供應(yīng)鏈下的多級存貨管理外文翻譯（節(jié)選）

1、<p>　　中文4800字，3200單詞，1.9萬英文字符</p><p>　　出處： Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture, 2007, 221(10):1553-1570.</p><p><b>　　原文<

2、;/b></p><p>　　Multi-echelon inventory management in supply chains with uncertain demand</p><p>　　and lead times: literature review from an operational research perspective</p><p>

3、;　　A Taskin Gu¨mu¨s* and A Fuat Gu¨neri</p><p>　　Abstract: </p><p>　　Historically, the echelons of the supply chain, warehouse, distributors, retailers, etc., have been managed in

4、dependently, buffered by large inventories. Increasing competitive pressures and market globalization are forcing firms to develop supply chains that can quickly respond to customer needs. To remain competitive and decre

5、ase inventory, these firms must use multi-echelon inventory management interactively, while reducing operating costs and improving customer service. The current paper rev</p><p>　　Keywords: supply chain, mul

6、ti-echelon inventory management, demand uncertainty, lead-time uncertainty</p><p>　　1 INTRODUCTION</p><p>　　Supply chain management (SCM) is an integrative approach for planning and control of m

7、aterials 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 competi

8、tive power. SCM is a set of approaches to integrate suppliers, manufacturers, warehouses, and stores efficiently, so that merchandise is produced and distributed at right quantities, to the righ</p><p>　　Inv

9、entory usually represents from 20 to 60 per cent of the total assets of manufacturing firms. Therefore inventory management policies prove critical in determining the profit of such firms [4]. Inventory management is, to

10、 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

11、 addresses SC issues under an integrated perspective.</p><p>　　Inventories exist throughout the SC in various forms for various reasons. The lack of a coordinated inventory management throughout the SC often

12、 causes the bullwhip effect, namely an amplification of demand variability moving towards the upstream stages. This causes excessive inventory investments, lost revenues, misguided capacity plans, ineffective transportat

13、ion, missed production schedules, and poor customer service.</p><p>　　Many scholars have studied these problems, as well as emphasized the need of integration among SC stages, to make the chain effectively a

14、nd efficiently 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.

15、g. lead times) and demand, information delays associated with the manufacturing and distribution processes characterize SCs.</p><p>　　Inventory management in multi-echelon SCs is an important issue, because

16、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. uncertain demands, lea

17、d times, production times, product prices, costs, etc., especially the uncertainty in demand and lead times where the inventory cannot be managed between echelons optimally.</p><p>　　In the current paper, a

18、detailed literature review is presented, addressing multi-echelon inventory management in SCs from 1996 to 2005. Here, the behavior of the papers against demand and lead time uncertainty is emphasized. First, echelon con

19、cept and multi-echelon inventory management in SCs are defined. Then, the literature review conducted from an operational research point of view between 1996 and 2005, is presented. Finally, directions for future researc

20、h are suggested.</p><p>　　2 MULTI-ECHELON INVENTORY MANAGEMENT IN SUPPLY CHAINS</p><p>　　Most manufacturing enterprises are organized into networks of manufacturing and distribution sites that p

21、rocure raw material, process them into finished goods, and distribute the finish goods to customers. The terms ‘multi-echelon’ or ‘multilevel ‘production/ distribution networks are also synonymous with such networks (or

22、SC), when an item moves through more than one step before reaching the final customer. Inventories exist throughout the SC in various forms for various reasons. At any manufac</p><p>　　Manufacturers procure

23、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 the final cu

24、stomer, it forms a ‘multi-echelon’ inventory system. The echelon stock 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 i

25、ts downstream stock points.</p><p>　　The analysis of multi-echelon inventory systems that pervades the business world has a long history. Multi-echelon inventory systems are widely employed to distribute pro

26、ducts 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 developm

27、ent of the economic order quantity (EOQ) formula by Harris (1913), researchers and practitioners have been act</p><p>　　Clark and Scarf were the first to study the two echelon inventory model. They proved th

28、e optimality of a base-stock policy for the pure-serial inventory system and developed an efficient decomposing method to compute the optimal base-stock ordering policy. Bessler and Veinott extended the Clark and Scarf m

29、odel to include general arborescent structures. The depot warehouse problem described above was addressed by Eppen and Schrage who analysed a model with a stockless central depot . They derived</p><p>　　Sher

30、brooke considered an ordering policy of a two-echelon model for warehouse and retailer. It is assumed that stockouts at the retailers are completely backlogged. Also, Sherbrooke constructed the METRIC (multi-echelon tech

