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研究生:吳坤山
研究生(外文):Wu, Kun-Shan
論文名稱:可控制前置時間的欠撥與銷售損失混合存貨模型之研究
論文名稱(外文):A Study of Mixture Inventory Model with Backorders and Lost Sales for Controllable Lead Time
指導教授:歐陽良裕, 葉能哲
指導教授(外文):Ouyang Liang-Yuh, Yeh Neng-Che
學位類別:博士
校院名稱:淡江大學
系所名稱:管理科學研究所
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:1997
畢業學年度:85
語文別:中文
論文頁數:94
中文關鍵詞:存貨欠撥銷售損失前置時間
外文關鍵詞:inventorybackorderslost saleslead time
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在存貨管理中,前置時間是一個很重要的因素而且也是很多學者感興
趣的一個研究主題。前置時間的長短直接影響到訂購數量的多寡,對顧客
的服務水準以及企業經營者對外的競爭能力。在傳統的存貨理論中之存貨
控制大都將前置時間視為已知且為不可控制的常數或隨機變數,但是在許
多的實際情況,前置時間是可藉由趕工成本的增加來縮短;換句話說,前
置時間是可以控制的。因此已有許多的廠商已開始對固定的前置時間產生
質疑,因為他們所需要的是可以控制的前置時間。在另一方面,傳統的存
貨模型,很多是探討在缺貨期間缺貨數量允許欠撥或是缺貨不補的情況下
,最適(Q,r)存貨策略的擬訂。然而在實際問題中,既使有多家供應商
的競爭,但由於某些顧客對特定供應商的忠誠及信賴,該供應商縱有缺貨
的情形發生,顧客仍願意等待。因此,缺貨數量允許部份欠撥、部份不補
的情況是值得予以考慮的。 本論文是針對可控制的前置時間提出
五個存貨管理的數 學模型,模型中前置時間與訂購量均為決策變數,且
在缺貨期間考慮缺貨數量允許部份欠撥 、部份不補的情形,並以計量的
方法來決定最適訂購策略。文中首先假設前置時間內的需求量服從常態分
配,前置時間內的作業由n個成份組成,每一種成份各有不同的正常作業
時間,充分趕工下的作業時間及單位時間的趕工成本;此時的期望總相關
成本為:訂購成本,期望持有成本,期望缺貨成本及趕工成本,同樣的我
們希望在期望總相關成本最小化的狀況下,求出最適的前置時間與最適的
經濟訂購量。其次討論需求量的機率分配為未知時的最適前置時間及經濟
訂購量。此乃先前的推廣,所考慮的前置時間內需求量之機率分配型式為
未知,但其平均數與標準差則為已知。我們利用分配自由之大中取小準則
來決定此模型的最適解。接著探討滿足某一服務水準下的最適存貨策略。
在實際問題中,因缺貨所發生的缺貨成本包括,契約規定的懲罰,顧客不
再上門的損失,商譽受損,潛在的未來需求減少等等。其中大部份的缺貨
成本值是很難正確的估計得到。基於此原因,我們試著將期望總相關成本
函數中之缺貨成本項,以服務水準限制式來取代,此處服務水準限制式是
指每一週期的缺貨率不超過某一已知的百分率。最後,我們探討在到達的
訂購批量中含有某些數量的瑕疵品之最適存貨策略。傳統的存貨模型大都
假設在訂購量中不含有任何的瑕疵品,事實上這是不太可能的。由於供應
商的生產過程不完備或在運送的過程中,物品遭受到損壞,因此在訂購量
到達訂購者手中時多少會含有一些瑕疵品。當訂購量中含有瑕疵品時將會
影響到現有的存貨水準,缺貨數量以及訂購次數。因此傳統的最適存貨策
略並不適合於含有瑕疵品的存貨模型。所以,文中乃針對先前所討論的混
合存貨模型,考慮到達的訂購量中含有隨機數量的瑕疵品,它具有二項式
機率分配。我們假設在訂購量到達後檢查所有的物品(檢查的過程是非破
壞性的),而且經檢查後發現的瑕疵品(不可修復)均保留至下一個週期
訂購量進貨時退還給供應商。基本上文中所有的存貨數學模型都將進行敏
感度分析並作經濟上之解說。
Lead time plays an important role and has been a topic of
interest for many authors in inventory management. The length of
lead time directly affects the size of order quantity, the
service level for customer, and the competitive ability in
business. Almost all inventory models assume that lead time is a
prescribed constant or a stochastic variable. But in many real
situations, lead time can be reduced at an added crashing cost;
in other words, it is controllable. Therefore, many firms felt
doubtful about the uncontrollability of lead time. In addition,
for the traditional inventory models, many researchers studied
the (Q,r) inventory model which considers the case that all
demand during the stockout period is either backordered or lost
sales. In practical market situations, some customers maintain
the loyalty and trust for specific supplier though it has many
competitors, and the customers are also willing to wait whenever
a shortage occurs. Hence, the total amount of stockout during
the stockout period is worth to be considered a mixture of
backorders and lost sales. This paper focuses on the
controllable lead time and presents six mathematical inventory
models, in which both lead time and order quantity are the
decision variables. In addition, during the stockout period, the
total amount of stockout considers a mixture of backorders and
