution, in which a few high degree nodes play a key role in the function and can effectively reduce the communication cost. We also detect the community structure to find the basic functional unit. It shows that information communication between nodes is crucial to improve the resource utilization. We should pay attention to the global resource configuration for such electronic production management.

B2B2C供应链物流-订单流复合网络鲁棒性研究

基于渗流理论,考虑节点的渗流容量和受上下游失效节点的影响不同,设计了复合网络上下游级联失效策略,采用平均最短路径长度、最大连通子图率和网络全局效率评估B2B2C复合网络的鲁棒性。仿真表明:随着渗流容量系数的增加,网络鲁棒性增强;复合网络对于蓄意攻击的抵抗性较差,平均最短路径长度、全局效率和最大连通子图率呈断崖式下降到0,网络基本瘫痪,而面对随机攻击则具有较好的鲁棒性;与物流网络相比,复合网络平均度低40.6%,幂指数高12.1%,鲁棒性较好。

基于复杂网络的突发事件下汽车产业供应链韧性研究

汽车产业供应链中,各企业间由于合作伙伴关系或者竞争关系而产生的交互作用影响整个供应链网络,加之其参与主体众多,更易受到各种突发事件的干扰影响网络韧性。文章以复杂网络模型为基础,收集中国经济金融研究数据库数据库汽车供应链板块中141家车企数据构建复杂网络关系矩阵模型,通过复杂网络特性分析对所构建的网络模型进行检验。采用目标干扰和随机干扰两种方式来模拟突发事件产生的供应链中断情景,由矩阵工厂和大型复杂网络分析工具对网络进行仿真实验,通过最大连通子图所表示的弹性性能和效率性能两项数据来观测网络稳定性,得出提升汽车产业供应链韧性的方法。

新能源汽车供应链安全攻击模拟:对提高鲁棒性的影响

汽车供应链面临日趋复杂的环境,以鲁棒性视角分析供应链的抗干扰能力,对提高我国新能源汽车供应链的安全性和稳定性有重要意义。文章根据我国销量排行前10的新能源汽车企业,挖掘其上下游企业的合作关系,采用复杂网络理论构建我国新能源汽车供应链网络模型。首先,从复杂网络特征指标度与度分布、平均路径长度、聚类系数对网络拓扑结构进行分析;其次,设计随机攻击策略和基于度值、介数的蓄意攻击策略,对新能源汽车供应链网络鲁棒性进行分析。结果表明,我国的新能源汽车供应链网络不仅具有小世界网络特性,还具有无标度网络特性,面对随机攻击时有较强的鲁棒性,面对蓄意攻击时又显得很脆弱,基于介数的攻击策略对新能源汽车供应链网络的影响略大于基于度值的攻击策略。最后基于仿真结果,提出增强新能源汽车供应链鲁棒性的建议。

供应链关系与企业数字化转型——基于动机与能力双重视角的分析

从上下游供应链视角探索企业数字化转型的影响要素是破解当前数字化转型实践中企业“不愿转、不敢转、不会转”难题的新思路,本文围绕供应链关系对企业数字化转型的可能影响及作用机理展开实证考察。研究结果表明,在考虑内生性等问题后,供应链集中度对企业数字化转型存在负向影响。机制检验结果表明,随着供应链集中程度的加大,一方面企业开展数字化转型的动机容易因弱化的研发动力与简单的业务体系而受到抑制,另一方面企业参与数字化建设的能力容易因密集的专用性资产与不良的信息透明度而受到损害。在动机与能力双重机制的作用下,集中的供应链形态不利于企业数字化转型程度提升,且这种影响效应受企业内外部要素的调节,在非国有、处于高度市场化水平环境的企业中更为突出。本文为企业从供应链关系管理维度加快推进数字经济发展提供了一定启示。

国际化、供应链复杂性与供应链韧性

本文基于交易成本理论和生存分析模型,从抵御能力和恢复能力对供应链韧性进行量化分析,探究国际化程度对供应链韧性的影响,并考察供应链结构中的供应商复杂性和顾客复杂性对国际化程度与供应链韧性之间的调节效应。通过对126家上市汽车零部件企业数据进行分析,本文实证结果表明:国际化程度较高的企业在抵御能力和恢复能力方面均表现不佳;而供应商复杂性能够作为一种有效措施提高供应链抵御能力;顾客复杂性对供应链抵御能力具有负向影响;同时,两方面复杂性对供应链韧性中的恢复能力调节作用不显著。异质性分析发现,国际化程度的提高对于民营企业,位于中、西部地区的企业和规模较大的企业供应链抵抗能力造成了更明显的负向影响。

