一种特殊的冲击型负荷模型及其供应链可靠度研究

基于一种特殊的单次冲击型负荷模型,对供应链系统受到冲击源N(t)为强度λ的poisson流冲击时的可靠性进行了研究.当冲击间隔小于常数δ时供应链失效,给出了供应链的可靠度函数及数字特征.研究表明可以通过预测该特殊冲击型负荷模型下供应链的期望寿命,做好应急物流保障.     

一类基于随机着色Petri网的多级供应链可靠性模型研究

由多种要索组成的供应链系统在实际运作过程中必须符合可靠性要求。供应链系统由于内外部的不确定性，特别是外部需求不确定性而与其他可靠性系统有所不同。本文在考虑其可靠性问题的条件下，提出了一种随机着色Petri网来对供应链系统可靠性问题进行建模分析。     

基于可靠性的企业优化模型

供应链中的企业连接着供应商和销售商,它的运作存在很多风险,如原材料供应的风险,生产过程的风险,用户需求的风险,这些风险直接影响企业运作的可靠性.本文通过分析供应链中企业的状态转移,利用增补变量法,建立了偏微分方程组刻画的供应链中企业的优化模型.     

考虑风险偏好的动态生产库存问题的鲁棒优化模型

不同阶段需求不确定情况下,决策者的风险偏好和生产过程中的废品处理影响着供应链生产库存管理和供应链整体效益。本文考虑决策者风险偏好下,构建了包含I个生产者企业,一个库存点和一个废物处理基地的T阶段动态供应链生产库存框架,建立了椭球型需求不确定集下,以追求整体收益最大化为目标的不确定优化模型,并应用鲁棒优化理论得到了数据确定性线性鲁棒对应模型,讨论了模型解的可靠性和有效性。最后的算例表明,只有当决策者风险偏好参数在一定范围内时,才会存在满足条件且具有较高可靠性的鲁棒决策,验证了该鲁棒优化模型的合理性。     

供应链网络可靠性的多层Bayes估计模型

对供应链网络可靠性进行界定和分析,以节点企业间的协同为基础,得到可靠度计算模型,以此为依据采集实证样本无失效运行的数据.根据供应链网络可靠性统计特性,建立一种多层Bayes估计方法,应用于样本可靠性评估中.在估计失效率的基础上,对供应链网络可靠度进行估计,对仿真结果进行分析,显示多层Bayes估计方法应用效果较好,精确度高,反映了参数不确定性对供应链网络可靠性的影响,能够较好地解决依据无失效数据判定供应链网络可靠性水平的问题.     

供应链物流网络优化设计及其可靠性

针对供应链网络优化设计和供应链可靠性,建立P-中值选址的0-1规划模型决策供应链物流网络布局.考虑供应链网络的确定性破坏和随机性破坏问题,定义破坏绩效,建立综合破坏性效益指标,得到破坏后损失评估模型,进而探讨供应链物流网络的可靠性.     

基于BP神经网络的供应链绩效评价方法

动态供应链绩效评价是一个包含多个指标输入输出的复杂评估系统,各绩效指标具有模糊性、不确定性,绩效指标数量较多,彼此之间存在非线性关联性。针对这样一个复杂的评估系统,本文讨论利用神经网络技术来对动态供应链绩效进行综合评价。本文首先介绍了人工神经网络的基本概念。针对供应链绩效的五维平衡计分卡模型,利用BP神经网络(Back Propagation NeuralNetwork,BP网络)来对供应链综合绩效评价结果进行学习和预测,文中我们详细讨论了供应链绩效评价中BP网络的学习过程和存在的问题,并给出了仿真结果。计算实例表明本文提出的动态供应链绩效评价模型是合理、有效的,能够为供应链的合理分析和决策制定提供依据。     

面向客户定制模式的供应链管理系统优化模型

建立供应链管理系统优化模型是构建高效率供应链以及发挥供应链优势的前提和基础 .本文建立了面向客户定制模式的集成的供应链管理系统优化模型 ,即一个多目标、具有约束的非线性混合规划模型 ,并提出了针对这种模型的求解思路 .通过对模型的仿真求解既可以优化选择供应链系统中涉及的相关协作企业 ,同时优化系统的订货、生产、库存策略 ,对构建高效率供应链管理系统具有重要意义 .     