31、nique for recoverable item control) model, which identifies the stock levels that minimize the expected number of backorders at the lower-echelon subject to a budget constraint. This model is the first multi-echelon inve

32、ntory model for managing the inventory of service parts</p><p>　　. Thereafter, a large set of models, which generally seek to identify optimal lot sizes and safety stocks in a multi-echelon framework, were p

33、roduced by many researchers). In addition to analytical models, simulation models have also been developed to capture the complex interactions of the multi-echelon inventory problems.</p><p>　　Figure 1 shows

34、 a multi-echelon system consisting of a number of suppliers, plants, warehouses, distribution centres, and customers.</p><p>　　So far literature has devoted major attention to the forecasting of lumpy demand

35、, and to the development of stock policies for multi-echelon SCs. Inventory control policy for multi-echelon systems with stochastic demand has been a widely researched area. More recent papers have been covered by Silve

36、r 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</p><p>

37、;　　3 LITERATURE REVIEW: FROM 1996 TO 2005</p><p>　　In this section, a detailed literature review, conducted from an operational research point of view, is presented. It addresses multi-echelon inventory mana

38、gement in SCs, from 1996 to 2005. The selection criteria of the papers that are reviewed are: using operational research techniques to overcome multiechelon inventory management problems, and being demand and lead time s

39、ensitive (there are uncertain demand and lead times). Here, the behavior of the papers against demand and lead time uncertai</p><p>　　The papers reviewed here are categorized into groups on the basis of the

40、research techniques in which they are used. These techniques can be grouped as:</p><p>　　(a) mathematic modeling (only);</p><p>　　(b) mathematic modeling and other techniques (in the same paper)

41、; (c) METRIC modeling;</p><p>　　(d) Markov decision process;</p><p>　　(e) simulation (only);</p><p>　　(f) Stackelberg game;</p><p>　　(g) literature review;</p>&

42、lt;p>　　(h) other techniques (vari-METRIC method, heuristics, scenario analysis, fuzzy logic, etc.).</p><p>　　While the research techniques are common for papers that are grouped according to their researc

43、h techniques, the number of echelons they consider, inventory/system policies, demand and lead time assumptions, the objectives, and the solutions’ exactness may be different. Therefore these factors are also analysed.&l

44、t;/p><p>　　Mathematic modeling technique</p><p>　　Rau et al., Diks and de Kok, Dong and Lee, Mitra and Chatterjee , Hariga, Chen, Axsater and Zhang, Nozick and Turnquist, and So and Zheng use a mat

45、hematic modelling technique in their studies to manage multi-echelon inventory in SCs. Diks and de Kok’s study considers a divergent multi-echelon inventory system, such as a distribution system or a production system, a

46、nd assumes that the order arrives after a fixed lead time. Hariga, presents a stochastic model for a single-period production system </p><p>　　Chen, Axsater and Zhang, and Nozick and Turnquist consider a two

47、-stage inventory system in their papers. Axsater and Zhang and Nozick and Turnquist assume that the retailers face stationary and independent Poisson demand. Mitra and Chatterjee examine De Bodt and Graves’model(1985),wh

48、ich they developed in their paper ‘Continuous-review policies for a multi-echelon inventory problem with stochastic demand’, for fast moving items from the implementation point of view. The proposed modification of t<

49、/p><p>　　Furthermore, they assume that the supplier’s delivery lead times are variable and are affected by the retailer’s order quantities. Dong and Lee’s paper revisits the serial multi-echelon inventory syste

50、m 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 cost for the basic model of Clark

51、 and Scarf. Second, they show that the structure of the optimal stocking policy</p><p>　　After reviewing the literature about multiechelon inventory management in SCs using mathematic modeling technique, it

52、can be said that, in summary, 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 ex

53、act or approximate solutions.</p><p>　　Mathematic modeling and other techniques together</p><p>　　Dekker et al. analyses the effect of the break quantity rule on the inventory costs. The break q

54、uantity 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-warehouse N-retailers dist

55、ribution systems, it is assumed that all customer demand takes place at the retailers. However, it was shown by Dekker et al. that delivering large orders from the warehouse can lead t</p><p>　　Andersson and

56、 Markland’s approach is based on an approximate cost-evaluation technique. Axsater presents a method for exact evaluation of control policies that provides the complete probability distributions of the retailer inventory

