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。     

需求不确定条件下价值网竞争优势研究

本文通过建模分析,发现在需求不确定的条件下,价值网企业(拥有紧密的客户资源网和供应合作网)可识别需求不确定性,并可通过柔性生产和快速反应把握这种不确定性,借助于适度裕量的产能投资策略,有效规避缺货风险和存货积压风险,从而获取更高的收益。     

基于UML的钢铁企业APS订单计划系统建模

在基于APS的钢铁企业生产计划体系中,订单计划将客户订单转化为生产订单,其内容包括对订单在工序上的分解及交货期的初步确定等.本文从某钢铁企业对订单计划管理的实际需求出发,采用UML建模语言对钢铁企业APS中的订单计划系统进行需求分析,构造了系统的用例图和分析类图,并对订单拆分、库存匹配和产能匹配等典型用例进行了动态建模.本文研究的订单计划系统以客户订单为输入,可以实现订单的拆分、库存匹配和产能匹配,确定订单的交货期,进而合理安排中长期订单计划,达到帮助企业编制高效的生产批量计划和生产调度方案的目的.     

Make-to-Order 模式下多产品占线生产策略研究

本文研究的是按订单生产模式企业面对需求不确定条件下的生产决策问题.这类企业经常会遇到如下情形:客户的产品订单需求变动具有不可预期性,同时生产单批产品的固定成本较高,企业在承担一定的延期惩罚费用的条件下可以延期交货.因此需要考虑采用某种适当的生产策略来减少成本损失,即需要研究在未来产品订单需求不确定的条件下确定在什么时间对哪个产品进行生产使得总的固定生产成本及延期惩罚成本最优的决策问题.以往的研究一般都是假设包括订单到达时刻和订单需求量等需求信息是随机波动的,而实际情况中这些信息常常是不可预测且不能用概率分布刻画的.因此,本文从占线理论出发考虑了未来订单需求信息未知情形下的最优生产决策问题,构造了相应的数学模型,设计了一个竞争策略,证明了其具有较好的常数竞争比.数值分析进一步验证了该策略的有效性.     

基于网络外部性的规模收益与产品差异化

通过构造一个纵向产品差异化的两阶段模型(先决定产品质量再决定产量) ,研究了当产 品具有网络外部性特征时,其规模收益特征对企业的产品质量差异度、利润、产品价格和需求 等因素的影响. 然后对产品的规模收益递增和递减两种情况作了比较分析并得出相应的结论. 研究表明,当不考虑网络外部性时递减规模收益假设下产品的质量(不论是高质量还是低质 量) 都要低于递增规模收益情形;而考虑网络外部性时递减规模收益假设下的高质量要远大于 递增规模收益假设下的质量;递减规模收益假设下的市场需求都要低于递增规模收益假设下 的市场需求,这与产品是否具有网络外部性特征无关.     

基于EMSR方法的订单接受策略研究

选择性的订单接受策略对于按订单生产的制造型企业具有重要意义。本文在单一资源的情况下,采用收益管理中常用的期望边际座位收益EMSR-a和EMSR-b方法,分别得出了利润最大化的订单接受策略。然后,把这两种策略运用到一个算例,与FCFS策略进行比较。数据结果显示在企业利润方面,这两种策略都明显优于FCFS,利润均提高20%以上。     

Analysis of Supply Chain's Demand Information Sharing Values Based on Decision-Maker's Risk Aversion Characteristics

在随机需求条件下,利用条件风险估值( conditional value-at-risk,CVaR)的风险度量准则建立了供应链的需求信息共享决策模型,着重分析了零售商的风险规避程度以及市场需求的不确定性信息对供应链各决策者以及供应链整体信息共享价值的影响.研究结果表明,需求信息共享价值与零售商的风险规避程度、市场不确定性大小以及市场不确定信息所预测的市场需求变化情况有关.数值分析结果表明,零售商越害怕市场的不确定性风险,需求信息共享越有利于提升分散供应链的运作效率;但当市场信息反映出未来的市场需求是消极且零售商接近风险中性时,供应链的需求信息共享价值反而小于零,此时没有进行信息共享的必要.     

