需求和提前期不确定下的两级供应链系统研究

由一个部件提供商和一个装配商组成的两级组装供应链系统,部件提供商提供两种不同的部件给装配商进行装配;分析在单销售周期内,系统上同时存在部件的生产提前期和装配提前期的不确定,以及需求的不确定时,系统的特性.采用博弈论方法,装配商确定装配计划提前期,以及向部件提供商提交的订购量;而部件提供商确定部件生产计划提前期,以及部件批发价格.得出,首先,不确定提前期导致供应链系统订购量减小;其次,在分散控制的组装供应链系统中,系统的总生产、装配计划提前期,要大于集中控制系统中的,并且装配计划提前期与部件生产计划提前期无关;再者,过大的提前期不确定性对组装供应链系统的影响要比需求不确定对组装供应链的影响大.     

信息共享对瞬时补货多级供应链牛鞭效应影响的建模分析

对不稳定市场需求下的瞬时补货多级供应链系统进行建模,定量地分析了需求信息共享前后供应链各节点企业的牛鞭效应,并进行了数值实验.研究表明:无需求信息共享时,牛鞭效应始终存在;需求信息共享后,牛鞭效应明显地减小,在一定条件下会出现反牛鞭效应.     

具有时变参数的短生命周期产品供应链协调

技术和需求的快速变化,使得时间竞争成为短生命周期产品最重要的竞争战略.压缩订货提前期在提高销售商需求预测精度的同时却使制造商的生产成本增加,分析了分散决策下提前期压缩对供应链成员利润的影响,提出采用收益共享契约进行供应链协调.研究证明选择恰当的利润分配系数能够使供应链达到Pareto优化,而利润分配系数的取值范围与订货提前期有关,随着提前期的压缩,其取值范围逐渐缩小.最后用一个算例进行了说明.     

紧急订单成本信息不对称下的激励契约设计

在正常订单和紧急订单供应商共存情况下.分析制造商的最优订货策略.正常订单供应商采购提前期较长.需在销售期前进行订货.紧急订单供应商交货期较灵活.但交货期长短与成本相关且该成本信息为其私有信息.考虑在此条件下制造商的订货策略(与正常订单供应商)和激励合同设定问题(与紧急订单供应商).最后,比较了紧急订单供应商的存在与否对制造商的订货以及利润的影响.     

产品质量、价格及提前期竞争下的企业最优决策

基于产品质量角度,应用客户需求及优化理论,研究了产品质量、价格及交付提前期竞争下的企业最优决策问题.首先构建了产品质量、价格及交付提前期相互竞争下的质量敏感型和非敏感型客户需求及企业净利润模型.并进一步确定了企业质量服务水平可协调的范围,在协调范围内分别求解了产品质量、价格、提前期的稳定均衡最优解及相应的企业最大净利润...     

弹性需求条件下供应链协作的批发价格机制研究

研究了一类由供应商与分销商组成的两级供应链在弹性需求下的协作机制设计问题.分析了供应商与分销商未进行任何协作时整个供应链的收益情况.在此基础上,对供应商与分销商进行协作时最优订货量与整个供应链的收益进行了分析.研究结果表明双方协作可以提高整个供应链系统的收益,但并不能保证合作各方的收益均会增加.为此,提出了一种基于不对称Nash协商模型的批发价格契约机制来协调合作双方的收益,并进行了数据模拟与综合分析.     

分销系统安全库存策略及研究

早期的生产分销模式并没有重视生产中心和分销点及分销点之间信息传递和调度，导致库存管理造成很大的问题，安全库存急剧增大，甚至出现级联放大效应，本文针对上述问题，在理论上讨论了生产分销系统中进行信息协调调度与控制的可行性。     

组合折扣条件下带有可变提前期的库存策略

为了有效地分析随机需求条件下库存策略,在连续库存补货策略中考虑运输和采购的组合折扣且进货提前期为可变情形,建立订单量、再订货点和进货提前期优化决策模型,并设计模型求解的有效算法.最后通过算例,验证模型的有效性和实用性,并就考虑运输与不考虑运输条件下的库存策略进行了比较分析,就模型主要参数对订单量、再订货点、进货提前期和...     