57、 levels. Mitra and Chatterjee examine the effect of utilizing demand information in a multi-echelon system. Seferlis and Giannelos present an optimization-based control approach that applies multivariable model-predictiv

58、e control principles to the entire network. The</p><p>　　Cachon and Fisher and Tsiakis et al. use mathematical modelling and scenario analysis in their studies. Cachon and Fisher consider a twoechelon invent

59、ory system with stochastic demand, while Tsiakis et al. consider a four-echelon inventory system with time-invariant demand, differently from most studies. Cachon and Fisher [58] study the value of sharing demand and inv

60、entory data in a two-echelon inventory system, while Tsiakis et al.’s objective is the minimization of the total annualized cost o</p><p>　　Parker and Kapuscinski use mathematical modeling and Markov decisio

61、n processes in their paper, and consider a two-echelon inventor system with stochastic demand. Extending the Clark and Scarf model to include installations with production capacity limits, they demonstrate that a modifie

62、d echelon base-stock policy is optimal in a twostage system when there is a smaller capacity at the downstream facility.</p><p>　　A multi-product, multi-stage, and multi-period production and distribution pl

63、anning model is proposed in Chen and Lee to tackle the compromised sales prices and the total profit problem of a multi-echelon SC network with uncertain sales prices. They use mathematical modeling (mixed integer non-li

64、near programming) and fuzzy optimization in their study.</p><p>　　Jalbar et al. use mathematical modeling, Schwarz heuristic, Graves and Schwarz procedure, Muckstadt and Roundy approach, and O(N log N) heuri

65、stic in their paper, and consider a two-echelon inventory system with one-warehouse and N-retailers.</p><p>　　The goal is to determine single-cycle policies that minimize the average cost per unit time, that

66、 is, the sum of the average holding and set-up costs per unit time at the retailers and at the warehouse.</p><p>　　In Routroy and Kodali’s paper mathematical modeling and differential evolution algorithms ar

67、e used. A three-echelon inventory system is considered consisting of a retailer, a warehouse, and a manufacturer.</p><p>　　Han and Damrongwongsiri’s purpose is establishing a strategic resource allocation mo

68、del to capture and encapsulate the complexity of the modern global SC management problem. A mathematical model is constructed to describe the stochastic multi-period two-echelon inventory with the many to-many demand–sup

69、plier network problem. Genetic algorithm (GA) is applied to derive near optimal solutions through a two-stage optimization process. Demand in each period can be represented by the probability dist</p><p>　　M

70、ost of the papers reviewed here use simulation with mathematical modeling. They consider intensively two-echelon inventory system with stochastic demand, 1, 3, or N-echelon systems are rarely considered. They gain exact

71、or approximate solutions.</p><p>　　METRIC modeling technique</p><p>　　Moinzadeh and Aggarwal use METRIC modelling and simulation techniques in their study, while Andersson and Melchiors and Wang

72、 et al. use METRIC modelling only. The three of them consider a two-echelon inventory system with stochastic demand, and obtain approximate solutions.</p><p>　　Moinzadeh and Aggarwal study a (S-1,S)-type mul

73、ti-echelon inventory system where all the stocking locations have the option to replenish their inventory through either a normal or a more expensive emergency resupply channel. Wang et al. study the impact of such centr

74、e-dependent depotreplenishment lead times (DRLTs) on system performance. Andersson and Melchiors evaluate and optimize S-1,S-policies for a two-echelon inventory system consisting of one central warehouse and an arbitrar

75、y number of r</p><p>　　Markov decision process technique</p><p>　　Iida , Chen and Song , Chen et al. , and Minner et al. use the Markov decision process in their studies, while Chiang and Monaha

76、n use Markov decision process and scenario analysis, and Johansen uses Markov decision process, simulation, and Erlang’s loss formula together. Iida and Chen and Song consider an N-echelon inventory system, but under st

77、ochastic demand in the first study and Markov-modulated demand in the second one, respectively. Chen et al. , Minner et al. , and Chiang and Monahan con</p><p>　　The main purpose of Iida’s paper is to show

78、that near-myopic policies are acceptable for a multiechelon inventory problem. It is assumed that lead times at each echelon are constant. Chen and Song’s objective is to minimize the long-run average costs in the system

79、. In the system by Chen et al. , each location employs a periodic-review (R,nQ), or lot-size reorder point inventory policy. They show that each location’s inventory positions are stationary and the stationary distributi

80、on is uniform a</p><p>　　In multi-echelon inventory management there are some other research techniques used in literature, such as heuristics, vari-METRIC method, fuzzy</p><p>　　sets, model pre