基于复杂网络理论的供应链研究

供应链是由原材料供应商到最终客户的一系列生产和流通过程所形成的链条结构,连接上、下游各个企业之间的关系.供应链包含采购、生产、仓储、分销、客户服务、信息管理和资金管理等不同环节之间的物料、资源、资金和信息等的相互关联流动,从而形成复杂的网链结构.高效可靠的供应链对于增强企业的市场竞争力、推动社会和经济持续发展具有重要意义.近年来,采用复杂网络的理论和方法对供应链进行建模和分析受到了越来越多学者的关注.本文系统性地论述基于实证数据和网络模型两种类型的供应链网络构建研究,在此基础上探讨供应链网络的拓扑结构、脆弱性、关键节点识别、社团检测等结构性质,阐明供应链网络的风险传播、竞争博弈等管理特性.本文综述了基于复杂网络方法的供应链研究内容和前沿热点,论证了复杂网络理论在供应链网络研究中的有效性和适用性,分析了供应链网络研究现存的一些问题,并展望若干未来的重要研究方向.本文期望为供应链研究提供见解,并推动复杂网络方法在供应链研究中的发展和应用.

基于SIR模型的直播电商供应链运营风险传播与控制研究

为正确识别直播电商供应链的风险因素,分析、研判风险在直播电商供应链的传播规律,构建了直播电商供应链的结构框架,利用复杂网络模拟了供应链的运营过程。首先,识别出直播电商供应链的22个风险因素,引入SIR风险传染模型。其次,根据风险因素的分类,设置不同初始风险状态和传播规则,对风险传播过程进行模拟仿真分析。结果发现:品牌方的销售策略、主播的直播状态、直播间消费者对产品和主播的负面评价等风险需要重点关注。最后,结合风险传播路径和关键风险因素,提出控制直播电商供应链运营风险的管理措施。

基于复杂网络的航空制造供应链关键节点识别研究

随着不稳定因素的增加以及航空制造供应链的参与主体增多,航空制造供应链的管理所面临的风险也随之增大。因此针对航空制造供应链网络的风险管理,以复杂网络为工具研究供应链网络中的关键节点识别问题,从而帮助航空供应链提升抗风险能力。通过分析我国航空制造供应链网络现状和特点,提出供应链形成机制并划分供应链层级,对航空制造供应链进行构建及指标界定,对度中心性、介数中心性、接近中心性三种经典中心性算法以及传统K-Shell分解算法进行加权改进;结合熵值-TOPSIS法提出一种针对加权网络的供应链关键节点识别算法——WKC算法,通过构造网络来进行算例分析,验证该种算法的有效性。结果表明:本文提出的WKC算法原理科学、计算复杂度较低,为航空制造等高端装备制造业供应链的风险管理提供了一定的参考。

基于复杂网络的闭环供应链风险传播模型构建及仿真

根据闭环供应链的结构特征,设计闭环供应链演化网络,并从风险对抗能力出发改进灾害蔓延动力学模型,以构建闭环供应链风险传播模型。仿真结果表明:闭环供应链网络中的风险传播范围与初始风险值、初始攻击节点数量成正相关;网络对抗风险能力与节点企业风险阈值和风险恢复能力分布的平均程度成正相关,且只有当风险阈值系数超过关键风险阈值系数时才能有效控制和预防风险的传播;度大蓄意攻击与随机攻击比度小蓄意攻击对网络风险传播的影响大,且制造商作为闭环供应链网络的中心节点,当其受到风险攻击时对网络造成的影响较大。

基于复杂自适应系统与库龄策略的血液供应链绩效评估

提升血液供应链保障绩效,有效应对临床血液需求,具有重要的实践意义。为此,文章基于复杂自适应系统视角,运用智能体建模方法研究血液供应链保障绩效演进问题。以血小板为研究对象,集成物流、信息流和效益流,采用数学语言描述血液供应链各Agent的行为方式,并分析供应链系统的总体特征。利用Anylogic平台构建一个考虑血制品库龄,由医院Agent、血液中心Agent、献血车Agent以及献血者Agent组成的四级供应链模型;对血液供应链系统的总体特征进行了仿真分析;针对血液供应链主要Agent的关键参数,做了敏感性分析。研究表明:(1)血液供应链系统具有复杂自适应特征。(2)考虑血制品库龄信息,可有效降低短缺率与过期率。(3)扩大初始献血者人数,加大宣传力度,均能降低血液中心Agent的短缺率,但同时会提高过期率。在初始献血者人数较少时,加大宣传力度对降低过期率的效果不明显;当初始献血者人数较多时,加大宣传力度对降低短缺率的效果同样不明显。(4)提高最大库存水平、缩短血小板保质期均能降低医院的血液短缺率,但也会提高过期率。当医院Agent最大库存水平较高时,缩短保质期对降低短缺率的效果不明显。研究成果有助于血液供应链重要节点的控制与决策优化,对血液供应链管理具有指导意义。

