簡易檢索 / 詳目顯示

回結果列表
研究生： Fransiskus Verdian Sudjatmika
Fransiskus - Verdian Sudjatmika
論文名稱： 使用模糊階層式分析法求解供應商評選問題-食品工業個案研究
Solving Supplier Selection Problem Based on the Fuzzy Analytic Hierarchy Process - A Case Study on the Food Industry
指導教授： 羅士哲
Shih-Che Lo
口試委員: 林希偉
Shi-Woei Lin
蔡鴻旭
Hung-Hsu Tsai
學位類別： 碩士
Master
系所名稱： 管理學院 - 工業管理系
Department of Industrial Management
論文出版年： 2014
畢業學年度： 103
語文別： 英文
論文頁數： 93
中文關鍵詞： 決策 、區隔 、模糊層次分析法 、供應商選擇問題
外文關鍵詞： Decision making, Segmentation, Fuzzy analytic hierarchy process, Supplier selection problem.
相關次數： 點閱：362  下載：26 
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

    • 現今，供應商的選擇已經成為最重要的問題之一，而且在每家公司的發展中也扮演著關鍵的角色｡因此，對每家公司來說，成功地選擇供應商是非常重要的，況且公司也需要長時間來承擔所做的選擇，另外，也需投入大量的資金和精力｡因此，當每家公司尚處於起步階段時，公司需要不斷的選擇最好的供應商｡然而，如果選擇正確的供應商，公司可能就會從中獲利｡否則，公司可能面臨許多問題，所以對於決策者來說，在每個階段選擇合適的決定是相當重要的｡
    本研究主要提出模糊層次分析法(FAHP)來評估供應商的效率｡由於這是一個多準則決策問題，我們將問題分成兩個主要的分群準則，包括能力和意願兩大準則｡然而模糊層次分析方法能夠得到公司的候選供應商的排序，所以我們為公司選擇最好的決定｡根據我們的研究案例得到一個結論，我們所提出的方法是非常實用且有效率的幫助決策者選出要與哪個供應商做進一步的合作｡

    Supplier selection has become one of the most important problems and plays a key role in every company. It is vital for every company to successfully select suppliers, also requires companies to undertake selection for a long time, and to invest enormous of capital and effort. Therefore, every company has to keep making critical decisions in choosing the best supplier while the company is still in the beginning stage. However, if the decision for the supplier choosing is right, the company can make profit from it. Otherwise, the company may face the crisis of having many problems, so it is very important for the decision maker to make proper decisions in every phase.
    This study aims to propose a Fuzzy Analytic Hierarchy Process (FAHP) method for the efficiency evaluation of suppliers. Since it is a multi-criteria decision making problem, we decompose the problem into two main clusters grouping criteria including the criterion of Capability and Willingness, and the FAHP method is able to acquire a ranking of the candidate supplier for the case company, so we choose the best solution for the company. Following our case study, we conclude that the proposed method is a very practical and efficient technique for the decision makers to select which supplier to go for further working together.