互联网借贷能否实践"扶弱解难"的普惠金融理念——基于"人人贷"数据的分析

本文研究了存在随机产出风险时供应链上游高技术生产企业的专利运作战略.分别构建了3种最常见专利战略——独占、授权和共享下的供应链上下游决策模型.独占战略下,上游供应商自己生产零件并向下游制造商供货,但生产过程存在随机产出风险;授权战略下,供应商不生产零件但把技术授权给代工厂商并收取专利许可费;共享战略下,供应商把专利共享给代工厂商,当其随机产出实现且不能满足下游订单时由代工厂商来补足订单.研究结果表明,对供应商而言,若下游制造商面临的市场规模较小,则授权战略占优;若市场规模较大,此时哪种战略更好取决于其供应的可靠性:当可靠性较低时独占战略占优,当可靠性较高时共享战略占优.与分散决策相比,集中决策下授权战略占优的区间扩大,而独占战略占优的区间缩小.此外本文还发现,对供应商而言最优的专利战略和社会最优(即对整条供应链而言最优的专利战略)之间存在一定程度的偏离,且偏离的程度随启动成本的降低而加剧,随可靠性的降低而缓解.     

有限缓冲区的多节点订单接受模型与算法

订单接受问题广泛存在于生产管理中,而现有多节点订单接受问题中大多不考虑缓冲区约束对订单接受的影响。针对这一问题,以缓冲区约束的多节点生产为背景,建立了订单接受模型。利用改进NEH算法、离散和声搜索算法和变邻域搜索的混合算法对模型进行求解。实验结果显示,当问题规模较小时,算法取得较好的计算效果。问题规模较大时,求解效果一般。缓冲区的大小对订单完工时间影响较小,与无限缓冲区的计算结果相似。混合算法具有较好的求解速度,能够有效求解问题模型。     

随机订单干扰下考虑合并决策的供应链网络调度研究

为满足客户个性化需求的快速响应，企业需具备柔性的外部供应链网络结构，以协同方式共同完成产品生产。本文考虑具有交互特征的多个不同类型协同供应链网络，构建生产成本、库存成本、等待成本以及订单延期交货成本最小化的目标函数，并设计合并决策判断变量构建同类订单在相同协同企业处的开始时间约束。此外，模型中考虑确定订单以及随机订单两种类型订单，并设计随机订单在区间时间段中离散时间点的到达概率。为获取协同供应链网络生产调度优化策略，基于随机订单到达与否的场景构建四个子决策模型，并进一步设计判断提前安排随机订单协同生产和不提前安排随机订单协同生产不同调度策略下成本差异的主决策模型。仿真结果表明合并决策在带来生产成本效益的同时也引起了部分订单的延期交货，且不同类型的协同供应链网络对随机订单的抗干扰能力存在一定程度的差异。     

Impacts of buyers' order batching on the supplier's demand correlation and capacity utilization in a branching supply chain

There are several ways for a manufacturer to cope with demand uncertainty, e.g. inventories, capacity and cash. Among these, this study focuses on the second one, the capacity, especially on the problem of investing in flexible facilities and enhancing their utilization via demand management. In a supply chain, demands that an upstream firm (supplier) faces are the purchase orders from the downstream members (buyers). We analyse the impacts of buyers' order batching on the supplier's demand correlation and capacity utilization in a simple branching supply chain, where a supplier does business with two buyers whose market demands are correlated. Our results show that: (i) a supplier whofacesa smaller demand correlation coefficient (i.e. closer to-1) would invest more in flexible facilities; (ii) an increase in order lot size mitigates the correlation of purchase orders; and (iii) a supplier whose facilities are flexible would prefer frequent orders with smaller lots only when market demands are highly negatively correlated. This means that even suppliers whose facilities are flexible would rather prefer infrequent orders with larger lots in the presence of positively correlated demands. Additionally, some managerial implications are discussed.     

