供应商—零售商联合库存的供应链库存成本分析

联合库存是商业零售企业改善供应链库存管理的有效途径。本文通过对传统供应模式与联合库存模式下库存成本模型的比较分析,发现联合库存模式能够很好地降低整个供应链的库存成本;通过算例分析证明了联合库存降低供应链成本的现实意义。     

基于时变需求的供应链基本库存水平优化研究

在时变需求环境下,基于模型推导得到供需双方基本库存水平局部优化与整体优化决策方程,并基于算例对基本库存水平整体优化的成本绩效以及需求时变性的影响进行数据分析,得到如下重要结论:基本库存水平整体优化明显降低供应链库存成本.     

基于交货期库存协调的供应链转移定价研究

在将缺货成本和延期惩罚成本纳入决策模型的前提下,对供应商—制造商两阶供应链在转移定价、安全库存,以及总成本之间的相互作用进行了探讨:首先探讨基于 Stackelberg 收益共享定价机制的最优决策;然后,以一体化供应链为参照系,探讨对供应链各成员的行为进行优化的两部制(two-part scheme)收益共享转移定价决策在实践中的运用;最后,探讨模型中部分变量变化对最优决策所产生的影响.通过分析发现,承诺的交货期、延期惩罚成本与缺货成本将会影响供应链的总成本和转移定价决策,进而影响供应商的最优库存决策,而制造商则可以通过适当的激励机制设计,激励供应商按照供应链整体最优的方式进行转移定价、安全库存及相关决策.     

信息不对称条件下可控提前期供应链协调机制研究

探讨了信息不对称条件下提前期可以通过额外的赶工成本来加以控制的两级供应链协调问题。分别建立了分散决策和集中决策情形下的可控提前期供应链库存优化模型,并在充分考虑各参与方个体理性的基础上,探讨了分销商库存信息不对称情形下的供应链协调机制。最后通过数值分析证明该协调机制既能诱使分销商申报真实的库存持有成本信息,又能够在供应链合作双方成本均有改进的基础上,达到供应链系统的最优。     

基于神经网络的供应链安全库存预测模型

供应链的不确定性要求企业建立安全库存,随着现代产品多样性的增加、产品生命周期不断缩短,安全库存成为库存成本的重要组成部分。供应链成功的关键是在不损害产品供应水平的情况下,找到降低安全库存水平的有效途径。本文主要采用利用一种新型的GRNN神经网络技术,构建安全库存预测模型,并对模型的指标设置与仿真过程进行分析。     

一类制造商与零售商纵向集成供应链的最优生产与库存策略

对供应链内部库存系统进行优化控制是提高供应链协调性的一种重要手段.而竞争的不断激化加剧了需求的波动,此时作为消化需求波动缓冲库的库存系统对提高供应链的协调性起着重要的作用.本文综合考虑顾客退货、库存自然损失等随机因素对供应链生产和库存策略的影响,构造出一类制造商与零售商纵向集成的供应链的最优生产与库存模型,并借助于动态规划的最优性原理给出了最优生产库存策略的表达式.本文从协调生产与销售的角度探索了提高供应链协调性的方法,不仅对供应链协调性的理论研究而且对实际应用中如何供应链协调性都作了一个崭新的尝试.     

不确定需求环境下多级库存系统优化与协调模型研究

论文首先将模糊随机变量扩展为混合随机变量,并用来描述不确定需求.然后对多级单周期库存系统在模糊随机和混合随机需求环境下的优化与协调问题作了研究,提出了通过集成库存管理使库存系统整体收益期望值最大化的优化模型和协调合作伙伴利益的数量折扣契约模型,并根据遗传算法理论和计算机模拟技术设计了求解模型的智能算法.最后通过实例对模型进行了仿真分析.     

