供应链下的多级存货管理【外文翻译】

1、本科毕业论文（设计）外 文 翻 译原文：Multi-echelon inventory management in supply chains Historically, the echelons of the supply chain, warehouse, distributors, retailers, etc., have been managed independently, buffered by large inventories. Increasing competitive pressures and market globalization are forcing firm

2、s to develop supply chains that can quickly respond to customer needs. To remain competitive and decrease inventory, these firms must use multi-echelon inventory management interactively, while reducing operating costs and improving customer service. Supply chain management (SCM is an integrative ap

3、proach for planning and control of materials and information flows with suppliers and customers, as well as between different functions within a company. This area has drawn considerable attention in recent years and is seen as a tool that provides competitive power .SCM is a set of approaches to in

4、tegrate suppliers, manufacturers, warehouses, and stores efficiently, so that merchandise is produced and distributed at right quantities, to the right locations and at the right time, in order to minimize system-wide costs while satisfying service-level requirements .So the supply chain consists of

5、 various members or stages. A supply chain is a dynamic, stochastic, and complex system that might involve hundreds of participants.Inventory usually represents from 20 to 60 per cent of the total assets of manufacturing firms. Therefore, inventory management policies prove critical in determining t

6、he profit of such firms. Inventory management is, to a greater extent, relevant when a whole supply chain (SC, namely a network of procurement, transformation, and delivering firms, is considered. Inventory management is indeed a major issue in SCM, i.e. an approach that addresses SC issues under an

7、 integrated perspective.Inventories exist throughout the SC in various forms for various reasons. The lack of a coordinated inventory management throughout the SC often causes the bullwhip effect, namely an amplification of demand variability moving towards the upstream stages. This causes excessive

8、 inventory investments, lost revenues, misguided capacity plans, ineffective transportation, missed production schedules, and poor customer service.Many scholars have studied these problems, as well as emphasized the need of integration among SC stages, to make the chain effectively and efficiently

9、satisfy customer requests (e.g. reference. Beside the integration issue, uncertainty has to be dealt with in order to define an effective SC inventory policy. In addition to the uncertainty on supply (e.g. lead times and demand, information delays associated with the manufacturing and distribution p

10、rocesses characterize SCs.Inventory management in multi-echelon SCs is an important issue, because there are many elements that have to coordinate with each other. They must also arrange their inventories to coordinate. There are many factors that complicate successful inventory management, e.g. unc

11、ertain demands, lead times, production times, product prices, costs, etc., especially the uncertainty in demand and lead times where the inventory cannot be managed between echelons optimally.Most manufacturing enterprises are organized into networks of manufacturing and distribution sites that proc

12、ure raw material, process them into finished goods, anddistribute the finish goods to customers. The terms multi-echelon or multilevelproduction/distribution networks are also synonymous with such networks (or SC, when an item moves through more than one step before reaching the final customer. Inve

13、ntories exist throughout the SC in various forms for various reasons. At any manufacturing point, they may exist as raw materials, work in progress, or finished goods. They exist at the distribution warehouses, and they exist in-transit, or in the pipeline, on each path linking these facilities.Manu

14、facturers procure raw material from suppliers and process them into finished goods, sell the finished goods to distributors, and then to retail and/or customers. When an item moves through more than one stage before reaching thefinal customer, it forms a multi-echelon inventory system. The echelon s

15、tock of a stock point equals all stock at this stock point, plus in-transit to or on-hand at any of its downstream stock points, minus the backorders at its downstream stock points.The analysis of multi-echelon inventory systems that pervades the business world has a long history. Multi-echelon inve

16、ntory systems are widely employed to distribute products to customers over extensive geographical areas. Given the importance of these systems, many researchers have studied their operating characteristics under a variety of conditions and assumptions. Since the development of the economic order qua

17、ntity (EOQ formula by Harris (1913, researchers and practitioners have been actively concerned with the analysis and modeling of inventory systems under different operating parameters and modeling assumptions .Research on multi-echelon inventory models has gained importance over the last decade main

18、ly because integrated control of SCs consisting of several processing and distribution stages has become feasible through modern information technology. Clark and Scarf were the first to study the two-echelon inventory model. They proved the optimality of a base-stock policy for the pure-serial inve

19、ntory system and developed an efficient decomposing method to compute the optimal base-stock ordering policy. Bessler and Veinott extended the Clark and Scarf model to include general arbores cent structures. The depot-warehouse problem described above was addressed by Eppen and Schrage who analyzed