    摘要....................................................................i ABSTRACT................................................................ii ACKNOWLEDGMENTS.........................................................iii CONTENTS................................................................iv FIGURES.................................................................vi TABLES..................................................................vii CHAPTER 1 INTRODUCTION..................................................1 1.1 Research Motivation.................................................1 1.2 Research Structure..................................................3 CHAPTER 2 LITERATURE REVIEW.............................................4 2.1 Decision-Making Methods.............................................4 2.1.1 Linear Weighting Model............................................4 2.1.2 Statistical Hypothesis Testing....................................6 2.1.3 Decision Tree.....................................................8 2.1.4 Goal Programming..................................................11 2.1.5 Structural Equation Modeling......................................13 2.1.6 Game Theory.......................................................15 2.2 Multi Criteria Decision Making......................................17 2.2.1 TOPSIS............................................................19 2.2.2 ELECTRE...........................................................20 2.2.3 Grey Theory.......................................................21 2.3 Fuzzy Set Theory....................................................22 2.4 AHP and FAHP........................................................25 2.4.1 AHP...............................................................25 2.4.2 FAHP..............................................................29 CHAPTER 3 PROBLEM FORMULATION AND FUZZY ANALYTIC HIERARCHY PROCESS......32 3.1 Introduction to Fuzzy Theory........................................32 3.1.1 Fuzzy Numbers.....................................................32 3.1.2 Linguistic Variables..............................................33 3.2 AHP.................................................................34 3.3 FAHP................................................................37 CHAPTER 4 COMPUTATIONAL EXPERIMENTS.....................................40 4.1 Data Collection.....................................................40 4.1.1 Capabilities Criteria.............................................42 4.1.2 Willingness Criteria..............................................43 4.2 Fuzzy Multiple Criteria Decision-Making.............................45 4.2.1 The FAHP Model....................................................45 4.2.2 The Implementation................................................46 4.3 Summary of the Experiment...........................................53 CHAPTER 5 CONCLUSIONS AND FUTURE RESEARCH...............................57 5.1 Conclusions.........................................................57 5.2 Further Research....................................................57 REFERENCES..............................................................59 APPENDIX................................................................65

    Akarte, M.M., Surendra, N.V., Ravi, B., and Rangaraj, N. (2001). Web Based Casting Supplier Evaluation Using Analytical Hierarchy Process, Journal of the Operational Research Society, 52, 511–522.
    Ataei, E. (2013). Application of TOPSIS and Fuzzy TOPSIS Methods for Plant Layout Design, World Applied Science Journal, 24(7), 908-913.
    Baily, P. (2010). Purchasing Procurement, Principles and Management, Prentice Hall, 10.
    Beccali, G., Cellura, M., and Mistretta, M. (2003). New Exergy Criterion in The Multi-Criteria Context: A Life Cycle Assessment of Two Plaster Products, Elsevier, 14(17), 2821-2838.
    Bellman, R. E., and Zadeh, L. A. (1970). Decision-Making in a Fuzzy Environment Management, Management Science, 17(4), 141–164.
    Bezdek, J.C. (1978). Fuzzy Partitions and Relations and Axiomatic Basis for Clustering, Fuzzy Sets and Systems, 1, 111–127
    Bollen, K. A. (1989). Structural Equations with Latent Variables, New York, NY: John Wiley and Sons, Inc.
    Buckley, J. J. (1985). Fuzzy Hierarchical Analysis, Fuzzy Sets and Systems, 17, 233–247.
    Buyukozkan, G., Arsenyan, J., and Ruan, D. (2012). Logistics Tool Selection With Two-Phase Fuzzy Multi Criteria Decision Making: A Case Study for Personal Digital Assistant Selection, Expert Systems with Applications, 39(1), 142-153.
    Buyukozkan, G., and Cifci, G. (2012). A Combined Fuzzy AHP and Fuzzy TOPSIS Based Strategic Analysis of Electronic Service Quality in Healthcare Industry, Expert Systems with Applications, 39(3), 2341–2354.
    Cabuk, S. (1986). Simple Test of Hypotheses on System Availability and Mean Time to Repair, IEEE Transactions on Reliability, 35(5), 581–583.
    Calabrese, A., and Costa, R. (2013). Using Fuzzy AHP to Manage Intellectual Capital Assets: An Application to the ICT Service industry, Expert Systems with Applications, 40(9), 3747–3755.
    Chan, F. T. S. (2003). Interactive Selection Model for Supplier Selection Process: An Analytical Hierarchy Process Approach, International Journal Production Research, 41, 3549–3579.
    Chan, F. T. S., and Chan, H.K. (2004). Development of The Supplier Selection Model – A Case Study in The Advanced Technology Industry, Proceedings of the Institution of Mechanical Engineers Part B – Journal of Engineering Manufacture, 218, 1807–1824.