血液供应链绩效演进与评价研究:基于ABM+SD耦合建模与仿真

提高血液供应链绩效水平,完善血液保障体系,对于缓解我国的区域性/季节性血荒具有重要价值。为此,从复杂自适应角度出发,以血小板为研究对象,考虑宏观环境调控会影响献血者人数进而影响供应链绩效,提出以血液中心Agent为核心,基于库龄信息的ABM+SD耦合的四级血液供应链绩效演进与评价模型,并对其进行现实性检验与敏感性分析。研究表明:①血液中心Agent与医院Agent均存在自适应调整过程。②提高血液紧缺事件影响力,提升初始献血者人数,均能降低血液中心Agent的短缺率,但也会同时提高过期率。初始献血者人数的增多对于降低短缺率、提高过期率的作用并不明显。而当事件影响力提升至一定程度后,短缺率下降速率逐步放缓,过期率的提高速率逐步加快。③采用血型替代策略可有效降低医院Agent的短缺率与过期率。④提高最大库存水平、缩短血小板保质期均能降低医院Agent的短缺率,并提高过期率。但就整个仿真周期而言,缩短保质期对降低短缺率的作用并不显著。文章研究成果有助于重要节点在血液紧缺背景下更高效地进行供应链决策与控制,提升绩效水平;对破解血液紧缺困境具有一定的指导意义。

复杂社会技术系统视角下区块链赋能供应链信息管理的框架、路径与挑战

区块链技术与供应链信息管理的结合是数字化供应链发展变革的趋势,其研究逐步受到各界关注。本研究对Web of Science中基于区块链的供应链信息管理的文献进行了主题演化分析和关键词聚类分析,提出了研究框架,并从复杂社会技术系统视角探究了通过区块链技术数智赋能供应链信息管理的路径。通过知识共享、信息溯源、信任建立的方式,区块链技术将社会系统中的物资流通、商业流通、信息流通、资金流通与技术系统各层级信息进行交错相联并相互验证,从而赋能物流安全可视化、商流透明可溯化、信息流共享不可篡改、资金流可信匿名化。同时从管理挑战和应用行业方面分析了区块链技术下供应链信息管理实践,并展望了未来研究。本研究从技术系统和社会系统的层面,探究了区块链技术赋能信息管理的变革,复杂社会技术系统视角下的信息管理思考将为供应链数字化转型发展提供启示。

我国新能源汽车供应链复杂网络特征研究

疫情时期我国各产业供应链运行都受到不同程度的影响,汽车作为我国仅次于房地产的第二大家庭消费品,其供应链安全是我国经济稳步发展的重要支撑。近年来,我国新能源汽车产业发展迅猛,研究其供应链网络的结构特征有着重要的理论价值和现实意义。文章基于市场关系构建了我国新能源汽车制造业的供应链复杂网络模型,并计算和分析了网络各项指标特征,进而给出了相应的对策建议。

考虑复杂度的鲁棒闭环供应链网络设计模型

针对顾客需求不确定和部分设施节点失效情况下闭环供应链网络设计问题,考虑网络结构复杂度,以最小化闭环供应链运营成本和维护成本为优化目标,构建非线性混合整数规划模型.采用鲁棒对等式理论处理需求不确定性,采用情景分析方法处理单一设施节点中断不确定性;采用信息熵理论量化网络结构复杂度并采用分段线性逼近方法进行结构复杂度线性重构,构建混合不确定因素影响下的鲁棒优化模型,利用Gurobi求解进行节点开放及流量分配决策.针对算例,将鲁棒优化模型与随机规划模型进行对比,结果显示,考虑网络结构复杂度进行网络设计,与随机规划模型相比,鲁棒优化模型的目标函数值在不确定情景下的波动幅度显著减小,表明模型具有较好的抵抗外部风险的能力.