20、 a model with a stockless central depot. They derived a closed-form expression for the order-up-to-level under the equal fractile allocation assumption. Several authors have also considered this problem in various forms. Owing to the complexity and intractability of the multi-echelon problem Hadley

21、and Whitin recommend the adoption of single-location, single-echelon models for the inventory systems.Sherbrooke considered an ordering policy of a two-echelon model for warehouse and retailer. It is assumed that stock outs at the retailers are completely backlogged. Also, Sherbrooke constructed the

22、 METRIC (multi-echelon technique for coverable item control model, which identifies the stock levels that minimize the expected number of backorders at the lower-echelon subject to a bud get constraint. This modelis the first multi-echelon inventory model for managing the inventory of service parts.

23、 Thereafter, a large set of models which generally seek to identify optimal lot sizes and safety stocks in a multi-echelon framework, were produced by many researchers. In addition to analytical models, simulation models have also been developed to capture the complex interaction of the multi-echelo

24、n inventory problems.So far literature has devoted major attention to the forecasting of lumpy demand, and to the development of stock policies for multi-echelon SCs Inventory control policy for multi-echelon system with stochastic demand has been a widely researched area. More recent papers have be

25、en covered by Silver and Pyke. The advantage of centralized planning, available in periodic review policies, can be obtained in continuous review policies, by defining the reorder levels of different stages, in terms of echelon stock rather than installation stock.Rau et al. , Diks and de Kok , Dong

26、 and Lee ,Mitra and Chatterjee , Hariga , Chen ,Axsater and Zhang , Nozick and Turnquist ,and So and Zheng use a mathematic modeling technique in their studies to manage multi-echelon inventory in SCs. Diks and de Koks study considers a divergent multi-echelon inventory system, such as a distributio

27、n system or a production system, and assumes that the order arrives after a fixed lead time. Hariga, presents a stochastic model for a single-period production system composed of several assembly/processing and storage facilities in series. Chen, Axsater and Zhang, and Nozick and Turnquist consider

28、a two-stage inventory system in their papers. Axsater and Zhang and Nozickand Turnquist assume that the retailers face stationary and independent Poisson demand. Mitra and Chatterjee examine De Bodt and Graves model (1985, which they developed in their paper Continuous-review policies for a multi-ec

29、helon inventory problem with stochastic demand, for fast-moving items from the implementation point of view. The proposed modification of the model can be extended to multi-stage serial and two -echelon assembly systems. In Rau et al.s model, shortage is not allowed, lead time is assumed to be negli

30、gible, and demand rate and production rate is deterministic and constant. So and Zheng used an analytical model to analyze two important factors that can contribute to the high degree of order-quantity variability experienced bysemiconductor manufacturers: suppliers lead time and forecast demand upd

31、ating. They assume that the external demands faced by there tailor are correlated between two successive time periods and that the retailer uses the latest demand information to update its future demand forecasts. Furthermore, they assume that the suppliers delivery lead times are variable and are a

32、ffected by the retailers order quantities. Dong and Lees paper revisits the serial multi-echelon inventory system of Clark and Scarf and develops three key results. First, they provide a simple lower-bound approximation to the optimal echelon inventory levels and an upper bound to the total system c

33、ost for the basic model of Clark and Scarf. Second, they show that the structure of the optimal stocking policy of Clark and Scarf holds under time-correlated demand processing using a Martingale model of forecast evolution. Third, they extend the approximation to the time-correlated demand process

34、and study, in particular for an autoregressive demand model, the impact of lead times, and autocorrelation on the performance of the serial inventory system.After reviewing the literature about multi-echelon inventory management in SCs using mathematic modeling technique, it can be said that, in sum

35、mary, these papers consider two, three, or N-echelon systems with stochastic or deterministic demand. They assume lead times to be fixed, zero, constant, deterministic, or negligible. They gain exact or approximate solutions.Dekker et al. analyses the effect of the break-quantity rule on the invento

36、ry costs. The break-quantity rule is to deliver large orders from the warehouse, and small orders from the nearest retailer, where a so-called break quantity determines whether an order is small or large. In most l-warehouseN-retailers distribution systems, it is assumed that all customer demand tak

37、es place at the retailers. However, it was shown by Dekker et al. that delivering large orders from the warehouse can lead to a considerable reduction in the retailers inventory costs. In Dekker et al. the results of Dekker et al. were extended by also including the inventory costs at the warehouse.

