跳到主要內容

簡易檢索 / 詳目顯示

回結果列表
研究生： 廖錦農
Chin-Nung Liao
論文名稱： 應用一個整合方法於供應商評估與選擇
An integrated approach to the evaluation and selection of suppliers
指導教授： 高信培
Hsing-Pei Kao
口試委員:
學位類別： 博士
Doctor
系所名稱： 管理學院 - 工業管理研究所
Graduate Institute of Industrial Management
畢業學年度： 99
語文別： 英文
論文頁數： 68
中文關鍵詞： 田口損失函數 、供應鏈管理 、供應商選擇 、多選擇目標規劃 、理想解類似度偏好順序評估法 、層級分析法
外文關鍵詞： Taguchi loss function, Supplier selection, analytical hierarchy process (AHP), Supply chain management (SCM), Techniques for order preference by similarity to, Multi-choice goal programming (MCGP)
相關次數： 點閱：19  下載：0 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • 供應商選擇一直是供應鏈管理上一個重要的議題。近年來評估與選擇最適合供應商在行銷研究論文成為策略考量。然而，供應商的評選是一種多目標與多準則的問題，其涉及到各種定性 與定量因素。又已往這些研究所提出對選擇最好供應商的評估僅關注於定性決策準則而忽略定量準則因素。本研究考慮定性與定量因素，提出兩種方法進行供應商選擇問題; 1.採用田口損失函數，分析階層程序法與多選目標規劃法來決定供應商; 2. 應用模擬理想解類似度偏好順序評估與多選目標規劃法進行最佳供應商的評估與選擇分案。本研究應用決策者選擇最佳供應商之不同期望水準，提出鐘錶業與食品業兩個實務案例，說明上述兩種決策分析模式之應用。

    Supplier selection is an important issue in supply chain management. In recent years, determining the best supplier in the supply chain has become a key strategic consideration in marketing researches. However, these decisions usually involve multi-goal and multi-criteria or qualitative and quantitative factors. The previous research force in qualitative criterions and ignore the quantitative factors for supplier selection. This study considering both tangible and intangible criteria proposes two integrated methods. First, this study use Taguchi loss function, analytical hierarchy process (AHP) and multi-choice goal programming (MCGP) model for solving the supplier selection problem. Second, it addressed fuzzy techniques for order preference by similarity to ideal solution (TOPSIS) and MCGP approach to evaluate the best supplier. The advantage of these methods is that it allows decision makers to set multiple aspiration levels for supplier selection. The integrated models are illustrated by two examples in watch and food firms.

    Chapter 1 Introduction………………………………………………… 1 1.1. Motivation………………………………………………………. 2 1.2. Objectives……………………………………………….………. 4 Chapter 2 Literature Review………………………………………….. 5 2.1. Supply chain management……………………………………… 5 2.2. Supplier evaluation criteria……………………………………... 6 2.3. Supplier selection method………………………………………. 10 Chapter 3 Models Construction……………………………………….. 15 3.1. Taguchi loss functions…………………………………………... 15 3.2. Analytical hierarchy process (AHP)……………………………. 17 3.3. Technique for order preference by similarity to ideal solution (TOPSIS)………………………………………………………. 20 3.4. Multi-choice goal programming (MCGP) ……………………... 28 3.5. Suppliers evaluation and selection using Taguchi loss function, AHP and MCGP for watch industry……………………........... 33 3.6. Suppliers evaluation and selection using TOPSIS and MCGP for food industry…………………………………………………… 34 Chapter 4 Industrial Application……………………………………... 38 4.1. The watch company case……………………………….. ……... 38 4.2. The food company case…………………………………………. 46 4.3. Analysis and discussion………………………………………… 55 Chapter 5 Conclusions and Future Works…………………………… 60 5.1. Conclusions…………………………………………….. ……… 60 5.2. Limitations and future works…………………………... ……… 61 References………………………………………………………………… 63