面向零售商的供应链联盟合作伙伴选择研究

处于供应链末端的零售商在现代供应链中扮演着服务中心、信息搜集中心和预警中心的角色,满足了零售商的需求就意味着在很大程度上满足了市场需求.本文以零售商满意为切入点,以制造型企业作为供应链的核心企业来考虑供应链联盟合作伙伴的选择,在分析了供应商和分销商的不同特性之后为供应链上下游备选合作伙伴建立了不同的评价指标.文中采用传统的数据包络方法评价供应商的相对有效性,并以此为依据粗选上层供应商.对下层分销商采用作业成本法结合网络数据包络的方法展开相对有效性分析粗选分销商.在完成上下游合作伙伴的粗选之后,以零售商满意度最大化为目标建立了供应链联盟伙伴选择模型,据此选择出最理想的供应链联盟伙伴的组合.     

考虑多因素的集成库存模型及其优化解

在提前期与质量水平可控且需求分布形式未知的情况下,研究了有顾客流失的单买方单卖方联合期望总成本最小化问题.将订购批量、生产过程失控概率、安全系数、提前期和运送批次作为决策变量,建立了一套库存决策模型和求解算法,并与Ouyang等(2006)的求解结果进行了比较.比较证明,所求得的系统总成本是分布情况未知时所能求得的最优总成本,它大于正态分布下的系统总成本.     

Analysis of the bullwhip effect in multi-product,multi-stage supply chain systems–a simulation approach

This research aims to develop a simulation approach based on system dynamics modelling (SDM) and adaptive network based fuzzy inference system (ANFIS) for quantifying and reducing the bullwhip effect in a multi-product, multi-stage supply chain. The proposed model is comprised of three groups of variables influencing the bullwhip effect, namely the structure of a supply chain network, supply chain contributions (ordering process in regular situation or when a supplier has a promotion or shortage gaming) and supply chain performances (the number of defects and ordering lead time). As a result, a two layer simulation model is developed with three generic models. The flexibility of this proposed approach is its ability to model various types of ordering policies which are basic inventory policies, material requirement planning (MRP) system and just in time (JIT) approach. The supply chain of a beverage company was selected to validate and demonstrate the flexibility of the proposed model. The findings of the proposed simulation model are consistent with the results obtained from the case study. The error magnitude of the bullwhip effect level varied between 0 and 9% resulting in bullwhip effect reductions of up to 92%. Accordingly, the bullwhip effect levels are significantly decreased by using the proposed simulation model.     

Measure of the bullwhip effect considering the market competition between two retailers

In order to consider the market competition, a new supply chain with one supplier and two retailers is established in this paper. Two retailers employ different AR(1) demand processes, respectively, and an order-up-to inventory policy characterises the inventory decisions. The bullwhip effect in this supply chain is measured under the moving average forecasting technique. We investigate the effects of the lead time, the span of forecast, market competition and the consistency of demand volatility on the bullwhip effect using the algebraic analysis and numerical simulation. Conclusions indicate that different factors lead to the bullwhip effect following different patterns in the supply chain. Moreover, some suggestions are present to help managers to control parameters that yield the lower bullwhip effect.     

Underestimating the bullwhip effect: a simulation study of the decomposability assumption

We investigate the assumption of decomposability as it pertains to modelling the bullwhip effect in multi-stage supply chains. Decomposing a multi-stage supply chain into a set of node pairs, each of which can be efficiently represented with a two-stage model, is a common modelling technique when analysing the bullwhip effect in supply chains. This approach depends on the validity of the decomposability assumption since most supply chains are coupled systems that are a logical fit for singular, or ‘monolithic’, multi-stage models. We utilise a simulation study to compare decomposition-based supply-chain models with monolithic models and determine if decomposition modelling significantly alters the predicted severity of the bullwhip effect. We find decomposition-based models exhibit a significantly lower level of bullwhip effect than monolithic models of the same supply chain. The systematic underestimation of the bullwhip effect by decomposition-based models indicates that the assumption of decomposability is flawed. Our study also confirms previous work showing the significant benefit of using actual, instead of approximate, lead-time demand information. We discuss implications for supply-chain modelling, supply-chain design, and data collection.     

基于遗传算法的供应链需求预测优化模型研究

整体优化是供应链管理的核心问题之一.为降低供应链的整体运作成本,减小"长鞭效应"的影响,建立了多级供应链的Multi-agent模型,并运用遗传算法(GA)对其需求预测进行优化研究.最后利用算例进行分析,表明提出的方法能有效减小"长鞭效应",有效降低供应链的整体运作成本.     