38、 The study by Mohebbi and Posners contains a cost analysis in the context of a continuous-review inventory system with replenishment orders and lost sales. The policy considered in the paper by Vander Heijden et al. is an echelon stock, periodicreview, order-up-to policy, under both stochastic deman

39、d and lead times.The main purpose of Iidas paper is to show that near-myopic policies are acceptable for a multi-echelon inventory problem. It is assumed that lead times at each echelon are constant. Chen and Songs objective is to minimize the long-run average costs in the system. In the system by C

40、hen et al., each location employs a periodic-review, or lot-size reorder point inventory policy. They show that each locations inventory positions are stationary and the stationary distribution is uniform and independent of any other. In the study by Minner et al., the impact of manufacturing flexib

41、ility on inventory investments in a distribution network consisting of a central depot and a number of local stock points is investigated. Chiang and Monahan present a two-echelon dual-channel inventory model in which stocks are kept in both a manufacturer warehouse (upper echelon and a retail store

42、 (lower echelon, and the product is available in two supply channels: a traditional retail store and an internet-enabled direct channel. Johansens system is assumed to be controlled by a base-stock policy. The independent and stochastically dependent lead times are compared.To sum up, these papers c

43、onsider two- or N-echelon inventory systems, with generally stochastic demand, except for one study that considers Markov-modulated demand. They generally assume constant lead time, but two of them accept it to be stochastic. They gain exact or approximate solutions.In multi-echelon inventory manage

44、ment there are some other research techniques used in literature, such as heuristics, vary-METRIC method, fuzzy sets, model predictive control, scenario analysis, statistical analysis, and GAs. These methods are used rarely and only by a few authors.A multi-product, multi-stage, and multi-period sch

45、eduling model is proposed by Chen and Lee to deal with multiple incommensurable goals for a multi-echelon SC network with uncertain market demands and product prices. The uncertain market demands are modeled as a number of discrete scenarios with known probabilities, and the fuzzy sets are used for

46、describing the sellers and buyers incompatible preference on product prices.In the current paper, a detailed literature review, conducted from an operational research point of view, is presented, addressing multi-echelon inventory management in supply chains from 1996 to 2005.Here, the behavior of t

47、he papers, against demand and lead time uncertainty, is emphasized.The summary of literature review is given as: the most used research technique is simulation. Also, analytic, mathematic, and stochastic modeling techniques are commonly used in literature. Recently, heuristics as fuzzy logic and GAs

48、 have gradually started to be used.Source: A Taskin Gu¨mu¨s* and A Fuat Gu¨neri Turkey, 2007. “Multi-echelon inventory management in supply chains with uncertain demand and lead times: literature review from an operational research perspective”. IMechE Vol. 221 Part B: J. Engineering

49、Manufacture. June, pp.1553-1570.译文：供应链下的多级存货管理从历史上看，多级供应链、仓库、分销商、零售商等，已经通过大量的库存缓冲被独立管理。竞争压力的增加和市场的全球化迫使企业发展能够快速满足客户需要的供应链。为了保持竞争力，降低库存，这些企业必须交互使用多级库存管理，同时降低运营成本，改善客户服务。供应链管理是一种集成的管理思想和方法，它执行供应链中从供应商到最终用户以及公司内部不同部门之间的物流的计划和控制等职能。最近几年，供应链管理这个领域已经引起了广泛关注，并且它被视作能够帮助企业获得竞争优势的一种工具。供应链管理是为了在满足服务水平的同时使系统成本达

50、到最小，从而把供应商、制造商、仓库和商店的业务效率都整合起来，使商品以正确的品质、在正确的地点、在正确的时间进行生产和销售的一套方法。可见，供应链由各种各样的成员或者阶段组成。供应链是一个动态的、随机的和复杂的系统，因此，需要许许多多的人来参与。在制造企业中，存货通常占企业总资产的20%到60%。因此，对于那些追求利润的企业，存货管理政策是关键。当考虑到整个供应链 ，也就是一个由采购、转化和运输公司组成的网络时，存货管理在很大程度上就与这整个供应链有关。在供应链管理中，存货管理的确是一种主要方法，它能从整体上解决供应链问题。因各种不同的原因，存货以不同形式存在在供应链中。在整个供应链中，存货管