lost sales to obtain the optimal solution. In this thesis, we
first assume that the demand of lead time follows normal
distribution and the lead time consists of n components which
have different normal durations, minimum durations and crashing
costs. The objective is to determine the optimal lead time and
the order quantity pair so as to minimize the expected total
cost which is composed of the ordering cost, the expected
carrying cost, the expected shortage cost and the crashing cost.
Second, we assume that the distribution of lead time demand is
free. This model is an extended model of the previous inventory
model. We consider the cumulative distribution function of the
lead time demand which has only known mean and variance, but
make no assumption on the distributional form, and try to apply
the minimax distribution free approach criterion to find out the
optimal solution. Next, we discuss the mixture inventory model
with a service level constraint. In many practical problems, the
stockout cost includes: the penalty of contract, the damage of
goodwill, loss of goodwill for customer, the reduced potential
of the future demand, and so on. Since it is difficult to
estimate an exact value of the stockout cost, we try to replace
the stockout cost in the objective function by the service level
constraint. The service level constraint here indicates that the
stockout level per cycle is bounded. Finally, we discuss an
arrival order which contains some defective units in mixture
inventory model. Traditionally, inventory models almost assume
that an arrival order has no defective units. In fact, this is
impossible. As a result of imperfect production of the supplier,
and/or damage in transit, an arrival order often contains some
defective units. If there are defective units in orders, there
will be impact on the on-hand inventory level, the number of
shortage and the frequency of orders in inventory system.
Therefore, ordering policies determined by conventional
inventory models may be inappropriate for the defective
inventory situation. Hence, in this situation, we change the
previous inventory models and assume that an arrival order may
contain some defective units. And the number of defective units
in an arrival order is a random variable with binomial
probability distribution. We also assume that the purchaser
inspects the entire items which are assumed to be non-
destructive, and the defective units in each lot which can not
be repaired will be returned to the vendor at the time of
delivery of the next lot. In all mathematical inventory models,
we discuss the effects of parameters and give economic
interpretation of the circumstances.
封面
圖目錄
表目錄
符號一覽表
第一章 緒論
1.1 問題背景
1.2 研究動機與目的
1.3 相關文獻探討
1.4 本文結構
第二章 需求量服從常態分配的最適前置時間及經濟訂購量
2.1 前言
2.2 符號與假設
2.3 模型的建立
2.4 敏感度分析
第三章 需求量的機率分配為未知時的最適前置時間及經濟訂購量
3.1 前言
3.2 模型的建立
3.3 範例
3.4 敏感度分析
第四章 服務水準限制下的最適存貨策略
4.1 前言
4.2 模型的建立
4.2.1 需求量呈常態分配的情形
4.2.2 需求量的機率分配為未知的情形
4.3 範例
4.4 敏感度分析
第五章 含有瑕疵品的欠撥和銷售損失之混合存貨模型
5.1 前言
5.2 符號與假設
5.3 模型的建立
5.4 敏感度分析
5.5 服務水準限制下的數學模型
第六章 結論
6.1 主要的研究成果
6.2 未來的研究方向
參考文獻
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