    Aguarón, J. & Moreno-Jiménez, J.M. (2003). The geometric consistency index. Approximated thresholds. European Journal of Operational Research 147(1), 137-145.
    Antony, J. & Kaye, M. (2000). Experiment quality. Kluwer Academic Publishers, Dordrecht, MA.
    Bevilacqua, M., D’Amore, A. & Polonara, F. (2004). A multi-criteria decision approach to choosing the optimal blanching–freezing system. Journal of Food Engineering 63, 253–263.
    Cakravastia, A. & Takahashi, K. (2004). Integrated model for supplier selection and negotiation in a make-to-order environment. International Journal of Production Research 42, 4457-4474.
    Chang, C.T. (2007). Multi-choice goal programming. Omega 35(4), 389-396.
    Chang, C.T. (2008). Revised multi-choice goal programming. Applied Mathematical Modelling 32, 2587-2595.
    Charnes, A. & Cooper, W.W. (1961). Management model and industrial application of linear programming. New York: Wiley.
    Chen, C.T., Lin, C.T. & Huang, S.F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics 102, 289-301.
    Cho, Y.G. & Cho, K.T. (2008). A loss function approach to group preference aggregation in the AHP. Computers & Operation Research 35, 884-892.
    Cox, A. (1999). Power, value and supply chain management. Supply Chain Management: An International Journal 4 (4), 167–175.
    Deng, H., Robert, J.W. & Yeh, C.H. (2000). Inter-company comparison using modified TOPSIS with objective weight. Computer & Operation Research 27(10), 963-973.
    Dickson, G.W. (1966). An analysis of supplier selection system and decision. Journal of Purchasing 2(1), 5-17.
    Faez, F., Ghodsypour, S.H., and O’brien, C., (2009). Vendor selection and order allocation using an integrated fuzzy case-based reasoning and mathematical programming model. International Journal of Production Economics, 121, 395-408.
    Ghodsypour, S.H. & O’Brien, C. (1998). A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. International Journal of Production Economics 56-57, 199-212.
    Ghodsypour, S.H. & O’Brien, C. (2001). The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint. International Journal of Production Economics 73, 15-27.
    Guneri, A.F., Yucel, A. & Ayyildiz, G. (2009). An integrated fuzzy-lp approach for a supplier selection problem in supply chain management. Expert Systems with Applications 36(5), 9223-9228.
    Ha, S.H. & Krishnan, R. (2008). A hybrid approach to supplier selection problem for the maintenance of a competitive supply chain. Expert Systems with Applications 34(2), 1303-1311.
    Hwang, C.L. & Yoon, K. (1981). Multiple attributes decision-making methods and applications. Spring, New York.
    Ignizio, J.P. (1976). Goal programming and extensions. Lexington Books, Lexington, MA.
    Kahraman, C., Cevik, S., Ates, N. Y. & Güfer, M. (2007). Fuzzy multi-criteria evaluation robotic systems. Computers & Industrial Engineering 52, 414-433.
    Kethley, R.B. & T.A. Waller. (2002). Improving customer service in the real estate industry: A property selection model using Taguchi loss functions. Total Quality Management 13(6), 739-748.
    Kokangul, A. & Susuz, Z. (2009). Integrated analytical hierarch process and mathematical programming to supplier selection problem with quality discount. Applied Mathematical Modelling 33, 1417-1429.
    Krajewsld, L.J. & Ritzman, L.P. (1996). Operations management strategy and analysis. Addison-Wesley Publishing Co., London.
    Kumar, M., Vrat, P. & Shankar, R. (2006). A fuzzy programming approach for vendor selection problem in a supply chain. International Journal of Production Economics 101, 273-285.
    Liao, C.N. (2009). Formulating the multi-segment goal programming. Computers & Industrial Engineering 56, 138-141.
    Liao C.N. (2010). Supplier selection project using an integrated Delphi, AHP and Taguchi loss function. ProbStat Forum 3, 118-134
    Liao, C.N. & Kao, H.P. (2010). Supplier selection model using Taguchi loss function, analytical hierarchy process and multi-choice goal programming. Computers & Industrial Engineering 58, 571–577.