Product mix in the TFT-LCD industry

As operational costs and equipment depreciation in the TFT-LCD (thin film transistor-liquid crystal display) industry are a high percentage of the total cost, most manufacturers usually fully utilise their production capacity to reduce the average unit cost. However, when the market demand is less than the supply the stock of panels increases; this forces manufacturers to instigate a price war to reduce levels of stock and results in a wide fluctuation in panel prices. Inventory stocks of panels could be decreased by optimising the product mix. This will help manufacturers to reduce the risk of holding stocks, increase profit, and improve competitive advantage. This study uses mixed integer linear programming (MILP) to construct a product mix for the TFT-LCD industry given the conditions of profit, productivity, raw materials supply, and market demand. A case study shows that this model is proven to be effective in generating product mix for the TFT-LCD industry while improving profit. The product mix generated by this model can provide a reference for the sales department for orders and shipping, for the production department for the order quantity, and for master production scheduling for each product.     

Replanning the Master Production Schedule for a Capacity-Constrained Job Shop

This research examines the use of both frozen and replanning intervals for planning the master production schedule (MPS) for a capacity-constrained job shop. The results show that forecast error, demand lumpiness, setup time, planned lead time, and order size have a greater impact on the mean total backlog, total inventory, and number of setups than the frozen and replanning intervals. The study also shows that a repetitive lot dispatching rule reduces the importance of lot sizing, and a combination of repetitive lot dispatching rule and single-period order size consistently produces the lowest mean total backlog and total inventory. The results also indicate that rescheduling the open orders every period produces a lower mean total backlog and total inventory when the forecast errors are large relative to the order sizes. This result suggests that the due date of an open order should be updated only when a significant portion of the order is actually needed on the new due date.     

An association-based clustering approach to order batching considering customer demand patterns

Research on warehousing systems has gained interest since the 1980s, reflecting the fact that supply chain management has pursued a demand-driven organization with high product variety, small order sizes, and reliable short response times throughout the supply chain. This market trend has affected warehouse management and operations tremendously. Order batching in a warehouse attempts to achieve high-volume order processing operations by consolidating small orders into batches. Order batching is an essential operation of order processing in which several orders are grouped into batches. This paper describes the development of an order batching approach based on data mining and integer programming. It is valuable to discover the important associations between orders such that the occurrence of some orders in a batch will cause the occurrence of other orders in the same batch. An order-clustering model based on 0–1 integer programming can be formulated to maximize the associations between orders within each batch. From the results of several test problems, the proposed approach shows its ability to find quality solutions of order batching problems.     

Revenue Management in Order‐Driven Production Systems

This article investigates the effectiveness of a tactical demand‐capacity management policy to guide operational decisions in order‐driven production systems. The policy is implemented via a heuristic that attempts to maximize revenue by selectively accepting or rejecting customer orders for multiple product classes when demand exceeds capacity constantly over the short term. The performance of the heuristic is evaluated in terms of its ability to generate a higher profit compared to a first‐come‐first‐served (FCFS) policy. The policies are compared over a wide range of conditions characterized by variations in both internal (firm) and external (market) factors. The heuristic, when used with a Whole Lot order‐processing approach, produces higher profit compared to FCFS when profit margins of products are substantially different from each other and demand exceeds capacity by a large amount. In other cases it is better to use the heuristic in conjunction with the Split Lot order‐processing approach.     

