有效的供應鏈管理可有效因應顧客需求，降低企業生產成本並提升企業競爭力。其中，供應商的選擇與組成，主宰了整個供應鏈管理的成效。由於選擇正確的供應商為企業成敗的一個關鍵決策，如何透過各式各樣的評選準則去選擇出優良的供應商正是供應鏈管理文獻上廣泛討論的課題。然在供應商評選的文獻中，目前大多著墨於整體供應鏈的供應商評選為主，針對個別企業對零組件有需求的情況下而進行之零組件供應商評選的議題討論較少。本研究回顧供應鏈管理、供應商評選、約略集合理論與模糊理論的重要文獻，提出在滿足企業對零組件供應商之需求下，找尋整體產品之最適供應鏈之供應商評選方法。同時針對以往學者所提出之模糊約略集合演算法可能發生之缺失，調整修正而發展出「改良式模糊約略集合演算法」以作為零組件供應商篩選之規則產生方法。同時將前述產生之規則透過基因演算法之運算，正確且快速地求得在滿足企業需求之零組件供應商中所建立之最適產品供應鏈。整體而言，本研究發展出一套供應商評選之雛形系統，佐以實驗來驗證此改良式模糊約略集合演算法的成效。實驗結果顯示，經此改良式模糊約略集合演算法篩選過後之零組件供應商群中所產出整體產品最適供應鏈之總效用，明顯優於傳統使用人工所設定評選準則的門檻值以進行零組件供應商篩選與產出整體產品供應鏈之總效用。因此本研究所發展之供應商評選方法，不但為相關零組件供應商評選研究上提供了一套雛形系統，未來更可繼續發展成實用模型，協助企業在供應鏈管理實務上之決策。

Effective Supply Chain Management (SCM) can respond with the customers’ instant demand, lower the production cost, and enhance the competitive strength of the enterprise. Thus, how to evaluate and select the appropriate suppliers into the supply chain plays a critical role that determines the success or not of SCM. A plenty of research about the supplier selection had been conducted; however, most of them put attention on the supplier selection issues on the scope of whole supply chain system. Few researches have focused on how an individual company selects the component providers. After reviewing the literatures about the SCM, Supplier Selection, Rough Set Theory, and Fuzzy Theory, this study firstly developed the “Adaptive Fuzzy Rough Set” algorithm to generate the criteria for selecting the suppliers. Those criteria then were introduced into the Genetic Algorithms for generating the optimal supply chain. This supplier selection developed in this study was also empirically verified. The results point out that the generalized utility from the providers selected by this framework is significantly superior to those by traditional models in which the thres holds was manually and arbitrarily set. To sum up, this study not only provides a useful method in selecting the component providers for the SCM academic studies, but also helps to develop the practical module for the enterprise in deciding their component providers.

摘要 I
Abstract II
致謝 III
目錄 IV
圖目錄 VI
表目錄 VII
第一章 緒論 1
1.1 研究動機與背景 1
1.2 研究目的 4
1.3 論文架構 6
1.4 研究限制與範圍 7
1.5 研究流程架構 9
第二章 文獻探討 10
2.1 供應鏈管理 10
2.2 供應商評選 13
2.3 約略集合 19
2.4 模糊理論 24
第三章 研究方法 31
3.1 模糊約略集合演算法分析 32
3.2 供應商評選準則之選擇與評選方法 39
3.3 改良式模糊約略集合演算法 42
3.4 基因演算法 46
3.5 供應商評選方法 53
第四章 雛型系統與實驗分析 60
4.1 系統描述 60
4.2 基因演算法之參數說明 60
4.3 範例說明 62
4.4 實驗進行 95
第五章 結論與未來研究 108
參考文獻 110
附錄一 零組件供應商門檻值設定之問卷 117

圖目錄
圖 2-1 供應商評選流程 15
圖 2-2 上界近似與下界近似 21
圖 2-3 一般常用的標準隸屬函數 27
圖 2-4 三角型模糊數 28
圖 2-5 梯型模糊數 29
圖 3-1 改良式模糊約略集合演算法流程圖 44
圖 3-2 常見的基因編碼方式 47
圖 3-3 染色體交配方式(黑框為交配部分) 50
圖 3-4 染色體突變方法(黑框為突變部份) 51
圖 3-5 基因演算法流程圖 51
圖 3-6 供應商評選法流程圖 59
圖 4-1 範例流程圖 64
圖 4-2 隸屬函數 68
圖 4-3 基因演算法收斂圖 95
圖 4-4 實驗流程圖 97
圖 4-5 改良式模糊約略集合演算法之規則 102


表目錄
表2-1 Dickson 23 項供應商評選準則與Weber 之文獻整理 16
表2-2 供應商評選準則之文獻整理 18
表3-1 模糊約略集合演算法之相關研究 34
表3-2 傳統模糊約略集合演算法之優缺點 36
表3-3 模糊約略集合演算法之符號說明 38
表4-1 供應商部分資料表 60
表4-2 PC 基版之供應商資料表 66
表4-3 PC 基版之正規化供應商資料表 68
表4-4 PC 基版之模糊化供應商資料庫 69
