可变产能的按订单装配系统库存和生产决策研究

本文基于一个ATO 生产商的实践,考虑一个需求不确定并具有子装配件的单周期ATO 系统,为了应对较长的采购提前期和有限产能的挑战,生产商可以在得到确定的需求之前提前采购零件,装配子装配件以至于最终产品。由于产品物料清单结构中存在子装配件作为可选的中间件,因此完全使用零件和使用子装配件装配最终产品的不同,造成装配能力在时间上具有可变性。我们对此问题建立了利润最大化模型,分析在上述ATO 环境中的最优库存和生产决策。通过一系列最优解的性质,我们得到了该问题的有效解决方法。     

爱尔朗型按订单装配系统最优生产——库存控制策略研究

本文研究具有复杂装配结构的爱尔朗型按订单装配(ATO)系统的组件生产与库存优化控制问题。系统涉及多种组件,一个最终产品和多类客户需求。在此系统中,各种组件的生产时间服从爱尔朗分布,各类客户的需求为泊松到达过程。针对不同客户需求类型:产品需求与独立组件需求且同为销售损失型,建立基于马尔可夫决策过程(MDP)的平均总成本模型,应用动态规划方法求解最优策略。仿真模拟方法实现最优策略,并通过数值实验分析多生产阶段和系统参数对最优策略的影响。研究结果表明,爱尔朗型生产时间ATO系统的最优策略为状态依赖型策略,即组件的生产与库存分配由动态基础库存水平值和动态库存配给水平值控制。对于任一组件,其基础库存水平值和库存配给水平值均随着生产阶段的增加而降低,且生产阶段对基础库存水平值和平均总成本的影响较显著。     

偏好市场下制造/再制造系统最优生产决策

从消费者对再制造产品和新产品有着不同的需求偏好入手,引入市场需求偏好函数,构建单一垄断生产商利润最大化的带约束生产决策模型,探讨偏好市场下的两期和无限期的最优产量-价格决策策略.此外,通过对再制造经济优化模型的数据模拟,分析消费者偏好系数对生产商利润、成本节约、产品价格的影响,为生产商的生产决策,以及政府如何影响消费者偏好决策提供指导建议.     

偏好市场下制造 /再制造系统最优生产决策

从消费者对再制造产品和新产品有着不同的需求偏好入手, 引入市场需求偏好函数, 构建单一垄断生产商利润最大化的带约束生产决策模型, 探讨偏好市场下的两期和无限期的最优产量 -价格决策策略.此外, 通过对再制造经济优化模型的数据模拟, 分析消费者偏好系数对生产商利润、成本节约、产品价格的影响, 为生产商的生产决策, 以及政府如何影响消费者偏好决策提供指导建议     

二级供应链系统的三阶段协同订货模型

生产商-销售商联合生产库存系统是供应链的一个重要组成部分。但是目前协同条件下的相关订货策略具有明显的局限性,容易丢失真正的最优策略。本文利用边际分析法,通过改变销售商相邻两次订货量的大小来分析生产商和销售商库存费用的变化,发现销售商的订货量与系统库存费用变化量的确存在一定的规律。并且,进一步可以推导出该类系统的最优订货策略的订货量必须符合“三阶段”规律。根据该特点,只需设置各个阶段的初始订货量和订货次数等6个决策变量就可以构建订货策略的数学模型。该模型与直接求解的数学模型相比,不仅变量减少,而且其求解也相对简单。最后,利用各个文献中常用的两个实例仿真进行对比分析,验证了该策略确实能够找出其他策略丢失的最优解。     

随机供货下销售商最优订购决策

在实际生产生活中,存在着由于产品本身生产的随机性和一些外部因素导致生产商供货不确定的问题。在此背景下,本文研究单周期供货不确定情况下销售商的最优订购决策。从理论上分析了最终到货量为订购量与扰动变量加和的情况下,销售商存在最优订购量,按照新的策略订购可以使销售商利润最大化,并最大程度地消除由于订货不足或者订货过量所带来的负面效应。     

一种考虑原材料库存成本的变质物品EPQ模型

在库存管理研究中,单独实现产成品或原材料库存成本最小,往往无法获得整个库存系统的最优控制策略.本文提出了一种同时考虑产成品和原材料库存成本的变质物品EPQ集成模型.运用迭代寻优法得到模型最优解,得出计划期内最优原材料订购次数,原材料订购周期内的最优生产次数和最优服务水平,并对主要参数进行了灵敏度分析,为生产制造企业的库存管理提供了决策依据.     

