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研究生:辛佩珊
研究生(外文):Pei-ShanHsin
論文名稱:利用CCM演算法求解多目標存貨管理之非線性模式
論文名稱(外文):Using CCM Algorithm to Solve Nonlinear Program in Multiple Criteria Inventory Management
指導教授:林珮珺林珮珺引用關係
指導教授(外文):Pei-Chun Lin
學位類別:碩士
校院名稱:國立成功大學
系所名稱:交通管理學系碩博士班
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:59
中文關鍵詞:存貨管理非線性權重相乘模型正向座標法
外文關鍵詞:Inventory managementNonlinearWeighted Product ModelCanonical Coordinate System
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隨著國際貿易的興盛以及不斷增多且複雜的商品品項,為了追求良好的服務水準,存貨管理已成為備受關注的課題。ABC法則被視為存貨管理之圭臬,此法則主張物品應依其對公司之貢獻程度進行排序並分為A、B、C三種等級,再針對各等級貨品設計不同管理方針。傳統上,年度金錢使用量(Annual dollar usage, ADU)被視作衡量物品對公司貢獻程度之唯一指標。但因存貨管理許考量之因素繁多,近年來有許多學者提出單一指標並不足以評估眾多且複雜的品項,也因此需要一套合理的多準則評估機制幫助存貨正確地被分類。

目前已有許多處理準則存貨管理的研究方法,其中較被廣泛應用的為層級分析法(Analytic Hierarchy Process, AHP),也有一些學者使用啟發式演算法,譬如類神經分析法來解決此類問題。然而,目前求解的方法多少存在些不足之處,包含較不客觀之評估準則以及程序過於複雜…等。本論文希望能透過非線性模型配合有效之演算法,提供較簡易且合理之管理模型。存貨管理問題的本質即為非線性,利用非線性模型求解較能反映問題本質,因此在本研究中使用權重相乘之模型(Weighted Product Model, WPM)進行求解;再配合一有效解決非線性問題之正向座標演算法(CCM),可解決一般利用非線性模型求解時遭遇之困難。WPM與CCM的組合能夠提供較為合理的存貨排序,在本研究中也將列出各種求解方法之結果比較。

As the varieties of goods have increased to meet the demands of an uncertain market, inventory management has been gradually gaining in importance in recent years. ABC principle is the traditional way dealing with inventory management which classify all the items (SKUs) into three categories based on their valuation. In the past the sole criterion, Annual Dollar Usage (ADU) has been viewed as the only way to value SKUs; however, lots of scholars revealed that only one criterion would be insufficient, multiple criteria should be taken into account when tackling inventory classification.

There were plenty of solutions to the issue of multiple inventory management problem; but they somewhat have some drawbacks as including too much subjectivity or being complicated. This study aims to provide a nonlinear solution accompany with an efficient algorithm called CCM for solving the problem. A nonlinear formula weighted product model (WPM) is adopted in this thesis; furthermore, a powerful and efficient algorithm CCM helps ease difficulty of using nonlinear model. The combination of WPM and CCM offers good result of inventory management which better represents importance of each SKUs. The final part of this thesis will compare results of different methods dealing with the same exemplification of multiple criteria inventory management.

Table of Contents I
List of Tables III
List of Figures III
1 Introduction 1
1.1 Inventory management 1
1.2 ABC inventory analysis 2
1.3 Multiple Criteria Inventory Classification (MCIC)4
2 Literature review 5
2.1 Multiple Criteria Decision Analysis (MCDA) 6
2.2 Methods solving MCIC 7
2.2.1 Joint-Criteria Matrix 10
2.2.2 Analytic Hierarchy Process (AHP) 12
2.2.3 Heuristic approaches 14
2.2.3.1 Artificial neural networks (ANNs) 14
2.2.3.2 Genetic Algorithm (GA) 16
2.2.4 Weighted linear optimization 18
2.2.4.1 R-model 19
2.2.4.2 ZF-model 21
2.2.4.3 Peer-estimation (Chen’s model) 24
2.2.4.4 Ng-model 27
2.2.5 Weighted nonlinear optimization 30
3 Model development 34
3.1 Problem formulation 34
3.2 CCM Algorithm 36
3.2.1 Property of the algorithm 37
3.2.2 Solving scheme 37
4 Illustrative example 40
4.1 Solving procedure of CCM 41
4.2 Comparing with CCM algorithm and LINGO 42
4.2.1 Elapsed runtime and iteration 45
4.2.2 Quality of solutions 46
4.3 Comparison with other studies 49
5 Conclusion and future studies 54
Reference list 57

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