81、dictive control, scenario analysis, statistical analysis, and GAs. These methods are used rarely and only by a few authors.</p><p>　　The paper by Chandra and Grabis quantifies the bullwhip effect in the case

82、 of serially correlated external demand, if autoregressive models are applied to obtain multiple steps demand forecasts. Here, under autoregressive demand, inventory management of a two-echelon SC consisting of a retaile

83、r and a distributor is considered. It is assumed that the lead time is deterministic. The papers using the other techniques consider (one-, two-, three-, four-, five-, or N-echelon systems) assume stochasti</p>&l

84、t;p>　　4 FINDINGS OF THE LITERATURE REVIEW</p><p>　　Limited echelons of a multi-echelon inventory system is usually considered in the literature. They rarely generalize their models to N-echelon. Similarly

85、, they usually consider serial systems, instead of a tree conformation.</p><p>　　The authors generally assume demand and lead times to be stochastic, deterministic, constant, or negligible. There are only a

86、few studies that find these variables with heuristics, fuzzy logic, and GAs. These techniques are not examined adequately yet in inventory management in multi-echelon SC.</p><p>　　In addition, the papers pre

87、sent mostly approximate models. There are a small amount of papers that give exact solutions.</p><p><b>　　譯文</b></p><p>　　不確定的需求和交貨期供應(yīng)鏈下的多級存貨管理：</p><p>　　運(yùn)籌學(xué)的角度的一個文獻(xiàn)回顧&l

88、t;/p><p>　　摘要：從歷史上看,供應(yīng)鏈下的倉儲、分銷商、零售商等各層級一直都是獨(dú)立管理，通過維持很多庫存來保證價交易的正常進(jìn)行。日益增長的競爭壓力和市場全球化，迫使企業(yè)開發(fā)供應(yīng)鏈，以快速的響應(yīng)客戶需求。為了保持競爭力,降低庫存,這些公司必須使用多級庫存管理交互系統(tǒng),同時減少運(yùn)營成本來改善客戶服務(wù)。當(dāng)前的文獻(xiàn)資料，著力于研究從1996年到2005年的供應(yīng)鏈庫存管理。本文對需求和交貨時間的不確定性研究，主要是從運(yùn)

89、籌學(xué)的角度來進(jìn)行的。最后,對未來的研究方向做了一個建議。</p><p>　　關(guān)鍵詞:供應(yīng)鏈；多級庫存管理；需求的不確定性；交貨時間的不確定性</p><p><b>　　1.引言</b></p><p>　　供應(yīng)鏈管理(SCM)是一個綜合的材料控制、供應(yīng)商和客戶之間信息流動的計劃和方法。這個領(lǐng)域方面的研究，近年來吸引了學(xué)者們的廣泛關(guān)注。它被看

90、作是一個提高企業(yè)競爭力的工具。供應(yīng)鏈管理是一組方法，用來整合供應(yīng)商、制造商、倉儲和零售商，進(jìn)行有效地生產(chǎn)，并在正確的數(shù)量，在正確的地點(diǎn)和時間，以最小的成本滿足客戶的服務(wù)要求。因此,供應(yīng)鏈由不同的成員或階段所組成的。供應(yīng)鏈?zhǔn)且粋€動態(tài)的、隨機(jī)的復(fù)雜的系統(tǒng)，可能涉及數(shù)百個參與者。</p><p>　　庫存成本通常占制造業(yè)公司的總資產(chǎn)的20%—60%。因此，庫存管理策略對這些公司的利潤來說很重要。庫存，在更大程度上說,關(guān)

91、系到整個供應(yīng)鏈(SC),即供應(yīng)鏈?zhǔn)且粋€加工、轉(zhuǎn)換和傳遞到公司的一個系統(tǒng)。庫存管理也確實(shí)是供應(yīng)鏈管理方面的一個關(guān)鍵問題,需要在集成的視角下解決了供應(yīng)鏈問題。</p><p>　　庫存管理由于種種原因，以各種形式貫穿于供應(yīng)鏈過程的始終。在供應(yīng)鏈系統(tǒng)中，如果缺乏一個協(xié)調(diào)的庫存管理，那么經(jīng)常會導(dǎo)致牛鞭效應(yīng),即一個放大的需求的變化，不斷地向上游階段放大需求。這將導(dǎo)致過多的庫存成本，造成利潤損失,也會造成錯誤的生產(chǎn)計劃和低水