随机需求环境下联产品系统价格与产量决策研究

基于固定比例生产技术和多产品随机需求的情形,研究了联产品制造商的两阶段产量和价格联合优化模型。通过反向倒推的优化求解,得到了联产品制造商的最优产量和价格决策以及变化规律。同时研究了需求服从均匀分布时,需求波动对均衡的影响。研究结果表明,在订货成本较低和一种产品的需求波动性较大时,当另外一种产品的波动增大,则该产品的最优订货量增大,同时价格下降。借助数值仿真,分析了价格敏感度和产出比例对最优决策和利润的影响。结果表明,在给定一种产品的价格敏感度时,另外一种的价格敏感度越大,那么该产品的价格就越低,制造商的订货量就下降。当一种产品的产出比例固定时,另一种产品的产出比例上升时,则该产品的价格下降,制造商的订货量下降,总利润上升。     

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。     

Concerning Workload Control and Order Release: The Pre‐Shop Pool Sequencing Decision

Every production planning concept that incorporates controlled order release will initially withhold jobs from the shop floor and create a pre‐shop pool. Order release is a key component of the Workload Control concept that aims to maintain work‐in‐process within limits while ensuring due dates are met. Order release includes two decisions: (i) a sequencing decision that establishes the order in which jobs are considered for release; and, (ii) a selection decision that determines the criteria for choosing jobs for release. While selection has received much research attention, sequencing has been largely neglected. Using simulation, this study uncovers the potential for performance improvement in the sequencing decision and improves our understanding of how order release methods should be designed. Although most prior studies apply time‐oriented sequencing rules and load‐oriented selection rules, analysis reveals that load balancing considerations should also be incorporated in the sequencing decision. But an exclusive focus on load balancing is shown to increase mean tardiness and, paradoxically, require high workloads. A new sequencing rule is developed that only balances loads when multiple orders become urgent. It avoids high mean tardiness and allows the shop to operate at a low workload level. At the same time, the percentage tardy is reduced by up to 50% compared to a purely time‐oriented rule. The findings have implications not only for Workload Control but for any concept that features order release control, such as ConWIP and Drum‐Buffer‐Rope.     

需求不确定下企业生产规模选择及影响因素研究

基于企业生产规模的不同情况，讨论了需求不确定下企业生产规模决策问题，构建了企业生产规模决策模型并得出了不同条件下的表达式。分析表明：需求不确定下企业存在生产最优规模，随着成本的增加，企业最优生产规模临界值将增大，利率、市场力量与企业最优生产规模负相关；企业生产规模为Q时，企业最优生产规模与单位时间收益流的波动率和期望增长率正相关，而与单位成本无关；在区间0≤q（t）≤Q，企业最优生产规模与企业单位时间收益流的波动率负相关，随着企业单位时间收益流的期望增长率的增加先降低后增加，且随着企业单位成本C的增加先不变后增加。这为需求不确定下企业生产规模决策提供了一种解释。     

考虑捐赠行为的食品动态定价策略研究

由于质量控制不当和库存过多导致的浪费是企业管理易腐食品面临的主要挑战。针对当前食品浪费严重的问题，建立考虑变质率的动态定价模型，研究捐赠行为下单一定价、两次定价与多级折扣定价三种定价策略对食品企业最优决策的影响。通过数值分析，发现捐赠行为能够提升企业利润且在多级折扣定价策略下效果更为显著，但当折扣次数较少时，单一定价策略对考虑捐赠的企业而言更优；食品最初质量、变质率、打折时间点、捐赠时间点、税收返回比率均是影响企业定价决策的重要因素；若质量差异越大，企业在多级折扣定价策略下的利润会减少，而考虑捐赠行为会使得企业利润呈上升趋势；在变质率越高时，考虑捐赠的单一定价策略会降低企业的利润，但对多级折扣定价策略下的利润影响不大；当折扣时间越接近于捐赠时间点时，基于捐赠行为的多级折扣定价策略会更优；当捐赠时间点越接近于保质期时，考虑捐赠的价格策略会优于不考虑捐赠时的价格策略。此外，研究还表明增加税收返回比率对考虑捐赠下的定价策略不一定是有利的。