The impact of exponential smoothing forecasts on the bullwhip effect

An important phenomenon often observed in supply chain management, known as the bullwhip effect, implies that demand variability increases as one moves up the supply chain, i.e., as one moves away from customer demand. In this paper we quantify this effect for simple, two‐stage, supply chains consisting of a single retailer and a single manufacturer. We demonstrate that the use of an exponential smoothing forecast by the retailer can cause the bullwhip effect and contrast these results with the increase in variability due to the use of a moving average forecast. We consider two types of demand processes, a correlated demand process and a demand process with a linear trend. We then discuss several important managerial insights that can be drawn from this research. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 269–286, 2000     

新体制下战场柔性后勤保障网链建设

为满足新体制下联合作战后勤保障需求,本文采用系统分析方法,针对战场后勤保障力量体系构建,提出以联勤保障部队为主体,构建一体化后勤保障网链。针对后勤保障网链保障能力的可变性,提出提升后勤保障网链柔性建设运用的方法措施。     

Excess procurement strategies by a dominant buyer under constrained supply

Supply chains are often characterized by the presence of a dominant buyer purchasing from a supplier with limited capacity. We study such a situation where a single supplier sells capacity to an established and more powerful buyer and also to a relatively less powerful buyer. The more powerful buyer enjoys the first right to book her capacity requirements at supplier's end, and then the common supplier fulfills the requirement of the less powerful buyer. We find that when the supplier's capacity is either too low (below the lower threshold) or too high (above the higher threshold), there is no excess procurement as compared to the case when supplier has infinite capacity. When the supplier's capacity is between these two thresholds, the more powerful buyer purchases an excess amount in comparison to the infinite capacity case.     

Stochastic production capacity: A bane or a boon for quick response supply chains?

The quick response (QR) system that can cope with demand volatility by shortening lead time has been well studied in the literature. Much of the existing literature assumes implicitly or explicitly that the manufacturers under QR can always meet the demand because the production capacity is always sufficient. However, when the order comes with a short lead time under QR, availability of the manufacturer's production capacity is not guaranteed. This motivates us to explore QR in supply chains with stochastic production capacity. Specifically, we study QR in a two-echelon supply chain with Bayesian demand information updating. We consider the situation where the manufacturer's production capacity under QR is uncertain. We first explore how stochastic production capacity affects supply chain decisions and QR implementation. We then incorporate the manufacturer's ability to expand capacity into the model. We explore how the manufacturer determines the optimal capacity expansion decision, and the value of such an ability to the supply chain and its agents. Finally, we extend the model to the two-stage two-ordering case and derive the optimal ordering policy by dynamic programming. We compare the single-ordering and two-ordering cases to generate additional managerial insights about how ordering flexibility affects QR when production capacity is stochastic. We also explore the transparent supply chain and find that our main results still hold.     

Data-driven research in retail operations—A review

We review the operations research/management science literature on data-driven methods in retail operations. This line of work has grown rapidly in recent years, thanks to the availability of high-quality data, improvements in computing hardware, and parallel developments in machine learning methodologies. We survey state-of-the-art studies in three core aspects of retail operations—assortment optimization, order fulfillment, and inventory management. We then conclude the paper by pointing out some interesting future research possibilities for our community.     

基于马尔可夫分析的人才拥有量研究

基于马尔可夫分析理论,给出了人才拥有量预测的马尔可夫模型,并且讨论了模型中转移概率的确定及模型的预测质量等问题.     

Simultaneous production of market‐specific and global products: A two‐stage stochastic program with additional demand after recourse

This paper analyzes the simultaneous production of market‐specific products tailored to the needs of individual regions and a global product that could be sold in many regions. We assume that the global product costs more to manufacture, but allows the decision concerning the allocation of products to regions to be delayed until after the manufacturing process has been completed. We further assume that there is additional demand after the region allocation but prior to delivery, extending the two‐stage stochastic program with recourse to include additional stochastic demand after the recourse. This scenario arises, for example, when there is additional uncertainty during a delivery delay which might occur with transoceanic shipments. We develop conditions for optimality assuming a single build‐allocate‐deliver cycle and stochastic demand during both the build and deliver periods. The optimal policy calls for the simultaneous production of market‐specific and global products, even when the global product is substantially more costly than the market‐specific product. In addition, we develop bounds on the performance of the optimal policy for the multicycle problem. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 438–461, 2003     

基于打击链的智能武器风险分析与控制方法研究

打击链是分析武器和系统等作战要素有效性的一种方法.针对当前智能武器概念缺乏一致定义的问题,本文提出了基于打击链作战方式的智能武器判定方法.针对智能武器认定困难引发的军控措施争论,分析了智能武器两方面的失控风险:人失去对自主武器的控制权与自主武器本身存在不可控因素和缺陷;以及智能武器的问责困境:如何在指挥者、编程者与智能...     

基于Petri网的指挥流程建模与优化

鉴于Petri网在企业业务流程优化与重组方面的成功运用,遂将Petri网原理应用于作战指挥流程的建模与优化,以期获得最优作战指挥流程.文中首先阐述Petri网基本原理,然后介绍指挥流程建模的Petri网模型,最后给出指挥流程优化的原则及基本模型,并利用Petri网对指挥流程进行建模和优化,结果表明Petri网理论能够明显优化作战指挥流程.提高作战指挥效率.     

Quality risk in outsourcing: Noncontractible product quality and private quality cost information

This article addresses the concept of quality risk in outsourcing. Recent trends in outsourcing extend a contract manufacturer's (CM's) responsibility to several functional areas, such as research and development and design in addition to manufacturing. This trend enables an original equipment manufacturer (OEM) to focus on sales and pricing of its product. However, increasing CM responsibilities also suggest that the OEM's product quality is mainly determined by its CM. We identify two factors that cause quality risk in this outsourcing relationship. First, the CM and the OEM may not be able to contract on quality; second, the OEM may not know the cost of quality to the CM. We characterize the effects of these two quality risk factors on the firms' profits and on the resulting product quality. We determine how the OEM's pricing strategy affects quality risk. We show, for example, that the effect of noncontractible quality is higher than the effect of private quality cost information when the OEM sets the sales price after observing the product's quality. We also show that committing to a sales price mitigates the adverse effect of quality risk. To obtain these results, we develop and analyze a three‐stage decision model. This model is also used to understand the impact of recent information technologies on profits and product quality. For example, we provide a decision tree that an OEM can use in deciding whether to invest in an enterprise‐wide quality management system that enables accounting of quality‐related activities across the supply chain. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009