基于通用件的ATO系统对家电行业的影响分析

面对消费者个性化的需求以及家电产品更新换代的加快，家电行业MTS的供应链模式逐渐体现其局限性：产品库存积压、旧产品零部件难以配型、消费者个性化需求不能满足等。基于通用件的ATO系统通过风险混同，减少了通用件的安全库存，缩小了成本，更大满足了消费者需求。本文分别建立了单期与多期最小成本模型，比较有通用件ATO系统与没有通用件MTS系统成本。证明有通用件ATO模型可以减少成本，同时减少通用件库存。。在一定服务水平前提下，当通用件的价格比其替代零部件的价格增加百分比不超过16％时，无论是单期模型还是多期模型（缺货不可补），采用通用件成本更低。而对于多期模型（缺货可补时），在一定服务水平前提下，当通用件的价格比其替代零部件的价格增加酉分比不超过0．5％时，采用通用件成本更低。依据家电行业的现状，只需对零部件进行合理的模块化设计以及与零售企业建立信息交换系统，就能很好的移植ATO系统，但各家电企业还需根据自身情况，斟酌利弊，权衡ATO系统带来的成本的节省与移植系统带来的额外成本的影响。     

变质率呈Weibull分布的一体化三级冷链库存策略研究

本文以有限期内一个生产商、多个分销商和多个零售商组成的冷链系统库存一体化决策为研究内容,建立了考虑可变运输成本、变质率服从三参数Weibull分布的三级冷链库存模型。文章从系统利润最大化的角度确定各个供应链成员的最佳补货策略,在与零售商主导的非一体化决策的对比分析中发现,库存一体化决策带来系统利润增加的同时也牺牲了部分成员的利益。与此同时,通过对变质率参数和运输成本参数的灵敏度分析发现,在运输距离一定的条件下,固定运输成本对最优库存策略的影响较大;在保鲜期一定情况下,变质率的尺度因子对系统总变质成本的影响较大。     

产能有限的供应商主导的双渠道分销策略研究

在供应商产能有限的背景下,研究供应商的最优分配策略和双渠道分销的问题。根据期望利润最大化建立供应商渠道分配模型,依据纳什均衡确定供应商的最优定价、最优产能和最优分销策略。结果表明,在双渠道策略的情况下,供应商应该优先满足销售企业的销售量。若供应链的销售量恰好得到满足,供应商应该按最优产能生产。供应商的渠道选择与供应商产能、供应链各节点的盈利能力和生产成本有关。     

Optimal Procurement Design of an Assembly Supply Chain with Information Asymmetry

We study a decentralized assembly supply chain in which an assembler (she) assembles a set of n components, each produced by a different supplier (he), into a final product to satisfy an uncertain market demand. Each supplier holds private cost information to himself, for which the assembler only has a subjective estimate. Furthermore, the assembler believes that the suppliers' costs follow a joint discrete probability distribution. The assembler aims to design an optimal menu of contracts to maximize her own expected profit. The assembler's problem is a complex multi‐dimensional constrained optimization problem. We prove that there exists a unique optimal menu of contracts for the assembler, and we further develop an efficient algorithm with a complexity of O(n) to compute the optimal contract. In addition, we conduct a comprehensive sensitivity analysis to analyze how environmental parameters affect individual firm's performance and the value of information to the assembler, to each supplier, and to the supply chain. Our results suggest that each supplier's private cost information becomes more valuable to the assembler and each supplier when the average market demand increases or when the final product unit revenue increases. Surprisingly, when a supplier's cost volatility increases and its mean remains the same, the value of information to the assembler or to each supplier does not necessarily increase. Furthermore, we show that when the suppliers' cost distributions become more positively correlated, the suppliers are always worse off, but the assembler is better off. However, the value of information for the assembler might increase or decrease.     

Single‐Period Two‐Product Assemble‐to‐Order Systems with a Common Component and Uncertain Demand Patterns

We consider a single‐period assemble‐to‐order system that produces two types of end products to satisfy two independent and stochastic customer orders. Each type of product is used to fulfill a particular customer order and these two products share a common component. Furthermore, one customer may confirm her order before the other one, and the manufacturer needs to make a commitment immediately upon the receipt of each customer order on how many products to be delivered. We propose a model for optimizing the inventory and production decisions under the above ATO environment. We also extend our model to the situation where the manufacturer can fulfill the unsatisfied low‐priority demand using the left‐over inventories after fulfilling the high‐priority demand, in case the low‐priority customer arrives first. Numerical experiments are conducted, which provide some interesting insights on the impact of uncertain demand pattern.     

A Production–Inventory Model for a Push–Pull Manufacturing System with Capacity and Service Level Constraints

We study a hybrid push–pull production system with a two‐stage manufacturing process, which builds and stocks tested components for just‐in‐time configuration of the final product when a specific customer order is received. The first production stage (fabrication) is a push process where parts are replenished, tested, and assembled into components according to product‐level build plans. The component inventory is kept in stock ready for the final assembly of the end products. The second production stage (fulfillment) is a pull‐based assemble‐to‐order process where the final assembly process is initiated when a customer order is received and no finished goods inventory is kept for end products. One important planning issue is to find the right trade‐off between capacity utilization and inventory cost reduction that strives to meet the quarter‐end peak demand. We present a nonlinear optimization model to minimize the total inventory cost subject to the service level constraints and the production capacity constraints. This results in a convex program with linear constraints. An efficient algorithm using decomposition is developed for solving the nonlinear optimization problem. Numerical results are presented to show the performance improvements achieved by the optimized solutions along with managerial insights provided.     