    Liao, C.N. & Kao, H.P. (2011). An integrated fuzzy TOPSIS and MCGP approach to supplier selection in supply chain management. Expert Systems with Applications 38(9), 10803-10811.
    Lin, H. T. & Chang, W.L. (2008). Order selection and pricing methods using flexible quantity and fuzzy approach for buyer evaluation. European Journal of Operational Research 187(2), 415-428.
    Lin C.T., Chen, C.B. & Ting, Y.C. (2011). An ERP model for supplier selection in electronics industrial. Expert Systems with Applications 38(3), 1760-1765.
    Monczka, R.M. & Trecha S.J. (1988). Cost-based supplier performance evaluation. Journal of Purchasing and Materials Management 24(1), 2-7.
    Önüt, S., Kara, S.S. & Isik, E. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Systems with Applications 36(2), 3887-3895.
    Önüt, S. & Soner, S. (2008). Transshipment site selection using AHP and TOPSIS approaches under fuzzy environment. Waste Management 28, 1552-1559.
    Pi, W.N. & Low, C. (2005). Supplier evaluation and selection using Taguchi loss functions. International Journal of Advanced Manufacturing Technology 26, 155-160.
    Romero, C. (2001). Extended lexicographic goal programming: a unifying approach. Omega 29(1), 63-71.
    Ross, P.J. (1996). Taguchi techniques for quality engineering. McGraw-Hill, New York.
    Saaty, T.L. (1980). The Analytic Hierarchy Process. McGraw-Hill, New York.
    Saaty, T.L. (1996). Decision making with dependence and feedback: the analytic network process. RWS Publications, Pittsburgh.
    Saaty, T.L. (2000). Fundamentals of the analytic hierarchy process. RWS Publications, Pittsburgh.
    Sarami, M., Mousavi, S.F. & Sanayei, A. (2009). TQM consultant selection in SMEs with TOPSIS under fuzzy environment. Expert Systems with Applications 36(2), 2742-2749.
    Schrage, L. (2002). LINGO Release 8.0, LINDO System, Inc.
    Shin, H., Collier, D.A. & Wilson, D.D. (2000). Supplier management orientations and supplier/buyer performance. Journal of Operations Management 18, 317-333.
    Tam, M.C.Y. & Tummala, V.M.R. (2001). An application of the AHP in vendor selection of a telecommunications system. Omega 29, 171-182.
    Tamiz, M., Jones, D. & Romero, C. (1998). Goal programming for decision marking: an overview of the current state-of-the-art. European Journal of Operational Research 111(3), 567-581.
    Thomas, D.J. & Griffin, P.M. (1996). Coordinated supply chain management. European Journal of Operational Research 94, 1-15.
    Thompson, E. (1990). An approach to vendor performance evaluation. Journal of Purchasing and Materials Management 22(4), 2-8.
    Tsai, S. P. (2005). Utility, cultural symbolism and emotion: A comprehensive model of brand purchase value. International Journal of Research in Marketing 22, 277–291.
    Wang, J.W., Cheng, C.H. & Cheng, H.K. (2009). Fuzzy hierarchical TOPSIS for supplier selection. Applied Soft Computing 9, 377-386.
    Weber, C.L., Current, J.R. & Benton, W.C. (1991). Vendor selection criteria and methods. European Journal of Operational Research 50(1), 2-18.
    Willis, T.H. & Houston, C.R. (1990). Vendor requirements and evaluation in a just-in-time environment. International Journal of Operations and Production Management 10(4), 41-50.
    Wu, T. & Blackhurst, J. (2009). Supplier evaluation and selection: an augmented DEA approach. International Journal of Production Research 47(16), p4593-4608.
    Youssef, M.A., Zairi, M. & Mohanty, B. (1996). Supplier selection in an advanced manufacturing technology environment: An optimization model. Benchmark Quality Management Technology 3(4), 60-72.
    Zadeh, L. (1965). Fuzzy sets. Information Control 8, 338-353.
    Zarei, M., Fakhrzad, M.B. & Paghaleh, M.J. (2011). Food supply chain leanness using a developed QFD model. Journal of Food Engineering 102, 25-33.
    Zimmermann, H.J. (1978). Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems 1, 45-55.
    Zimmermann, H.J. (1991). Fuzzy set theory and its applications, second ed. Kluwer Academic Publishers, Boston, Dordrecht, London.

    QR CODE
    :::