    Cebeci, U. (2009). Fuzzy AHP-Based Decision Support System for Selecting ERP Systems in Textile Industry by Using Balanced Scorecard, Expert Systems with Applications, 36, 8900–8909.
    Cebeci, U., and Ruan, D. (2007). A Multi-Attribute Comparison of Turkish Quality Consultants by Fuzzy AHP, International Journal of Information Technology and Decision Making, 6(1), 191–207.
    Chan, F. T. S., Chan, M. H., and Tang, N. K. H. (2000). Evaluation Methodologies for Technology Selection, Journal of Materials Processing Technology, 107, 330–337.
    Charnes A., Cooper W. W., Ferguson R. (1955). Optimal Estimation of Executive Compensation by Linear Programming, Management Science, 1, 138-151.
    Cheng, C. H., Yang, K. L., and Hwang, C. L. (1999). Evaluating Attack Helicopters by AHP Based on Linguistic Variable Weight, European Journal of Operational Research, 116(2), 423–443.
    De Cock, M., Bodenhofer, U., and Kerre, E. E. (2000). Modelling Linguistic Expressions Using Fuzzy Relations, Proceedings 6th International Conference on Soft Computing, 353-360.
    DiNardo, G., Levy, D., and Golden, B. (1989). Using Decision Analysis to Maryland’s River Herring Fishery: An Application of AHP, Journal of Environmental Management, 29(1), 193–213.
    Economides, A. A., and Silvester, J. A. (1991). Multi-Objective Routing in Integrated Services Networks: A Game Theory Approach, Tenth Annual Joint Conference of the IEEE Computer and Communications Societies. Networking in the 90s, 3, 1220–1227.
    Eilon, S. (1967). On The Theory of Games, The Production Engineer, 46(2), 112–120.
    Fisher, R. A. (1955). Statistical Methods and Scientific Induction, Journal of the Royal Statistical Society, 17(1), 69–78.
    Forman, E. H., and Singpurwalla, N. D. (1979). Optimal Time Intervals for Testing Hypotheses on Computer Software Errors, IEEE Transactions on Reliability, R–28(3), 250–253.
    Gandpa1, J. I., Olateju, O. E., and Ehie, I. (2011). An Integrated Analytic Hierarchy Process-Linear Programming (AHP-LP) Model for Capital Budgeting, Journal of Economics and International Finance, 3(4), 246–258.
    Geng, W., and Hu, Y. (2012). Information Security Management Model Based on AHP, 2012 International Conference on Measurement, Information and Control, 352–355.
    Hepp, M., Sayal, M., Lee, S., and Lee, J. (2007). Data Engineering Issues in E-Commerce and Services: DEECS 2007 Workshop Summary, DEECS 2007, 1–3.
    Hsieh, T. Y., Lu, S. T., and Tzeng, G. H. (2004). Fuzzy MCDM Approach for Planning and Design Tenders Selection in Public Office Buildings, International Journal of Project Management, 22, 573–584.
    Huang, D., and Meyn, S. (2012). Error Exponents for Composite Hypothesis Testing with Small Samples, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing, 3261–3264.
    Huang, W. C., and Chen C. H. (2005). Using the ELECTRE II Method to Apply and Analyze the Differentiation Theory, Proceedings of The Eastern Asia Society for Transportation Studies, 5, 2237-2249.
    Ijiri, Y. (1965). Management Goals and Accounting for Control, North Holland Pub. Co, University of Michigan.
    Kahraman, C., Ulukan, Z., and Tolga, E. (1998). A Fuzzy Weighted Evaluation Method Using Objective and Subjective Measures, ICSC Symposium on Engineering of Intelligent Systems (EIS’98), 1, 57–63.
    Keown, A. J., and Taylor, B. W. (1978). Integer Goal Programming Model for the Implementation of Multiple Corporate Objectives, Journal of Business Research, 221-235.