表4-5 PC 基版之篩選過供應商資料庫 70
表4-6 LCD 觸控螢幕之供應商資料表 81
表4-7 LCD 觸控螢幕之正規化供應商資料表 82
表4-8 LCD 觸控螢幕模糊化供應商資料庫 83
表4-9 LCD 觸控螢幕之篩選過供應商資料庫 84
表4-10 基因演算法之部分初始母體 92
表4-11 第五代母體 93
表4-12 第20 代母體 94
表4-13 第40 代母體 94
表4-14 問卷整理之結果 99
表4-15 控制組之基因演算法結果 101
表4-16 實驗組之基因演算法結果 103
表4-17 控制組與實驗組總效用之結果 104
表4-18 T 檢定－獨立樣本檢定 106

Abratt, R., (1986). Industrial buying in high-tech markets. Industrial Marketing Management 15(4), 293–298.
Agrawal, R. and Srikant,R., (1994), Fast algorithms for mining association rules, Proc. of the20th Conf. on Very Large Databases,487-499.
Amid, S. H., and Razmi J., (2009). An integrated fuzzy model for supplier management: A case study of ISP selection and evaluation, Expert Systems with Applications 36, 8639–8648
Ahn, H., and Kim, K.J., (2009). Bankruptcy prediction modeling with hybrid case-based reasoning and genetic algorithms approach, Applied Soft Computing 9, 599–607.
Albino, V., and Carbonara, N., and Giannoccaro, I., (2007). Supply Chain Cooperation in Industrial Districts: A Simulation Analysis, European Journal of Operational Research 177, 261-280.
Bai, C., and Sarkis J., (2010). Integrating sustainability into supplier selection with grey system and rough set methodologies, Int. J. Production Economics 124, 252–264.
Barbarosoglu, G., and Yazgac, T., (1997). An application of the analytic hierarchy process to the supplier selection problem, Production and Inventory Management Journal 1st quarter, 14–21.
Borisovsky, P., Dolgui, A., and Eremeev, A. (2008). Genetic algorithms for a supply management problem: MIP-recombination vs greedy decoder, European Journal of Operational Research 195, 770-779
Buffa, F.P., and Jackson, W.M., (1983) .A goal programming model for purchase planning, Journal of Purchasing and Materials Management 19 (3), 27–34.
Chaudhry, S.S., Forst, F.G., and Zydiak, J.L., (1993). Vendor selection with price breaks, European Journal of Operational Research, 7052–66.
Chan, F.T.S., and Kumar, N., (2007). Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega 35(4), 417-431.
Chang, B., Hung, H.F., and Lo, C.C., (2009) .Supplier Selection Using Rough set Theory, Industrial Engineering and Engineering Management 2007(Dec.), 1461 – 1465.
Che, Z.H., and Wang, H.S., (2008). Supplier selection and supply quantity allocation of common and non-common parts with multiple criteria under multiple products, Computers & Industrial Engineering 55, 110-133.
Chen S.M., and Lee L.W., (2010) .Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method, Expert Systems with Applications 37, 2790–2798.
Chen, D., Yang W., and Li, F.,(2008) Measures of general fuzzy rough sets on a probabilistic space, Information Sciences178, 3177-3187.
Chena, D., Heb Q., and Wang, X.,(2010). FRSVMs: Fuzzy rough set based support vector machines, Fuzzy set and systems, Fuzzy Sets and Systems 161, 596 – 607.
Choi, T.Y., and Hartley, J.L., (1996). An Explortation of Supplier Selection Practices across the Supply Chain, Journal of Operation Management 14, 333-343.
