本文選題：VMI模式 + 分布式庫存��； 參考：《北京交通大學(xué)》2017年碩士論文

【摘要】：近些年來,市場競爭隨著全球經(jīng)濟共同體的逐漸成熟而更激烈。對于變化多樣、難以預(yù)測的買方市場,企業(yè)之間往往存在激烈的競爭。同時,買方對產(chǎn)品的需求呈現(xiàn)出差異性、非靜態(tài)性和不確定性,產(chǎn)品的生命周期也在縮短。對于服裝行業(yè),這一形勢顯得尤為明顯。當(dāng)今服裝行業(yè)的特點是:產(chǎn)品生命周期短,品種多,數(shù)量小,顧客對服裝產(chǎn)品的到貨日期、價格、質(zhì)量和個性化要求也越來越高。企業(yè)為了快速響應(yīng)顧客需求,往往會有大量庫存。同時服裝企業(yè)擁有很多分銷網(wǎng)點,并且分布在不同位置,因此如何使庫存合理配置,降低庫存成本是現(xiàn)代服裝企業(yè)迫切需要解決的問題。本文研究的是供應(yīng)商管理庫存(Vendor Managed Inventory,縮寫為VMI)下的分布式庫存策略,探討在該模式下同城服裝門店的庫存補貨策略和調(diào)撥策略,使單位時間內(nèi)系統(tǒng)的總成本最小。主要進(jìn)行如下研究:(1)明確研究場景。分布式庫存管理實施的關(guān)鍵在于決策持有庫存量和當(dāng)需求來臨時庫存缺乏該如何處理。為了解決庫存控制問題,本文研究的是由供應(yīng)商和分銷商組成的二級供應(yīng)鏈系統(tǒng)在VMI模式下的分布式庫存策略,即供應(yīng)商對多個分銷商庫存進(jìn)行管理。采用集中控制和分散管理的模式,通過虛擬協(xié)調(diào)中心,對分散在各庫存點的庫存信息進(jìn)行集中控制。(2)進(jìn)行VMI模式下的分布式庫存需求預(yù)測方法的研究,服裝行業(yè)的庫存需求具有明顯的周期性變化特點,按年周期上升,并且考慮到這個變化特點所具有的不確定性,根據(jù)其歷史庫存需求數(shù)據(jù),采用隨機時間序列預(yù)測和灰色預(yù)測組合的預(yù)測算法進(jìn)行建模,將預(yù)測得到的數(shù)據(jù)與實際數(shù)據(jù)進(jìn)行對比改進(jìn),從而使擬合模型的精確度得到提高。進(jìn)行庫存需求預(yù)測,庫存策略的制定。(3)研究基于二級供應(yīng)鏈系統(tǒng)在VMI模式下的分布式庫存策略,對補貨和調(diào)撥策略進(jìn)行探討。以現(xiàn)實中的具體情況為依據(jù),分別根據(jù)補貨和調(diào)撥策略建立模型,采用自適應(yīng)遺傳算法對模型求解,求解出能使庫存成本最低的安全庫存、補貨量以及送貨點。(4)結(jié)合北京某企業(yè)的具體業(yè)務(wù),對歷史需求數(shù)據(jù)進(jìn)行分析和擬合,然后預(yù)測未來一段時間的產(chǎn)品需求量,進(jìn)行補貨和調(diào)撥分析,對比這兩種方式所產(chǎn)生的費用,來驗證采用VMI模式下的分布式庫存策略的優(yōu)勢。
[Abstract]:In recent years, the market competition with the global economic community gradually mature and more intense. For the diverse and unpredictable buyer market, there is often fierce competition between enterprises. At the same time, the buyer's demand for the product is different, non-static and uncertain, the product life cycle is also shortened. For the clothing industry, this situation is particularly obvious. Nowadays, the characteristics of garment industry are: short product life cycle, variety and small quantity. Customers have higher and higher demands on the date of arrival, price, quality and individuation of garment products. In order to quickly respond to customer demand, enterprises often have a large amount of inventory. At the same time, clothing enterprises have a lot of distribution outlets and are distributed in different places. Therefore, how to reasonably allocate inventory and reduce inventory cost is an urgent problem to be solved by modern garment enterprises. In this paper, the distributed inventory strategy under Vendor managed inventory (VMI) is studied. In this model, the inventory replenishment strategy and allocation strategy of clothing stores in the same city are discussed, so that the total cost of the system per unit time is minimized. The main research is as follows: (1) clear research scene. The key to implement distributed inventory management is to decide how to hold inventory and how to deal with the lack of inventory when demand comes. In order to solve the inventory control problem, this paper studies the distributed inventory strategy of a two-level supply chain system composed of suppliers and distributors under the VMI model, that is, the supplier manages the inventory of multiple distributors. By using centralized control and decentralized management mode and virtual coordination center, the inventory information scattered in each inventory point is centrally controlled. (2) the distributed inventory demand forecasting method based on VMI mode is studied. The inventory demand of the clothing industry is characterized by obvious cyclical changes, rising annually, and considering the uncertainty of this change, according to the historical inventory demand data, The prediction algorithm combined with stochastic time series prediction and grey prediction is used to model the model. The prediction data is compared with the actual data to improve the accuracy of the fitting model. Forecasting inventory demand and making inventory strategy. (3) based on the distributed inventory strategy of two-level supply chain system in VMI mode, the strategy of replenishment and allocation is discussed. According to the concrete situation in reality, the model is established according to replenishment and allocation strategy, and the model is solved by adaptive genetic algorithm, and the safe inventory with the lowest inventory cost can be solved. Combined with the specific business of a certain enterprise in Beijing, the historical demand data are analyzed and fitted, and then the product demand for a period of time in the future is predicted, and the replenishment and allocation analysis is carried out. Compare the cost of these two methods to verify the advantage of distributed inventory strategy in VMI mode.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F274;F426.86

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