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基于啟發(fā)式需求預(yù)測(cè)方法的產(chǎn)品組合的魯棒優(yōu)化研究

發(fā)布時(shí)間:2018-05-26 23:24

  本文選題:產(chǎn)品組合優(yōu)化 + 需求預(yù)測(cè) ; 參考:《南京大學(xué)》2017年碩士論文


【摘要】:本文研究了一個(gè)產(chǎn)品需求具有不確性的單個(gè)時(shí)期的產(chǎn)品組合優(yōu)化問題。并且,本文假設(shè)產(chǎn)品的需求分布是未知的且屬于一些可以用計(jì)算工具處理的不確定集合中;這些不確定集合將由文中提出的基于多項(xiàng)邏輯特模型(Multinomial Logit Model)的需求預(yù)測(cè)方法給出。商品流通領(lǐng)域的研究者認(rèn)為單個(gè)零售商的產(chǎn)品組合并不是孤立地發(fā)揮集客和滿足消費(fèi)者購(gòu)買的作用,事實(shí)上,能夠最大程度發(fā)揮上述作用的是由多個(gè)產(chǎn)品組合相互關(guān)聯(lián)的零售商通過(guò)相鄰選址形成的商業(yè)集聚。有鑒于此,本文研究的零售商是處于一個(gè)商業(yè)集聚之中的,這意味著其產(chǎn)品組合和產(chǎn)品的需求受到商業(yè)集聚中其他零售商的產(chǎn)品組合的影響。基于這個(gè)假設(shè),本文設(shè)計(jì)一種啟發(fā)式方法用以預(yù)測(cè)該零售商所經(jīng)營(yíng)的產(chǎn)品的需求進(jìn)而為備貨策略和庫(kù)存控制提供科學(xué)依據(jù)。在已知各產(chǎn)品需求所屬的不確定集合的基礎(chǔ)上,本文分別考慮零售商產(chǎn)品組合固定和可變兩種情況下的產(chǎn)品組合優(yōu)化問題。當(dāng)產(chǎn)品組合固定時(shí),產(chǎn)品組合的優(yōu)化目標(biāo)是通過(guò)將產(chǎn)品庫(kù)存控制在最優(yōu)水平以實(shí)現(xiàn)零售商收益最大化的目標(biāo)。具體的做法為,通過(guò)運(yùn)用魯棒優(yōu)化方法求解包含不確定性需求變量的庫(kù)存控制模型,進(jìn)而得出各類產(chǎn)品在給定庫(kù)存周期內(nèi)的最優(yōu)訂購(gòu)批量。當(dāng)產(chǎn)品組合可變時(shí),本文首先設(shè)計(jì)一種迭代算法從零售商所有能夠經(jīng)營(yíng)的產(chǎn)品種類集合中挑選出在零售商庫(kù)存約束范圍內(nèi)單位期望收益最大的產(chǎn)品集合作為其最優(yōu)產(chǎn)品組合。接著,運(yùn)用與產(chǎn)品組合固定時(shí)相同的優(yōu)化方法,我們可以得到最優(yōu)產(chǎn)品集合中各產(chǎn)品的最優(yōu)訂購(gòu)批量(庫(kù)存水平)。
[Abstract]:In this paper, a product portfolio optimization problem with uncertainty of product requirements in a single period is studied. Furthermore, this paper assumes that the demand distribution of the product is unknown and belongs to some uncertain sets that can be processed by computing tools; these uncertain sets will be given by the method of demand prediction based on the multi-logical special Logit model proposed in this paper. Researchers in the field of commodity circulation believe that the product mix of individual retailers does not play an isolated role in gathering customers and satisfying consumer purchases. In fact, It is the business agglomeration formed by the adjacent location of the retailers with multiple product combinations that can play the above role to the maximum extent. In view of this, the retailers studied in this paper are in a business agglomeration, which means that their product mix and product demand are influenced by the product mix of other retailers in the business agglomeration. Based on this assumption, this paper designs a heuristic method to predict the demand of the retailer's products and provide scientific basis for stock preparation strategy and inventory control. On the basis of the uncertain set of known product requirements, this paper considers the product portfolio optimization problem in the case of fixed or variable product portfolio of retailers, respectively. When the product portfolio is fixed, the objective of optimizing the product portfolio is to maximize the retailer's profit by controlling the product inventory at the optimal level. The specific approach is to solve the inventory control model with uncertain demand variables by using robust optimization method, and then obtain the optimal order batch of all kinds of products within a given inventory cycle. When the product portfolio is variable, this paper first designs an iterative algorithm to select the set of products with the largest expected return per unit within the retailer's inventory constraints as its optimal product combination from the set of all the products that can be operated by the retailer. Then, using the same optimization method as when the product combination is fixed, we can obtain the optimal order batch (inventory level) of each product in the optimal product set.
【學(xué)位授予單位】:南京大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:F274
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本文編號(hào):1939389

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