Choy, K.L., Lee, W.B., and Lo, V., (2002). An intelligent supplier management tool for benchmarking suppliers in outsources manufacturing. Expert Systems with Applications 22, 213–224.
Crama, Y., Pascual J., R., and Torres, A., (2004). Optimal procurement decisions in the presence of total quantity discounts and alternative product recipes. European Journal of Operational Research 159, 364–378.
Dacin, M.T., and Hitt, M. A. (1997). Selecting partners for successful international alliances: Examination of US and Korean firms. Journal of World Business 32(1), 3–16.
De Boer, L.,and Van der Wegen, L. L. M. (2003). Practice and promise of formal supplier selection: A study of four empirical cases. Journal of Purchasing and Supply Management 9(3), 109–118.
De Boer, L., Labro, E., and Morlacchi, P. (2001). A review of methods supporting supplier selection. Journal of Purchasing and Supply Management 7(1), 75–89.
Dickson, G. W., (1966).An Analysis of Vender Selection Systems and Decisions, Journal of Purchasing 2(1), 5-17.
Donaldson, B. (1994), Supplier Selection Criteria on the Service Dimension, European Journal of Purchasing and Supply Management 4, 209-217.
Dubois, D., and Prade, H, (1990). Rough fuzzy sets and fuzzy rough sets. Internat. J. General Systems 17(2–3), 191–209.
Dulmin, R., and Mininno, V., (2003). Supplier selection using a multi-criteria decision aid method. Journal of Purchasing and Supply Management 9, 177–187.
Dyer, J.S., Fishburn, P.C., Steuer, R.E., Wallenius, J., and Zionts, S., (1992) .Multiple criteria decision making, multi attribute utility theory: The next ten years, Management Science 38 (5) ,645.
Dymova, L., Sevastianov, P., and Bartosiewicz P. (2010). A new approach to the rule-base evidential reasoning: Stock trading expert system application, Expert Systems with Applications 37, 5564–5576.
Farley, G.A., (1997). Discovering supply chain management: a roundtable discussion. APICS -The Performance Advantage 7 (1), 38-39
Giannocearo, L. and Pontrandolfo, P. (2002), Inventory management in supply chains: A reinforcement learning approach, International Journal of Production Economics, 78(2), 153-161.
Guneri, A. F., Yucel, A., and Ayyildiz, G., (2009). An integrated fuzzy-lp approach for a supplier selection problem in supply chain management, Expert Systems with Applications 36, 9223–9228.
Hassanien, A.E., (2007).Fuzzy rough sets hybrid scheme for breast cancer detection, Image and Vision Computing 25, 172–183.
Harland, C.M., (1996). Supply chain management: relationships, chains and networks, British Academy of Management 7 (Special Issue), 63-80.
Hong, T.P. , Liou, Y.L., and Wang S.L., (2009). Fuzzy rough sets with hierarchical quantitative attribute, Expert Systems with Applications 36, 6790-6799.
Hong, T.P., Tseng L.H., and Chien, B.C., (2010). Mining from incomplete quantitative data by fuzzy rough sets, Expert Systems with Applications 37(3), 2644-2653.
Hong, T.P., Wang, T.T., Wang, S.L. and Chien B.C., (2000). Knowledge learning a coverage set of maximally general fuzzy rules by rough sets, Expert Systems with Application, 19, 97-103.
Hong, W.D., Lyes, B., and Xie, X.L., (2005). A simulation optimization methodology for supplier selection problem, International Journal of Computer Integrated Manufacturing 18 (2–3) 210–224.
Humphreys, P., Huang, G., Cadden, T., and McIvor, R., (2007). Integrating design metrics within the early supplier selection process. Journal of Purchasing and Supply Management 13, 42–52.
Jain, V., Wadhwa, S., and Deshmukh, S. G. (2009). Select supplier-related issues in modeling a dynamic supply chain: potential, challenges and direction for future research, International Journal of Production Research, 47(11), 3013-3039.
Keskin, G.A., Ilhan, S., and Özkan, C., (2010). The Fuzzy ART algorithm: A categorization method for supplier evaluation and selection, Expert Systems with Applications 37, 1235–1240.
Kumar, M., Vrat, P., and Shankar, R, (2004). A fuzzy goal programming approach for vendor selection problem in a supply chain. Computers & Industrial Engineering, 46, 69–85.
Lambert, D. M., Cooper, M. C., and Pagh, J. D., (1998). Supply Chain Management: Implementation Issues and Research Opportunities, The International Journal of Logistics Management 9(2), 1- 19.