51、理失衡，经常会引起“牛鞭效应”，即需求逆流而上，逐级变异放大的一个阶段。这种效应引起企业过多的存货积压，使收入减少，运输效率降低，扰乱了库存计划和产品生产计划，同时降低了企业的服务水平。许多学者已经对这些问题进行了研究，并且强调了对有效地满足客户需求的供应链各阶段之间进行整合的必要性。除了整合问题，为了确定一个有效地供应链库存政策，还必须处理不确定性问题。除了对供应（比如交货时间）和需求的不确定性，与生产和销售过程相关的信息延迟也是供应链的一个特点。多级供应链中的库存管理是一项重要的内容，因为有许多方面两者都必须相互配合，协调合作。它们还必须对它们的库存进行协调安排。有许多因素使成功的库存管理

52、变得复杂，例如。需求的不确定、交货时间、投产日期、产品价格、成本等，尤其是在不确定性的需求和交货时间下，管理者不能够将多级供应链中的存货管理得最优。大多数制造企业被组织起来形成了一个制造和分销为一体的网络，这个网络包括了原材料的采购、加工和产品的销售。当一个产品经过多个阶段才到达最终用户时，多级或者多层次生产/分销网络这些代名词也和前面所述的这样的网络意思相同。因各种不用的原因，存货以不用的形式存在在整个供应链中。在任何一个制造过程中，它们可能作为原材料、在制品或者产成品存在。它们存在于配送仓库，存在于运输途中，或者存在于管道里，它们存在于这些设备的每个链接处。制造商从供应商处采购原材料，将它

53、们加工成产品并销售给分销商，然后由分销商销售给零售商或者用户。当一个产品经过多个阶段才到达最终用户，它就形成了一个多级库存系统。某一库存节点的级库存等于这个库存节点上的所有库存加上转移或者正在转移的任何一个后续节点的库存，减去后续节点的缺货。在商界有关多级库存系统的分析已经有着悠久的历史。在许多领域，多级库存管理系统被广泛运用于向客户分销产品。鉴于这些系统的重要性，许多研究人员通过各种各样的条件和假设开始研究他们的运行特点。自从哈里斯提出经济订货批量模型以来，研究人员和实际工作者更加积极地关注在不同操作参数和模型假设条件下系统的分析和模型设计。在过去的十年里，对于多级库存管理模型的研究已经获得

54、了重要成就，主要是因为通过利用现代信息技术，使各个过程和分销阶段的供应链的整体控制逐渐变成可能。克拉克和斯卡夫最早研究两阶段存货模型。他们证实了库存系统的基础存货政策的最优性，并提出了一种用于计算最佳订货批量的政策。贝斯勒和凡诺特进一步发展了两阶段模型，使其包含一般块茎结构。上面提到的车间仓库问题通过埃本和施拉格分析一个缺货的中央仓库模型解决了。他们在相等的订货点分配假设条件下，对订购批量做出了更近似的表述。一些作者也已经考虑到了在各种形式下的这个问题。由于多阶段问题的复杂和棘手，哈德利和怀廷建议对库存系统采用单层次、单阶级模型。夏布鲁克把一个订购政策看做是一个仓储和零售商的两级模型，他假设零

55、售商的缺货是完全积压的，而且，夏布鲁克还建立了矩阵（可收回项目控制的多级技术）模型，它明确了在有预算约束的一个低级阶段中使库存水平最小化，这个模型是管理服务部分库存的第一个多级模型，此后，很多研究者提出了一大套模型，他们一般都是在多级框架下寻求最佳批量和安全库存。除了分析性模型，仿真模型也被开发了出来用于研究多级库存问题中复杂的相互作用问题。到目前为止，相关的一些文献主要关注于对需求的预测，以及对多阶段供应链库存政策的发展。需求随机的多阶段系统的存货控制政策已经具有了一个广泛的研究领域。近年来有许多论文都包含了斯尔福和派克的观点。用于定期评估标准的统一采购的优点是可以通过规定不同阶段的订购水平获得连续不断的评估标准，这是就所有库存而言，而不是单指设备。劳以及其他人，迪克斯和戴科克，唐格和里，密特拉和查特基，哈里加，陈，阿克斯特和章，诺齐克和特纳基斯特以及赛欧和郑都在他们的研究中利用了数学模型技术去管理供应链中的多级存货。迪克斯和戴科克的研究考虑到了不同的多级存货系统，比如配送系统或者生产系统，并且假设订单在一个固定的时间内到达。哈里加提出了由若干个装配或者整理和储存设备串联在一起组成的单个周期生产系统的随机模型。阿克斯特，诺齐克和特纳基斯特在他们