一类供应链的Stackelberg主从对策问题研究

本文研究了供应链中的一般订货模式和协调模式,提出了一类供应链Stackelberg主从对策问题,卖方作为主方给出最小补充期策略,买方作为从方以最优库存策略响应。考虑一致价格折扣弥补买方的库存成本增加,以及买方的库存成本合理化,建立买方需求确定下的卖方成本优化模型。最后,应用遗传算法对石油分销系统Stackelberg主从对策问题离线仿真计算,得出Stackelberg主从对策均衡解。     

供应商管理库存下基于消费者行为偏好的全渠道运营策略

在供应商管理库存背景下,研究了消费者线上参考效应、线下库存效应以及渠道偏好对供应链成员运营策略的影响。利用微分博弈和连续型动态规划理论获得了独立运营、基于供应商服务成本分担契约的部分合作运营以及协同运营三种模式下的成员策略及绩效。由比较静态分析和对比分析发现：库存效应对生产量具正向影响,对产品质量、大数据营销服务和线下服务具负向影响;消费者不同条件下的线上偏好对企业决策有不同的影响;供应商服务成本分担契约能激励零售商提升线下产品服务,一定程度上改进企业独立运营的绩效水平。为进一步协调分散式供应链,在上述契约基础上设计了供应商收益分享及双边成本分担契约。数值算例发现：新契约在一定条件下可实现分散式供应链的完美协调;消费者参考质量过度依赖品牌商誉易产生"锚定心理",不仅会抑制成员生产和服务积极性,造成库存积压,阻碍品牌商誉积累,损害企业利润,也不利于消费者获得更好的购物体验。     

企业库存物资结构的优化方法

本文概述了企业物资供应的重要性及目前企业库存积压的原因，分析了过去在库存周转量计算方法中存在问题，引进了适合现代市场经济条件下的库存结构优化方法－进消差训存控制模型，并对此模型提出了的出发点，目标，依据，适用条件等都作了阐述，并对此模型作了实证性的应用，收到了明显经济效果，论证了此模型在实际应用中的可行性和有效性。     

供应链库存合约研究

研究了制造商与其供应商的供应链最优库存策略和在非合作情况下的库存策略,比较分析了两种情况下的库存策略,并设计了库存合约;分析表明,制造商通过设计有效的转移支付合约,可以实现供应链库存的最优化。     

供应链提前期供需联合优化库存模型研究

本文研究由生产商和客户组成的二级供应链库存联合优化问题, 假设提前期服从均匀分布, 提前期订货受生产商的生产行为和客户的订货行为的制约, 建立了以库存成本为目标函数的供应链提前期供需库存模型, 提出了联合优化解决方案, 证明了目标函数在最优订货量和最优订货次数处存在最小目标值。在此基础上, 分析了提前期对供应链库存联合优化决策的影响。数据分析表明, 联合优化决策方法的库存成本曲线始终在分散决策优化方法的成本曲线的下方, 因此联合决策方法是非常有效的。     

Coordination and Priority Decisions in Hybrid Manufacturing/Remanufacturing Systems

Companies are increasingly realizing the need to coordinate their manufacturing and remanufacturing operations. This can be a challenge due to the inherent variability in the condition and amount of returns, which has a direct impact on remanufacturing costs and leadtimes. In this paper, we develop a modeling framework to compare two alternative strategies that use either manufacturing or remanufacturing as the primary means of satisfying customer demand. Of course, in the event that the demand cannot be met by the prioritized process, the secondary process is used as a contingency. In our basic model, the priority decisions are made at the component level in replenishing the serviceable inventory, while the disposal and new component ordering decisions are made independently. The second model represents the coordination of remanufacturable and new component inventory control decisions. Using simulation‐based optimization on a large number of experiments, we observe that when prioritization is in the upstream echelon and there is no coordination in managing component stocks, there exists a critical return ratio, below which it is beneficial to give priority to manufacturing and above which it is beneficial to give priority to remanufacturing. We also see that coordinated control of the component inventories considerably reduces the importance of prioritization. These observations remain valid when congestion in the shop floor is also taken into account. We also study the benefits of state‐dependent dispatching policies in a realistic case.     

基于时变需求的一对一供应链库存决策研究

随着竞争日趋激烈,需求变化节奏加快,需求时变性越加明显.在需求时变的环境下探讨了等周期补货情形下缺货时点优化以及非等周期补货情形下缺货时点与补货时点优化问题,特别着重研究了补货时点局部优化与整体优化的决策模型,并对非等周期补货与等周期补货、补货时点整体优化与补货时点局部优化作对比分析,并发现,在时变需求环境下非等周期补货与补货时点整体优化在降低库存成本方面具有明显优势.同时,分析了补货时点优化的效果与供需双方补货次数、需求时变性的关系.     