Stochastic characterization of upstream demand processes in a supply chain

In the supply chain management area, there has much recent attention to a phenomenon known as the bullwhip effect. The bullwhip effect represents the situation where demand variability increases as one moves up the supply chain. In this paper, we study this effect in an order-up-to supply-chain system when minimum Mean Square Error (MSE) optimal forecasting is employed as opposed to some commonly used simplistic forecasting schemes. We find that depending on the correlative structure of the demand process it is possible to reduce, or even eliminate (i.e., "de-whip"), the bullwhip effect in such a system by using an MSE-optimal forecasting scheme. Beyond the bullwhip effect, we also determine the exact time-series nature of the upstream demand processes.     

供应链中牛鞭效应的控制与弱化研究

为了弱化供应链中的牛鞭效应,本文剖析了其危害及形成机理,指出供应链的系统属性和管理运作两方面因素构成了牛鞭效应产生的主要原因,进而着眼于供应链的整体竞争力,有针对性地提出了控制牛鞭效应的系列策略,即强化战略协作及信息共享,消减供应链级数,开展敏捷管理,减少订货批量,控制安全库存,平衡库存责任和弱化最终需求的变异性.     

制造企业库存长鞭效应影响因子分析及控制方法

长鞭效应是供应链管理中由于供应链合作伙伴之间缺乏合作与协调的结果。从理论上刻画了长鞭效应的内在本质,分析了产生长鞭效应的原因,以一个跨国公司的库存管理为例,详细分析了影响长鞭效应三个方面的因子：（1）集中式与分散式管理;（2）需求与供应特征;（3）产品类型与库存再订货点。还从供需合作关系的角度提出了改善长鞭效应的几个控制方法。     

Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain†

The ripple effect refers to structural dynamics and describes a downstream propagation of the downscaling in demand fulfilment in the supply chain (SC) as a result of a severe disruption. The bullwhip effect refers to operational dynamics and amplifies in the upstream direction as ordering oscillations. Being interested in uncovering if the ripple effect can be a driver of the bullwhip effect, we performed a simulation-based study to investigate the interrelations of the structural and operational dynamics in the SC. The results advance our knowledge about both ripple and bullwhip effects and reveal, for the first time, that the ripple effect can be a bullwhip-effect driver, while the latter can be launched by a severe disruption even in the downstream direction. The findings show that the ripple effect influences the bullwhip effect through backlog accumulation over the disruption time as a consequence of non-coordinated ordering and production planning policies. To cope with this effect, a contingent production-inventory control policy is proposed that provides results in favour of information coordination in SC disruption management to mitigate both ripple and bullwhip effects. The SC managers need to take into account the risk of bullwhip effect during the capacity disruption and recovery periods.     

Effective bullwhip metrics for multi-echelon distribution systems under order batching policies with cyclic demand

A large number of problems in a distribution supply chain require that decisions are made in the presence of the bullwhip effect phenomenon. The impact of the order batching policies on the bullwhip effect is analysed in this paper, when cycle demand on a multi-echelon supply chain operating is considered. While investigating which bullwhip effect metrics are more adequate to measure the bullwhip effect in these type of systems, the optimal reordering plan that minimises the operation costs of the overall system is calculated. A Mixed Integer Linear Programming (MILP) model is developed that takes into account an inventory and distribution system formed by multiple warehouses and retailers with lateral transshipments. The bullwhip effect is measured through four metrics: the echelon average inventory; the echelon inventory variance ratio; the echelon average order; and the echelon order rate variance ratio. As conclusion the inventory metrics suggest that (i) using batching policy reduces instability; (ii) batching may reduce in general order variance if using larger batches and (iii) cycle demand length has no major impact in the bullwhip effect. A motivational example and a real word case study are used and tested.     

Dynamic analysis and design of a semiconductor supply chain: a control engineering approach

The combined make-to-stock and make-to-order (MTS-MTO) supply chain is well-recognised in the semiconductor industry in order to find a competitive balance between agility, including customer responsiveness and minimum reasonable inventory, to achieve cost efficiency while maintaining customer service levels. Such a hybrid MTS-MTO supply chain may suffer from the bullwhip effect, but few researchers have attempted to understand the dynamic properties of such a hybrid system. We utilise a model of the Intel supply chain to analytically explore the underlying mechanisms of bullwhip generation and compare its dynamic performance to the well-known Inventory and Order-Based Production Control System (IOBPCS) archetype. Adopting a control engineering approach, we find that the feedforward forecasting compensation in the MTO element plays a major role in the degree of bullwhip and the Customer Order Decoupling Point (CODP) profoundly impacts both the bullwhip effect and the inventory variance in the MTS part. Thus, managers should carefully tune the CODP inventory correction and balance the benefit between CODP inventory and bullwhip costs in hybrid MTS-MTO supply chains.