    Kulak, O., and Kahraman, C. (2005). Fuzzy Multi-Attribute Selection Among Transportation Companies Using Axiomatic Design and Analytic Hierarchy Process, Journal Information Sciences - Informatics and Computer Science: An International Journal, 170, 191-210.
    Kuzmin, V. B. (1982). Building Group Decisions in Spaces of Strict and Fuzzy Binary Relations, Nauka, Moscow, (in Russian).
    Lee, M., Pham, H., and Zhang, X. (1999). A Methodology for Priority Setting with Application to Software Development Process, European Journal of Operational. Research, 118, 375–389.
    Lee, S., and Ahn, H. (2009). Structural Equation Model for EDI controls: Controls Design Perspective. Expert Systems with Applications, 36(2), 1731–1749.
    Lee, S. M. (1972). Goal Programming for Decision Analysis, Auerbach Publication, Auerbach Management and Communication Series.
    Lei, P. W., and Wu, Q. (2007). Introduction to Structural Equation Modeling: Issues and Practical Considerations, Educational Measurement: Issues and Practice, 26(3), 33–43.
    Li, X., Nukala, S., and Mohebbi, S. (2013). Game Theory Methodology for Optimizing Retailers’ Pricing and Shelf-space Allocation Decisions on Competing Substitutable Products, International Journal of Advanced Manufacturing Technology, 1–15.
    Li, Y., and Wang, L. H. (2010). A Study on Manufacturer and Suppliers for Product Innovation Coordinating to Avoid the Risk Based on Game Theory, 2010 IEEE 17Th International Conference on Industrial Engineering and Engineering Management, 1254–1257.
    Liang T., and Tang, W. (2009). Fuzzy Game Theory and Applications in Financing, International Conference on Management and Service Science, 1–4.
    Liu, S. Y., and Chen, J. G. (1995). Development of a Machine Troubleshooting Expert System via Fuzzy Multi-Attribute Decision Making Approach, Expert Systems with Applications, 8(1), 187-201.
    Meng, Q. W., He, Q., Li, N., Du, X. R., and Su, L. N. (2009). Crisp Decision Tree Induction Based on Fuzzy Decision Tree Algorithm, International Conference on Information Science and Engineering, Nanjing, China, 4811–4814.
    Navada, A., Ansari, A. N., Patil, S., and Sonkamble, B. A. (2011). Overview of The Use of Decision Tree algorithms in Machine Learning, 2011 IEEE Control and System Graduate Research Colloquium, 37–42.
    Oddershede, A. M., Carrasco, A. R., and Barham, E. (2008). Multi-Criteria Decision Model for Assessing Health Service Information Technology Network Support Using the Analytic Hierarchy Process, Ibero - American Journal of Computing, Computation and Systems.
    Papastavrou, J. D., and Athans, M. (1992). On Optimal Distributed Decision Architectures in a Hypothesis Testing Environment, IEEE Transactions on Automatic Control, 37(8), 1154–1169.
    Punniyamoorthy, M., Mathiyalagan, P., and Parthiban, P. (2011). A Strategic Model Using Structural Equation Modeling and Fuzzy Logic in Supplier Selection, Expert Systems with Applications, 38(1), 458–474.
    Rezaei, J., and Ortt, R. (2013). Multi-Criteria Supplier Segmentation Using a Fuzzy Preference Relations Based AHP, European Journal of Operational Research, 225, 75–84.
    Roylance, D. (2006). Purchasing Performance: Measuring, Marketing and Selling the Purchasing, Ashgate Pub Co.
    Rupesh, K. P., Vrat, P., and Kumar, P. (2008). A Goal Programming Model for Paper Recycling System, OMEGA.
    Rustem, B. (1998). A Logic-Based Modelling Language and Integer Programming Framework for Multicriteria Optimization, PhD Dissertation, Department of Computing, Imperial College.