基于风险管理的动态供应链超网络均衡模型

基于风险管理的动态供应链超网络均衡模型的研究有助于供应链超网络节点厂商在动态环境下优化其风险管理,降低风险损失,提升供应链网络在风险管理下的竞争优势。本文以三层供应链超网络为研究对象,采用风险发生概率和损失函数表达供应链超网络中节点厂商中断风险的特征,构建了基于风险管理的动态供应链超网络均衡模型。模型中包括三种类型的节点,产品生产商、零售商和需求市场,生产商考虑风险损失的情况下,基于动态变化的风险、需求和成本追求个体期望效益最优化。接着,通过进化变分不等式来表达动态供应链超网络风险管理下的均衡解,并采用投影动态系统求解进化变分不等式,通过数值算例验证方法的可靠性和合理性,通过投影动态系统解释某一个厂商趋近均衡解的过程。通过单一厂商趋近均衡解的过程,阐述其他厂商相应的最优决策。     

存在价格差异的闭环供应链定价策略及契约协调

以零售商回收模式为对象,采用博弈论方法,研究再制造产品与新产品存在销售价格差异以及废旧产品存在回收价格差异时闭环供应链的定价策略及契约协调问题。对闭环供应链系统在分散决策和集中决策下的定价模型进行了分析,得到了系统各成员的最优定价策略和利润,发现分散决策会造成系统效率的损失。为此提出一种改进的特许经营费用契约对闭环供应链进行协调,使得闭环供应链系统不仅消除了"双重边际化"的问题,而且实现了完美协调。算例分析验证了定价策略及契约协调机制的有效性。     

An analysis of the structural complexity of supply chain networks

Each enterprise in a supply chain network needs quantitative indicators to analyze and manage its interactions with different business partners in the network. Supply chains exhibit the characteristics of complex systems. In a supply chain network, a large number of firms cooperate simultaneously with many suppliers and customers, and interact through a variety of information and material flows to achieve a balance between supply and demand. However, the complexity of a supply chain is not a simple linear structure where a small change often results in a chain reaction. When supply chain complexity increases, monitoring and managing the interaction between different elements of the chain becomes more difficult. An entropy model based on information theory provides an appropriate means of quantifying the complexity of a supply chain system by delivering information required to describe the state of the system. The entropy measure links uncertainty and complexity so that, as a system grows in uncertainty, it becomes more complex and more information is required to describe and monitor it. In this paper, we propose an entropy-based measure for analyzing the structural complexity in relation to the structure and system uncertainty. The method provides guidelines for estimating the complexity throughout the supply chain structure.     

基于系统动力学的供应链库存策略仿真研究

针对一个动态、多级的供应链库存系统,应用系统动力学的方法,建立了供应链(s,S)库存策略下的物流成本模型,并通过动态仿真,分析了库存策略的变动对于供应链库存系统各级成员间库存供需的动态行为,提出了(s,S)策略下的供应链库存系统的有效管理方法.     

区块链技术影响下的供应链系统动态响应性研究

为解决供应链系统中信息时滞和不对称问题,加快推动区块链技术在供应链管理中的创新发展,本文运用控制理论构建由分销商和零售商组成的二级供应链系统控制模型,引入区块链技术影响下的信息校正因子,推导系统的传递函数,通过MATLAB仿真不同需求信号下的订单可变性和库存波动。仿真结果表明:(1)区块链技术的应用提高了库存系统的精准性和稳定性;(2)高库存可变性伴随着高订单可变性;(3)指数平滑系数和区块链技术影响下的信息校正因子有效抑制供应链中的牛鞭效应;(4)信息延迟时间越长,区块链技术影响下的信息校正因子对控制系统的抑制作用越显著。本研究量化了区块链技术对供应链中牛鞭效应的影响,提高了供应链系统的精准性和稳定性,丰富了区块链技术在供应链管理中的应用,为企业管理者提供新的研究思路。     

公平偏好下基于批发价契约的供应链 协调研究

文中基于Nash讨价还价博弈思想建立公平偏好框架,构建公平偏好效用体系,以此为基础对采用批发价契约的报童模型展开行为研究,采用数理模型和数值分析方法分析了零售商和供应商的公平偏好行为对零售商和供应链系统最优订货量的影响,即零售商和供应商同时关注公平时,零售商和供应链系统的最优订货量趋于保守;并发现零售商和供应链系统的最优订货量随零售商的公平偏好程度增加而递减,但随着供应商公平偏好程度增加而递增,且供应链系统最优订货量变化趋势比零售商明显．然后,在此基础上分析比较得到,无论供应商和零售商是否偏好公平,批发价契约都不能实现供应链协调．最后,对批发价、零售价、供应商生产成本、零售商缺货成本和供应商缺货成本进行敏感度分析．     

基于回购契约的供应链鲁棒协调模型

研究了需求不确定条件下供应链回购契约协调问题。针对未知需求具体分布形式的两级供应链系统,建立了基于回购契约的供应链鲁棒协调模型。给出了仅知需求均值和方差信息条件下,集成供应链系统的鲁棒订货策略和分散供应链系统的鲁棒契约协调策略。分析了不同契约参数条件下的供应链及其成员利润情况。最后,进行了数值计算,验证了当获得需求的真实分布形式时．供应链鲁棒回购契约协调策略的有效性。结果表明,供应链鲁棒回购契约协调策略能够有效减少需求不确定性对系统及其成员利润的影响。     

