产能和需求不确定情形下ATO系统最优库存和生产决策研究

通过将产成品的最终组装环节延迟到观察到实际需求以后进行,按订单组装(Assemble-to-Order,ATO)策略能够有效避免按库存生产(Make-to-Stock)策略下因为生产过剩而带来的损失和风险。然而,在未来产能有限的情形下,生产商必须提前组装部分产成品,以最大化自身收益。本文考虑一个未来需求和组装产能同时具有不确定性的单周期ATO系统:在观察到实际需求以前,生产商必须准备好所有的零部件库存,并组装适量的产成品;观察到实际需求和实际可用组装能力以后,则根据需要进一步追加产成品产量,以尽可能满足客户需求,从而最大化自身利益。通过构建一个两阶段规划模型,我们研究了生产商的最优零部件库存和最优生产决策;并进一步考察了生产商可以通过紧急外包来获取额外组装产能时的最优决策。研究结果为随机环境下生产商合理采购零部件库存和合理安排生产提供了有益的管理启示。     

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。     

无外部市场条件下中间产品转移价格的研究

系统地讨论了不存在外部市场条件下中间产品最优转移价格的确定方法. 首先在各分厂 成本函数和最终产品需求函数已知条件下, 分别讨论了各分厂产量相同和产量不同情形下中 间产品最优转移价格的确定问题. 接着讨论了各分厂成本函数和最终产品需求函数未知条件 下中间产品转移价格的确定问题. 本文提出的三种确定中间产品转移价格的方法均给出了具 体的计算公式, 具有较大的理论价值和应用价值.     

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。     

拉动与推动混合供货方式下ATO系统的生产补货策略研究

考虑ATO系统由一个最终产品制造商与两个零部件供应商组成,供应商分别采用拉动式和推动式供货方式向制造商提供零部件,建立了相应的ATO系统生产、补货模型,运用逆向归纳法求得了系统最优解,并进行了理论分析、数值仿真和主要参数灵敏度分析。研究表明：ATO系统中处于主导地位的一方具有先动优势,能获得更多的利润;市场规模的变化对供应商和最终产品制造商利润的影响相同,且影响力与规模大小无关;产品销售价格的变化对企业利润的影响不相同,且销售价格越高影响力越小;生产成本的变化对企业利润的影响不同,对生产成本高的企业影响较大,对生产成本低的企业影响较小。     

价格相依随机需求下的逆向拍卖采购与定价联合决策

研究价格相依随机需求下零售商的逆向拍卖采购与定价联合决策问题。假定零售商首先确定一个采购合同,然后供应商投标,通过逆向拍卖选取一个获胜的供应商,由该供应商确定采购量并传递给零售商,同时零售商做定价决策影响其需求,目标是寻求一个最优的采购与定价策略以最大化零售商的期望利润。对于一般的随机需求函数,引进期望销售弹性这一新的概念并利用其性质证明零售商的期望收益(不包括采购费用)是采购量的凹函数,从而得到其最优的采购与定价策略。特别地,对正态需求分布情形给出了零售商的采购量和利润函数的解析表达式并进行数值分析。     

供应链库存分散决策研究

本文研究两级供应链库存问题,供应链包含一个客户和一个生产商.通过建立客户订货库存模型和生产商生产库存模型得到供应链库存模型.采用分散决策方法获得最优解,即最佳订货量和最佳订货次数.在此基础上,使用算例对最优解进行了数值分析.     

有限分布信息条件下MTO再制造系统提前期优化

在只知道零部件再制造时间有限分布信息（即一阶矩、二阶矩）条件下,基于MTO再制造策略研究由再制件和采购件组成的再制品的提前期问题,该问题被描述为一个矩问题。以最小化库存持有成本和缺货成本为目标建立min-max优化模型,在具有相同一阶矩、二阶矩的分布集合中寻找使最坏分布下的目标函数值最小的最优再制造提前期。最后通过算例进行了验证,求解结果与传统假设再制造时间服从正态分布、均匀分布得到的结果吻合较好,但本文的方法更符合生产实际,能保证在具有同样一阶矩和二阶矩的所有分布情况下的解的鲁棒性,对企业制定再制造计划、采购计划等具有现实的指导意义。     

采购风险期和零件订货批量之研究

采购风险期和订货批量是零件最优库存控制的两个关键因素.本文以博西威家电有限公司为例,通过设置采购风险期,有效地解决了采购提前期波动导致的缺货,辅之以设定经济订货批量,在确保连续生产的约束条件下控制库存量至最低水平.     