    Saaty, T. L. (1990). The Analytic Hierarchy Process. RWS Publications, 2, Pittsburgh.
    Saaty, T. L., and Gholamnezhad, H. (1982). High-level Nuclear Waste Management: Analysis of Options, Environment and Planning B, 9(1), 181–196.
    Salii, V. N. (1965). Binary L-relations, Matematika, 44, 1, 133–145
    Saaty, T. L., and Kearns, K. P. (1985). Analytical Planning: The Organization of Systems. Oxford: Pergamon Press.
    Saaty, T. L., Vargas, L. G., and Dellmann, K. (2003). The Allocation of Intangible Resources the Analytic Hierarchy Process and Linear Programming, Socio-Economic Planning Sciences, 37(3), 169–184.
    Saghafian, S., and Hejazi, S. R. (2005). Multi-Criteria Group Decision Making Using a Modified Fuzzy TOPSIS Procedure, IEEE, 215-221.
    Shaw, K., Shankar, R., Yadav, S. S., and Thakur, L. S. (2012). Supplier Selection Using Fuzzy AHP and Fuzzy Multi-objective Linear Programming for Developing Low Carbon Supply Chain, Expert Systems with Applications, 39(9), 8182–8192.
    Simaan, M. A., and Takayama, T. (1976). An Application of Differential Game Theory to a Dynamic Duopoly Problem with Maximum Production Constraints, 1976 IEEE Conference on Decision and Control including the 15th Symposium on Adaptive Processes, 15(1), 111–116.
    Tsai, C. F. (2012). The Application of Grey Theory to Taiwan Pollution Prediction, Proceedings of The World Congress on Engineering, 2, 731-736.
    Trennepohl, G. L. (1975). An Application of Goal Programming to Bank Asset Management, Proceedings of Southwest American Institute of Decision Science Meeting.
    Varley, R. (2006). Retail Product Management: Buying and Merchandising. Routledge, 2.
    Varshney, K. R., and Varshney, L. R. (2011). Multilevel Minimax Hypothesis Testing. In Proceedings of the IEEE International Workshop on Statistical Signal Processing, Nice, France, 109–112.
    Vidal, L. A., Sahin, E., Martelli, N., Berhoune, M., and Bonan, B. (2010). Applying AHP to Select Drugs to be Produced by Anticipation in a Chemotherapy Compounding Unit, Expert Systems with Applications, 37, 1528–1534.
    Von Neumann, J., and Morgenstern, O. (1944). Theory of Games and Economic Behavior, Princeton University Press.
    Wang, T. C., and Chen, Y. H. (2008). Applying Fuzzy Linguistic Preference Relations to the Improvement of Consistency of Fuzzy AHP, Information Sciences 178, 3755-3765.
    Yang, C. Z., and Li, H. M. (2011). Corporate Strategy and Environment: Study Based on Structural Equation Modeling. International Conference on Management Science and Engineering, Rome, Italy, 557–561.
    Yang, R., and Wang, X. (2012). Monitoring on Safety Factor of Mine Roadway Based on Structural Equation Model, 2012 2nd International Conference on Consumer Electronics, Communications and Networks. 384–386.
    Zadeh, L. A. (1965). Fuzzy Sets, Information and Control, 8, 338–353.
    Zadeh, L. A. (1968). Fuzzy algorithms, Information and Control, 12(2), 94–102.
    Zadeh, L. A. (1973). Outline of a New Approach to The Analysis of Complex Systems and Decision Processes, IEEE Transactions on Systems, Man, and Cybern, 3, 28–44.
    Zadeh, L. A. (1975). The Concept of a Linguistic Variable and its Application to Approximate Reasoning, Information Sciences, 8(1), 199–249; Information Sciences, 8(2), 301–57.
    Zanakis, S. H., and Gupta, S. K. (1985). A Categorical Bibliographic Survey of Goal Programming, OMEGA, 13, 211-222.

    QR CODE