Lee, A.H.I, (2009). A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks, Expert Systems with Applications 36, 2879–2893.
Lehmann, D. R., and O’Shaughnessy, O., (1974). Difference in Attribute Importance for Different Industrial Products, Journal of Marketing 38, 36-42.
Li, S., Ragu-Nathan, B., Ragu-Nathan, T. S., and Rao, S. (2006). The impact of supply chain management practices on competitive advantage and organizational performance, Omega, 34(2), 107-124.
Lin, K.P., Chang, P.T., Hung, K.C., and Pai, P.F.,(2010). A simulation of vendor managed inventory dynamics using fuzzy arithmetic operations with genetic algorithms, Expert Systems with Applications 37, 2571-2579.
Liu, J.W., Cheng, C.H. Chen, Y. H., and Chen, T.L. (2010). OWA rough set model for forecasting the revenues growth rate of the electronic industry, Expert Systems with Applications 37, 610-617.
Meade, L., Sarkis, J., (1999). Analyzing organizational project alternatives for agile manufacturing processes: an analytical network approach. International Journal of Production Research 37 (2), 241–261.
Mentzer, J.T., Flint, D.J., and Hult, G.T., (2001). Logistics service quality as a segment-customized process, Journal of Marketing (65), 82-104.
Min, H., and Galle, W.P., (1999). Electronic commerce usage in business to business purchasing. International Journal of Operations and Production Management 19(9), 909–921.
Minner, S., (2003). Multiple-supplier inventory models in supply chain management: a review. International Journal of Production Economics, 81-82,265–279.
Narasimhan, R., (1983). An analytic approach to supplier selection, Journal of Purchasing and Supply Management 1, 27–32.
New S.J., and Payne P., (1995).Research frameworks in logistics: three models, seven dinners and a survey, International Journal of Physical Distribution and Logistics Management 25 (10), 60-77.
Oliver, R. K., and Webber, M. D., (1982). Supply-Chain Management: Logistics Catches Up with Strategy. Outlook, cit. Martin Christopher, Logistics, The Strategic Issue. London Chapman and Hall, 1992.
Pawlak Z., (1982). Rough sets, International Journal of Computer and Information Science 11, 341-356.
Pourakbar, M., Farahani, R.Z., and Asgari, N.,(2007).A joint economic lot-size model for an integrated supply network using genetic algorithm, Applied Mathematics and Computation 189, 583–596
Rezaei, J., and Davoodi, M., (2008). A deterministic, multi-item inventory model with supplier selection and imperfect quality, Applied Mathematical Modelling 32, 2106-2116.
Sarkis, J., Talluri, S., and Gunasekaran, A., (2007). A strategic model for agile virtual enterprise partner selection. International Journal of Operations and Production Management 27 (11), 1213–1234.
Sonmez, M. (2006). A review and critique of supplier selection process and practices. Business school papers series 2006(1), Loughborough University.
Stank, T. P., Davis, B. R., and Fugate, B. S. (2005). A strategic framework for supply chain oriented logistics, Journal of Business Logistics, 26(2), 27-45.
Sun, B., Gong, Z., and Chen D.,(2008). Fuzzy rough set theory for the interval-valued fuzzy information systems, Information Sciences 178 , 2794–2815.
Timmerman, E., (1986). An approach to vendor performance evaluation, Journal of Purchasing and Supply Management 1, 27–32.
Thomas, J. (1999). Why your supply chain doesn't work, Logistics Management and Distribution Report, 38(6), 42-44.
Thompson, K.N., (1990), Vendor profile analysis, Journal of Purchasing and Materials Management 26 (1) 11–18.
Vokurka, R.J., and Fliedner, G.J., (1998).The journey toward agility. Industrial Data and Management Systems 98 (4), 165–171.
Walczak, B., and Massart D.L., (1999) .Rough Sets Theory, Chemometrics and Intelligent Laboratory Systems 47, 1-16.
Wang, H.S., (2008). Configuration change assessment: Genetic optimization approach with fuzzy multiple criteria for part supplier selection decisions, Expert Systems with Applications 34, 1541–1555
Wang, Y.F., (2003).Mining stock price using fuzzy rough set system , Expert Systems with Applications 24(1), 13-23.
Weber, C. A., Current J. R., and Benton, W.C., (1990). Vendor selection criteria and methods, European Journal of Operational Research 50(1), 2-18.