92、平的客戶服務(wù)。許多學(xué)者研究過這些問題，強(qiáng)調(diào)要整合供應(yīng)鏈的各個階段,有效地滿足客戶請求。關(guān)于集成問題,必須處理好交貨期的不確定性。除了供應(yīng)的不確定性(如交貨期和需求信息延遲)。</p><p>　　供應(yīng)鏈下的多級庫存管理是一個重要的問題，因?yàn)樵诠?yīng)鏈中，有許多元素互相協(xié)調(diào)。他們必須協(xié)調(diào)好他們的庫存。有很多復(fù)雜的因素會影響供應(yīng)鏈的協(xié)調(diào)，比如不確定的需求、交貨期、生產(chǎn)時間、產(chǎn)品價格、成本等,特別是需求和交貨期的不確定性

93、。在當(dāng)前的文獻(xiàn)中,對于解決多級庫存問題，從1996年到2005年的文獻(xiàn)已經(jīng)做了一個詳細(xì)的文獻(xiàn)綜述。在這里, 本文對需求和交貨時間的不確定性研究，主要是從運(yùn)籌學(xué)的角度來進(jìn)行的，最后,對未來的研究方向做了一個建議。 </p><p>　　2供應(yīng)鏈管理下的多級庫存</p><p>　　大多數(shù)生產(chǎn)企業(yè)是整個制造和分銷網(wǎng)絡(luò)站點(diǎn)的一個組成部分，采購原材料、加工生產(chǎn)出商品,最后交付給客戶。多級庫存這一術(shù)

94、語也是這樣的代名詞。庫存管理由于種種原因，以各種形式貫穿于供應(yīng)鏈過程的始終。在任何生產(chǎn)點(diǎn)，他們可能需要采購原材料、加工生產(chǎn)出商品,最后交付到客戶手中。他們需要做好倉儲管理，并做好和供應(yīng)鏈上其他階段庫存的協(xié)調(diào)。</p><p>　　制造商采購原材料，加工成商品,銷售給經(jīng)銷商，最后流動到零售或客戶手中，形成了一個多級庫存系統(tǒng)。商業(yè)世界，多級庫存系統(tǒng)的分析有著悠久的歷史。多級庫存系統(tǒng)是廣泛存在的，用來在廣泛的地理區(qū)域內(nèi)

95、向客戶銷售產(chǎn)品。</p><p>　　路易斯塔里夫考慮一種訂購的措施，用于兩級倉庫和零售商模型。它建立在零售商沒有庫存積壓的假設(shè)前提下。此外,這個模型是第一個多級庫存模型來管理庫存。此后,大量的模型試圖確定最優(yōu)庫存。除了分析模型,仿真模型也被開發(fā)來捕獲關(guān)于多級庫存的問題的復(fù)雜的交互信息。</p><p>　　目前的文獻(xiàn)主要關(guān)注預(yù)測的需求和發(fā)展方面。多級系統(tǒng)的庫存控制策略正被很多學(xué)者所研究，

96、比如希爾福和派克。集中計劃的優(yōu)勢,可以定期檢查庫存情況,并持續(xù)的通過多級庫存來協(xié)調(diào)庫存。</p><p>　　3 文獻(xiàn)回顧：從1996到2005</p><p>　　在本節(jié)中,將會進(jìn)行一個詳細(xì)的文獻(xiàn)綜述,主要是從運(yùn)籌學(xué)的角度來進(jìn)行的。它是從1996年到2005年專家學(xué)者們對多級庫存的研究。本文特選取這些文獻(xiàn)進(jìn)行一個綜述:使用運(yùn)籌學(xué)技術(shù)來克服多級庫存管理問題 (有不確定需求和交貨期的供應(yīng)鏈系

97、統(tǒng))。在這里,主要強(qiáng)調(diào)的是需求和交貨期的不確定性。</p><p>　　文獻(xiàn)綜述主要分為以下幾組，如下所述：</p><p><b>　　（a）數(shù)學(xué)建模;</b></p><p>　?。╞）數(shù)學(xué)建模和其他技術(shù);</p><p><b>　?。╟）指標(biāo)模型;</b></p><p&

98、gt;　　（d）馬爾可夫決策過程;</p><p><b>　?。╡）模擬仿真;</b></p><p><b>　　（f）博弈;</b></p><p><b>　?。╣）文獻(xiàn)綜述;</b></p><p>　　（h）其他技術(shù).(場景分析、模糊邏輯等)。</p>