供应链中创新协调的绩效控制问题研究

基于对供应链中的采购-供应关系的一般合作模式和创新协调模式的分析,本文研究了最终产品市场需求是价格的乘法函数的市场环境中,生产商对其供应商创新活动提供资金支持的一类创新协调问题。并分别建立了创新协调下生产商和供应商的离散优化问题模型,分别讨论了生产商提出创新支持策略、供应商接受创新支持策略、以及使双方受益的创新协调策略有效可行的充分条件。     

考虑成本共担的复杂产品零部件协同创新Stackelberg优化研究

在技术不断升级改造背景下,复杂产品作为高端装备产品的代表,它的工艺技术创新水平在一定程度上代表了制造业的技术水平。由数以万计的零部件所组成的复杂产品在生产研发过程中,零部件的生产创新直接决定复杂产品的生产创新,而如何从供应链角度去研究零部件生产协同问题来实现复杂产品的生产协同成为难点。本文基于复杂产品协同制造模式,从主制造商激励视角出发,考虑零部件的工艺创新和装备创新,研究主制造商成本共担机制下复杂产品零部件的协同创新问题。首先,为激励供应商进行创新积极性,通过设计创新程度相关参数,依据零部件工艺创新程度和装配创新程度构建了复杂产品生产函数,探讨了主制造商成本共担激励策略,建立了基于成本共担协同创新Stackelberg博弈模型;其次,借助于成本共担与不共担情形下对比研究了最优创新程度水平以及主制造商最佳成本共担比例;最后,借助某商用飞机电力支持系统进行数值验证,结果表明：供应商最优成本共担比例和工艺弹性和装配弹性呈正比,最优工艺创新程度和装配创新程度与工艺弹性和装配弹性呈反比例关系,当弹性在一定范围变动时,成本共担要比成本不共担要好;当弹性超过变动范围时,则不再分担成本进行激励。本文系统分析了成本分担下零部件创新程度问题,为供应商和主制造商长期激励合作提供了一定决策依据。     

Just-in-time in ATO vehicle manufacturing: The Minivan-Piaggio V.E. case study

The system adopted by Piaggio V.E. to run the production of 'Minivan' aims at conciliating the manufacturing philosophy 'just-in-time' JIT with the creation of a wide range of end-product codes. Some general assumptions for a JIT production, with small lot sizes, are described together with their implementation in the operationorganizing system adopted by Piaggio V.E. for the 'Minivan' assembly line. The strategy pursued by Piaggio V.E. for the Minivan focuses on the quality of the product and the level of service in the form of fast order cycle and a high number of options offered on catalogue. According to the logic of an ATO production system, the customer orders a customized product and the manufacturer does not keep any finished inventory, but aims at effective management of the information flows.     

Lifecycle Pricing for Installed Base Management with Constrained Capacity and Remanufacturing

Installed base management is the policy in which the manufacturer leases the product to consumers, and bundles repair and maintenance services along with the product. In this article, we investigate for the optimal leasing price and leasing duration decisions by a monopolist when the production and servicing capacity are constrained. The effect of diffusion of consumers in the installed base is considered, with the ownership of the product resting with the monopolist during the product lifecycle. The monopolist operating the installed base jointly optimizes the profits from leasing the product/service bundle along with maintenance revenues and remanufacturing savings. We formulate the manufacturer's problem as an optimal control problem and show that the optimal pricing strategy of the firm should be a skimming strategy. We also find that the effect of remanufacturing savings on the pricing decision and the length of the leasing duration changes significantly depending on the duration of the product's lifecycle. If the product lifecycle is long and remanufacturing savings are low, the firm should offer a shorter leasing duration, whereas if the remanufacturing savings are high, the firm should optimally offer a higher leasing duration. In contrast, if the time duration of the product lifecycle is low and remanufacturing savings are low, the firm prefers to offer a shorter leasing duration, whereas if the remanufacturing savings are high, the firm should optimally have a longer leasing duration. The article also shows that if the production capacity is small, the manufacturer increases the leasing duration. If the production capacity is very small, the manufacturer sets the leasing duration to be equal to the product lifecycle and does not use remanufacturing.     

Optimal Dynamic Order Scheduling under Capacity Constraints Given Demand‐Forecast Evolution

We consider a manufacturer without any frozen periods in production schedules so that it can dynamically update the schedules as the demand forecast evolves over time until the realization of actual demand. The manufacturer has a fixed production capacity in each production period, which impacts the time to start production as well as the production schedules. We develop a dynamic optimization model to analyze the optimal production schedules under capacity constraint and demand‐forecast updating. To model the evolution of demand forecasts, we use both additive and multiplicative versions of the martingale model of forecast evolution. We first derive expressions for the optimal base stock levels for a single‐product model. We find that manufacturers located near their market bases can realize most of their potential profits (i.e., profit made when the capacity is unlimited) by building a very limited amount of capacity. For moderate demand uncertainty, we also show that it is almost impossible for manufacturers to compensate for the increase in supply–demand mismatches resulting from long delivery lead times by increasing capacity, making lead‐time reduction a better alternative than capacity expansion. We then extend the model to a multi‐product case and derive expressions for the optimal production quantities for each product given a shared capacity constraint. Using a two‐product model, we show that the manufacturer should utilize its capacity more in earlier periods when the demand for both products is more positively correlated.     