基于库存分担策略的装配系统准时供货模型研究

本文考虑一个由多供应商和单制造商构成的装配系统。当市场的需求时间无法确定时,制造商通过对供应商设定合理的库存分担策略来降低自身成本,供应商则需要自行决定对制造商的补货时间并承担相应的库存持有成本和延迟惩罚成本。文章同时建立了供应商之间的纳什博弈模型和以制造商为主方的主从博弈模型,以找到供应商的最佳供货时间和制造商最优的库存承担时限。通过对比不同模式下供应链的整体绩效,找到实现供应链协调运作的必要条件,并通过数据分析进一步证明相关结论。     

BlueLinx can benefit from innovative inventory management methods for commodity forward buys

Commodity prices often fluctuate significantly from one purchasing opportunity to the next. These fluctuations allow firms to benefit from forward buying (buying for future demand in addition to current demand) when prices are low. We propose a combined heuristic to determine the optimal number of future periods a firm should purchase at each ordering opportunity in order to maximize total expected profit when there is uncertainty in future demand and future buying price. We compare our heuristic with existing methods via simulation using real demand data from BlueLinx, a two-stage distributor of building products. The results show that our combined heuristic performs better than any existing methods considering forward buying or safety stock separately. We also compare our heuristic to the optimal inventory management policy by full enumeration for a smaller data set. The proposed heuristic is shown to be close to optimal. This study is the first to decide both the optimal number of future periods to buy for uncertain purchase price and the appropriate purchasing quantity with safety stock for uncertain demand simultaneously. The experience suggests that the proposed combined heuristic is simple and can be very beneficial for any company where forward buying is possible.     

Assembly Systems with Sequential Supplier Decisions and Uncertain Demand

We consider multitier push assembly systems with sequential supplier decisions and a wholesale price contract. We show that both an Original Equipment Manufacturer (OEM)–Contract Manufacturer (CM) assembly and a modular assembly with sequential supplier decisions are mathematically equivalent to the corresponding traditional assembly. We determine that, in most cases, the first mover supplier realizes a higher profit than the second mover supplier but we also identify the sufficient conditions for the reverse to occur. We provide conditions under which the order quantity, the second mover profit, total supplier profits, and the assembler profit are either higher or lower for a multitier system with sequential suppliers compared to simultaneous suppliers. We conclude that the first mover is always better off in a three‐tier sequential system while she can be either better off or worse off in a four‐tier sequential system compared to the corresponding simultaneous systems. We also analyze the impact of information asymmetry on the supplier and assembler profits in a three‐tier sequential system. Finally, we determine the profit threshold for an independent manufacturer in a three‐tier system to become a CM in a four‐tier system and vice versa.     

随机供需条件下装配商的订购-定价联合决策问题

针对随机供需条件下装配商的订购与定价联合决策这一难题，运用随机非线性规划方法，以装配商期望利润最大化为目标，建立零部件订购量与最终产品定价的多维优化模型。刻画了给定价格时的最优订购量和给定订购量时的最优价格，最后给出关于最优订购-定价的必要条件。通过数值算例验证了模型结论并进一步探讨随机供需的影响，为装配商的订购-定价决策以及供应商改进提供有益的管理启示。     

On Optimal Expediting Policy for Supply Systems with Uncertain Lead‐Times

We examine the role of expediting in dealing with lead‐time uncertainties associated with global supply chains of “functional products” (high volume, low demand uncertainty goods). In our developed stylized model, a retailer sources from a supplier with uncertain lead‐time to meet his stable and known demand, and the supply lead‐time is composed of two random duration stages. At the completion time of the first stage, the retailer has the option to expedite a portion of the replenishment order via an alternative faster supply mode. We characterize the optimal expediting policy in terms of if and how much of the order to expedite and explore comparative statics on the optimal policy to better understand the effects of changes in the cost parameters and lead‐time properties. We also study how the expediting option affects the retailer's decisions on the replenishment order (time and size of order placement). We observe that with the expediting option the retailer places larger orders closer to the start of the selling season, thus having this option serve as a substitute for the safety lead‐time and allowing him to take increased advantages of economies of scale. Finally we extend the basic model by looking at correlated lead‐time stages and more than two random lead‐time stages.     

订单不确定条件下的供应链协同决策研究

在产品客户化程度较高的装配生产中,制造商在获得客户的订单需求信息,但订单尚未签订的情况下,往往就要求供应商开始生产订单所需的零部件,以便客户订单签订后可以立刻开始产品的装配生产,从而实现尽快向客户交付订单的目的。但是,在客户订单不确定条件下,供应商提前生产零部件存在着一定的风险。一旦客户订单最终未能签订,由于零部件客户化程度一般也比较高,在相当长一段时间内很难被其它订单消化,从而形成呆滞库存。本文基于这样的运作环境,通过数学建模分析,研究了制造商何时向供应商下达零部件订单最优,以及供应商的最优生产决策问题,并给出了具体的决策方法。最后通过算例验证了模型的结论,并分析了生产延滞成本分担系数对供应商和制造商双方期望利润的影响。