Robust Stochastic Lot‐Sizing by Means of Histograms

Traditional approaches in inventory control first estimate the demand distribution among a predefined family of distributions based on data fitting of historical demand observations, and then optimize the inventory control using the estimated distributions. These approaches often lead to fragile solutions whenever the preselected family of distributions was inadequate. In this article, we propose a minimax robust model that integrates data fitting and inventory optimization for the single‐item multi‐period periodic review stochastic lot‐sizing problem. In contrast with the standard assumption of given distributions, we assume that histograms are part of the input. The robust model generalizes the Bayesian model, and it can be interpreted as minimizing history‐dependent risk measures. We prove that the optimal inventory control policies of the robust model share the same structure as the traditional stochastic dynamic programming counterpart. In particular, we analyze the robust model based on the chi‐square goodness‐of‐fit test. If demand samples are obtained from a known distribution, the robust model converges to the stochastic model with true distribution under generous conditions. Its effectiveness is also validated by numerical experiments.     

Linking inventory efficiency,productivity and responsiveness to retail firm outperformance: empirical insights from US retailing segments

This paper establishes an empirical model linking a retail firm’s inventory management effectiveness to superior competitive operational performance for specific product-line retail segments. Using 16?years of US retail firm financial data from the COMPUSTAT Fundamentals database across 12 distinct competitive retailing segments, we develop and test a time-series model that links several inventory management execution measures to the competitive operational outperformance of retail firms. The analysis presented provides strong evidence that measures of inventory management performance are not ‘one size fits all’ for the retail industry, and helps to explain why extant research has had difficulty linking inventory control policy effectiveness to operational performance advantages in retailing. We discuss the implications of these empirical findings on the study of inventory policy execution, and offer some guidance for further research.     

Optimal ordering time interval taking account of time value

In this paper, the optimal inventory policies for an infinite lime span taking account of time value is discussed. First, bounds for the optimal ordering time interval are derived. Second, with these bounds, a simple algorithm to compute die optimal ordering time interval is developed. Numerical examples are given to illustrate the algorithm.     

基于似然估计的零售商库存鲁棒均值-风险模型

针对具有风险厌恶的零售商,建立了权衡期望利润和条件风险值（CVaR）的均值-风险库存优化模型,给出了离散需求分布不确定条件下能实现帕累托最优但具有较高保守性和非帕累托最优但具有较低保守性的两种鲁棒对应。针对不确定需求分布,在仅知历史需求样本数据情况下,应用统计推断理论构建了满足一定置信水平的基于似然估计的需求概率分布不确定集。在此基础上,运用拉格朗日对偶理论,将上述两种鲁棒对应模型转化为易于求解的凹优化问题,并证明了其与原问题的等价性。最后,针对实际案例进行了数值计算,分析了不同系统参数和样本规模对零售商最优库存决策及其运作绩效的影响,并给出了零售商期望利润和条件风险值两个目标权衡的帕累托有效前沿。结果表明,采用基于似然估计的鲁棒优化方法得到的零售商库存策略具有良好鲁棒性,能够有效抑制需求分布不确定性对零售商库存绩效的影响。而且,历史需求样本规模越大,鲁棒库存策略下的零售商运作绩效越接近最优情况。进一步,通过对比发现,两种鲁棒对应模型虽然保守性不同,但在最终库存策略上保持一致。     

On the integration of production,inventory and trade-credit policies

The primary objective of this paper is to highlight the need for the integration of procurement, production and marketing strategies. This is accomplished through the development of a model for a small firm, where the objective is the maximization of the present value of profits within an infinite horizon framework Other features include a JIT-like procurement system, a continuous production situation and a combination of cash discounts and credit period to stimulate sales. A numerical example is presented to illustrate the main features of the study.     

ABC Classification: Service Levels and Inventory Costs

ABC inventory classifications are widely used in practice, with demand value and demand volume as the most common ranking criteria. The standard approach in ABC applications is to set the same service level for all stock keeping units (SKUs) in a class. In this paper, we show (for three large real life datasets) that the application of both demand value and demand volume as ABC ranking criteria, with fixed service levels per class, leads to solutions that are far from cost optimal. An alternative criterion proposed by Zhang et al. performs much better, but is still considerably outperformed by a new criterion proposed in this paper. The new criterion is also more general in that it can take criticality of SKUs into account. Managerial insights are obtained into what class should have the highest/lowest service level, a topic that has been disputed in the literature.