Optimal Production and Admission Policies in Make‐to‐Stock/Make‐to‐Order Manufacturing Systems

In this article, we study optimal production and admission control policies in manufacturing systems that produce two types of products: one type consists of identical items that are produced to stock, while the other has varying features and is produced to order. The model is motivated by applications from various industries, in particular, the automobile industry, where a part supplier receives orders from both an original equipment manufacturer and the aftermarket. The product for the original equipment manufacturer is produced to stock, it has higher priority, and its demands are fully accepted. The aftermarket product is produced to order, and its demands can be either accepted or rejected. We characterize the optimal production and admission policies with a partial‐linear structure, and using computational analysis, we provide insights into the benefits of the new policies. We also investigate the impact of production capacity, cost structure, and demand structure on system performance.     

Lowest Cost May Not Lower Total Cost: Using “Spackling” to Smooth Mass‐Customized Production

Consider a manufacturer who mass customizes variants of a product in make‐to‐order fashion, and also produces standard variants as make‐to‐stock. A traditional manufacturing strategy would be to employ two separate manufacturing facilities: a flexible plant for mass‐customized items and an efficient plant for standard items. We contrast this traditional focus strategy with an alternative that better utilizes capacity by combining production of mass‐customized and standard items in one of two alternate spackling strategies: (1) a pure‐spackling strategy, where the manufacturer produces everything in a (single) flexible plant, first manufacturing custom products as demanded each period, and then filling in the production schedule with make‐to‐stock output of standard products; or (2) a layered‐spackling strategy, which uses an efficient plant to make a portion of its standard items and a separate flexible plant where it spackles. We identify the optimal production strategy considering the tradeoff between the cost premium for flexible (versus efficient) production capacity and the opportunity costs of idle capacity. Spackling amortizes fixed costs of capacity more effectively and thus can increase profits from mass customization vis‐à‐vis a focus strategy, even with higher cost production for the standard goods. We illustrate our framework with data from a messenger bag manufacturer.     

配额——交易机制下动态批量生产和减排投资策略研究

随着我国碳排放交易市场的建立和发展,在碳排放约束下逐步降低单位产出的碳排放水平成为企业生产经营管理中的中长期约束性目标。本文在一个多周期决策模型中研究了配额-交易机制下企业的最优动态批量生产、碳排放权交易和减排投资联合决策问题。生产商在整个决策周期期初决定是否进行减排投资以及投资规模,根据每个周期的生产计划决定减排设备的运行计划。根据节能减排技术的特点,本文假设生产商运行减排设备时不仅降低了产品的单位生产碳排放量,而且降低了产品的单位生产成本。本文基于广义Benders分解法对模型进行了最优性分析,得到了最优生产决策和最优减排投资决策的一些基本性质,并通过数值实验分析了碳排放配额和碳排放权价格对生产商总成本、总排放以及减排投资决策的影响。本文的数值实验分析结果发现:(1)当碳交易市场上的碳排放权充足时,减少碳排放配额或改变碳排放配额的分配方式并不能影响生产商的碳排放水平;(2)碳排放权价格是影响生产商的碳排放水平和减排投资规模的关键因素;(3)随着碳排放权价格的上升,即使拥有足够的碳排放配额,生产商仍会不断提高减排投资规模以获得减排收益。研究结果对碳排放交易体系下生产企业进行减排技术投资具有较强的管理启示。     

同步物流系统下准时化生产与配送调度问题研究

对于"加工-装配"行业而言,物流管理水平的高低直接决定了供应链绩效的好坏。本文以Supply Hub运作模式为背景,研究同步物流下装配系统中各节点的生产与配送调度问题。建立供应链各参与方的生产与配送模型,并通过规划求解得到供应商和制造商的最优生产周期、零部件的最优配送间隔以及零售商的最佳采购周期。最后,结合数值实验,对同步物流模式和传统物流模式下的供应链绩效进行了对比分析。研究结果表明:较之传统物流模式,基于同步化物流方式的装配系统总成本更低,这主要得益于库存成本的下降;由于采取拉动式的生产模式,因此同步物流系统下供应链中的生产和配送活动更加频繁;生产调整成本的增加提高了制造商的平均总成本,由此可见在同步物流系统下,供应商、制造商和零售商之间更需要相互协商和收益共享,从而实现多赢。