Willis, HT, Huston RC, and Pohlkamp F., (1993) Evaluation measures of just in time supplier performance. Production and Inventory Management Journal 34(2), 1–5.
Wilson E.J., (1994). The Relative Importance of Supplier Selection Criteria: A Review and Update, International Journal of Purchasing and Materials Management 30 (3), 35-41.
Xiao, Z., Chen, L., and Zhong, B., (2010). A model based on rough set theory combined with algebraic structure and its application: Bridges maintenance management evaluation, Expert Systems with Applications 37, 5295-5299.
Yeh, C.C., Chi, D.J., and Hsu, M.F., (2010). A hybrid approach of DEA, rough set and support vector machines for business failure prediction, Expert Systems with Applications 37, 1535-1541.
Zadeh, L. A., (1965). Fuzzy sets, Information and Control 8(3), 338-353.
Zegordi, S.H., Kamal Abadi, I.N., and Beheshti Nia, M.A., (2010). A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain, Computers & Industrial Engineering 58, 373-381.
Zhai, L.Y., Khoo, L.P., and Zhong, Z.W. (2009a). A dominance-based rough set approach to Kansei Engineering in product development, Expert Systems with Applications 36, 393-402.
Zhai, L.Y., Khoo, L.P., Zhong, Z.W., (2009b). Design concept evaluation in product development using rough sets and grey relation analysis, Expert Systems with Applications 36, 7072–7079
Zhao, S., and Tsang E.C.C.,(2008). On fuzzy approximation operators in attribute reduction with fuzzy rough sets, Information Sciences178, 3163-3176.

書籍
Bowersox, D. J. and Closs, D. J. (1996), Logistical Management: The Integrated Supply Chain Process, McGraw-Hill. , New York.
Christopher, M., (2004), Logistics and Supply Chain Management, 2nd ed., Prentice Hall, Norfolk.
Dobler, DW, Lee L, and Burt N., (1990) Purchasing and materials management: text and cases. McGraw-Hill Publisher, New York.
Dulmin, R., and Mininno, V., (2003).A Fuzzy Logic Approach to Improve Manufacturing Effectiveness. Springer Berlin-Heidelberg Publishing, New York.
Goldberg, D. (1989). Genetic algorithms in search, optimization, and machine learning. Addison Wesley, Reading Publisher, MA.
Graham, I., and Jones, P. L. (1988). Expert systems—knowledge, uncertainty and decision. Chapman & Hall, Ltd. Publisher, London, UK.
Harrison, A., and Hoek, R., (2005). Logistics Management and Strategy, 2nd ed., Prentice Hall, Essex.
Heckerman, D., Mannila, H., Pregibon, D., and Uthurusamy, R., (1997). Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, AAAI Press Publisher, CA
Holland, J.H. (1975). Adaptation in natural and artificial systems, Ann Arbor. MI: The University of Michigan Press. Publisher.
Kaufmann, A., and Gupta. (1991). Introduction to Fuzzy Arithmetic: Theory and Applications, Van No strand Reinhold Publisher, New York.
Monczka, R., Trent, R., Handfield, R., (1998). Purchasing and Supply Chain Management. South-Western College Publishing, New York.
Pawlak, Z., (1991). Rough Sets: Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, Netherlands.
Roscoe, J. T. (1975). Fundamental research statistics for the Behavioral sciences. New York: Holt Rinehart and Winston.
Seuring S, Müller M, Westhaus M, and Morana R., (2005).Conducting a literature review the example of sustainability in supply chains. Physica-Verlag HD Publishing.
Simchi-Levi, D., Kaminsky, P., and Simchi-Levi, E., (2000). Designing and managing the supply chain, 1st Ed., Irwin McGraw-Hill, and New York, NY.
Simchi-Levi, D., Kaminsky, P., Simchi-Levi, E., (2004). Managing the Supply Chain: The Definitive Guide for the Business Professional, McGraw-Hill, New York.
Stevenson, W.J., (1998).Production Management, 3nd ed., McGraw-Hill Publishing, New York.
Yager, R. R., Ovchinnikov, S., Tong, R. M., and Nguyen, H.T., (1987) .Fuzzy Sets and Applications：Selected Papers by L.A. Zadeh, John Wiley & Sons Publisher, MA.
Zopounidis Constantin, (1998). Operational Tools in the Management of Financial Risk, Springer Publisher, NY.