Optimal models for a multi-stage supply chain system controlled by kanban under just-in-time philosophy

This research studies a multi-stage supply chain system that operates under a JIT (just-in-time) delivery policy. Kanbans play an important role in the information and material flows in a supply chain system. Thus, a kanban mechanism is employed to assist in linking different production processes in a supply chain system to implement the scope of JIT philosophy. For a multi-stage supply chain system, a mixed-integer nonlinear programming (MINLP) problem is formulated from the perspective of JIT delivery policy where a kanban may reflect to a transporter such as a truck or a fork-lifter. The number of kanbans, the batch size, the number of batches and the total quantity over one period are determined optimally. It is solved optimally by branch and bound method. A greedy heuristic to avoid the large computational time in branch-and-bound algorithm is developed for solving a large MINLP. Coupled with plant-wide efforts for cost control and management commitment, a logistic system for controlling the production as well as the supply chain is built, which results in minimizing the total cost of the supply chain system. The results show that the improvements in reduction of inventory, wasted labor and customer service in a supply chain are significantly accomplished through the kanban mechanism.     

预付款融资下期权契约的协调研究

本文研究零售商占主导、供应商自有资金有限的二级供应链如何通过契约实现协调的问题。在预付款融资的基础上加入期权契约方法,构建用于预付款融资的期权契约模型,并求解出该模型下所能协调供应链的契约参数与此时零售商供应商双方的最优决策系统。研究表明当供应商自有资金大于等于某临界值时通过预付款融资下的期权契约可实现供应链协调。若小于则无法通过该契约协调,并且供应商自有资金约束越大,零售商最优订购数量越多,同时供应商的最优生产数量随着自有资金的减少而减少,供应链的参与者及整个供应链的利润也随着供应商自有资金的减少单调递减;另外,相比于无融资下的期权契约,预付款模式能提高零售商、供应商以及整个供应链的收益。     

Research on a scheduling mechanism in a complex system based on TOC

Under the condition where there is no seasonal demand fluctuation, short life cycle product supply chain should confront the market environment such as the decreasing of product value, the launch of substitutes and the appearance of competitors’ similar products, and the supply chain will become a very complex system. In this paper, the authors consider a TOC-based scheduling mechanism in this complex supply chain system. under the constant total production cost, it is more important to improve the availability of the wanted product in order to enhance the overall supply chain competitiveness so to obtain more effective output(profit rate) for the supply chain in a long period. Especially we try to apply the SDBR concept into a schedule mechanism in a particular supply chain system, and use numerical analysis to test the efficiency of the proposed method.     

Improve efficiency of biogas feedback supply chain in rural china

Feedback supply chain is a key structure in the supply chain system, and the development of feedback supply chain for biogas biomass energy is one of the important ways of the rural ecological civilization construction. Presently, the efficiency problem of biogas supply chain in rural China has been restricting the development of biogas biomass energy business. This article, on the basis of combination of regulation parameters, describes the dynamic changes in the system, using differential equations integrated with simulation to reveal the rules of regulation parameters to investigate the efficiency problem in the biogas supply chain. First of all, on the basis of the actual situation, the flow level and flow rate system structure model and simulation equation set are established for the biogas energy feedback supply chain from a scale livestock farm to peasant households; On the basis of the differentiability of the simulation equation a third order inhomogeneous differential equation with constant coefficients containing regulative parameters is established for the quantity of biogas stored in the feedback supply chain. A theorem and its corollaries are established for the operating efficiency of supply chain to reveal the change law of the quantity of biogas, the quantity of biogas consumed daily by peasant households and its standard-reaching rate as well as other variables.     

Understanding supply chain dynamics: A chaos perspective

Variability in orders or inventories in supply chain systems is generally thought to be caused by exogenous random factors such as uncertainties in customer demand or lead time. Studies have shown, however, that orders or inventories may exhibit significant variability even if customer demand and lead time are deterministic. In this paper, we investigate how this class of variability, chaos, may occur in a multi-level supply chain and offer insights into how to manage relevant supply chain factors to eliminate or reduce system chaos. The supply chain is characterized by the classical beer distribution model with some modifications. We observe the supply chain dynamics under the influence of various factors: demand pattern, ordering policy, demand-information sharing, and lead time. Through proper decision-region formation, the effect of various factors on system chaos is investigated using a factorial design. The degree of system chaos is quantified using the Lyapunov exponent across all levels of the supply chain. This study shows that, to reduce the degree of chaos in the supply chain system, the adjustment parameters for both inventory and supply line discrepancies should be more comparable in magnitude. Counter-intuitively, in certain decision regions, sharing demand information can do more harm than good. Similar to the bullwhip effect observed previously in demand, we discover the phenomenon of “chaos-amplification” in inventory across supply chain levels.