跳到主要內容

臺灣博碩士論文加值系統

(18.97.9.172) 您好!臺灣時間:2025/02/11 12:52
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:林文遠
研究生(外文):Lin, Wen-Yuan
論文名稱:建構一具有不準確多屬性特質之群體決策模式
論文名稱(外文):Implementation of a group decision model with imprecise multiple attributes
指導教授:時序時時序時引用關係
指導教授(外文):Shih,Hsu-Shih
學位類別:碩士
校院名稱:義守大學
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:2000
畢業學年度:88
語文別:中文
論文頁數:119
中文關鍵詞:群體決策多屬性決策共識促進權重名義群體技術TOPSIS群體決策支援系統不確定範圍
外文關鍵詞:group decision makingmultiple attributes decision makingconsensus facilitationweightNGTTOPSISgroup decision support systemimprecise range
相關次數:
  • 被引用被引用:11
  • 點閱點閱:652
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:3
摘 要
本研究旨在探討藉由群體決策(group decision making) 技術改進善多屬性決策(multiple attributes decision making) 方法;並以客觀指標明確顯示群體決策品質之改善;再據以建構一具模糊多屬性特徵的群體決策模式。
鑑於以往多屬性決策技術多著重於決策過程中之計算與評比,如評估準則之訂定、準則權重(weight) 之給予、及各方案(alternative) 在各準則下之評分等,而其中經由群體(專家)共識(consensus) 之內涵往往因較難表達而被忽視,造成決策資訊不完整,且客觀意見亦難以反映,故其決策輔助(decision aid)之品質不佳。因之,本研究引用名義群體技術 (NGT, Delbecq et al., 1975),來協助確定屬性集合、屬性權重、及方案篩選,再合併多屬性決策 TOPSIS (Hwang & Yoon, 1981) 之既有程序而成為一整體的決策輔助工具。其次,在群體決策執行步驟中相關協調與共識之促進(facilitation) 均以適切的具體指標顯示,因而協調的改善與共識的達成,得以確切掌握。
在多準則決策部份,以往 TOPSIS 意見(語意)表達之不確定範圍(imprecise range) 與標準化方法於實務上之缺失,亦有具體改良。此外,有關決策資訊不確定性係藉模糊隸屬函數(membership function) 表達,在權重及方案評估方面均獲改善。再者,前述多項研究結果經整合為一詳實可行之流程,並足以建構一具模糊多屬性特徵的群體決策支援系統(group decision support system)。最後,所發展的模式應用於一戰機採購案例,執行所建議步驟,模式之可行性亦得驗證。
關鍵字:群體決策(group decision making),多屬性決策(multiple attributes decision making),共識(consensus),共識促進(consensus facilitation),權重(weight),方案(alternative),名義群體技術(NGT),TOPSIS,群體決策支援系統(group decision support system),不確定範圍(imprecise range),隸屬函數(membership function)。
Abstract
The study aims to enhance a multiple attributes decision making (MADM) technique, TOPSIS, through combining a group decision making (GDM), NGT, process. Within the study, the quality improvement of GDM can be explicitly represented by introducing measure indices, and a group decision support system (GDSS) with fuzzy multiple attributes is established.
Most of the MADM techniques were focused on calculation and value evaluation, such as the setting standard for evaluation criteria, arranging the weight for each criterion, and grading each alternative under each criterion. Since the decision making process was over-simplified in consideration, some steps required a consensus among a group or a team are neglected, and the decision information is not sufficient as well. Consequently, the quality of decision making might not be as expected, and the suggested process might be impractical for real world applications. To overcome the mentioned drawbacks, this research is to propose an integrated procedure, constructing a attribute set and attributes weight and selecting feasible alternatives by NGT. In addition, the coordination and consensus facilitation have been clearly defined, and we can make an improvement based on the suggested index values for GDM.
Unlike other proposals, the imprecise range of linguistic variables and the standardization of aggregation in TOPSIS will be modified. In addition, our model can accommodate evaluations of multiple persons so that it is a real multiple inputs for GDM. Moreover, all vague information is represented by fuzzy membership function and weight and alternative evaluation will be improved as well. All above improvements are integrated into a GDSS with fuzzy MADM. In the final part, the proposed model has been verified by a project of fighter plane acquisition.
Keywords: group decision making, multiple attributes decision making, consensus, consensus facilitation, weight, alternative, NGT, TOPSIS, group decision support system, imprecise range, membership function.
目 錄
誌謝i
中文摘要ii
英文摘要iii
目錄iv
表目錄vi
圖目錄vii
第一章 緒論1
第一節 研究動機2
第二節 研究目的3
第三節 研究方法3
第四節 研究範圍與限制5
第五節 預期貢獻5
第二章 文獻探討7
第一節 決策問題7
壹、問題形成7
貳、決策程序8
第二節 多屬性決策9
壹、概要9
貳、技術10
第三節 群體決策15
壹、概要15
貳、技術18
第四節 模糊理論與應用22
第三章 NGT與TOPSIS 模式之改良25
第一節 改良NGT模式25
壹、數值分析支援NGT步驟研究26
第二節 改良模糊TOPSIS模式34
壹、TOPSIS之綜合比較34
貳、模糊TOPSIS之研究36
參、案例說明42
目 錄(續)
第四章 建構一具有不準確多屬性特質之群體決策模式48
第一節 模式發展概念與流程48
第二節 不準確多屬性特質之群體決策模式建構51
第五章 實證研究66
第一節 案例簡介66
第二節 案例運作流程67
第三節 決策建議之模擬分析87
第四節 案例比較90
第六章 結論與建議91
第一節 研究結論與建議91
壹、研究結論91
貳、研究建議92
參考文獻93
中文部分93
英文部分93
附錄97
附錄A 以往TOPSIS發展與分析97
附錄B TOPSIS 實例演算108
附錄C AHP及ELECTRE方法步驟114
附錄D 名義群體技術步驟117
附錄E 專家意見偏向與強度模擬分析119
表目錄
表2.1 群體決策之優缺點17
表2.2 名義團體技術的優缺點21
表2.3 評估群體決策技術的效果21
表2.4 模糊多屬性決策方法22
表3.1 專家意見表達之強度意義30
表3.2 TOPSIS基本步驟與對映符號35
表3.3 TOPSIS模式發展之綜合比較36
表3.4 相似度量方法比較41
表3.5 待選戰鬥機之屬性資訊42
表3.6 TOPSIS及修正方法比較47
表5.1 待選戰鬥機之屬性資訊66
表5.2 屬性項目之得票數及總評比分69
表5.3 個別專家之評估屬性權重評估71
表5.4 兩兩專家平均意見偏向集中度指標72
表5.5 專家間偏向集中度之聚類分析73
表5.6 意見分歧之關鍵屬性分析73
表5.7 意見偏向修正後之個別專家評估屬性權重評估74
表5.8 修正偏向後之兩兩專家意見偏向集中度指標與整體平均指標75
表5.9 專家共識強度分析76
表5.10 共識強度修正後之個別專家評估屬性權重評估76
表5.11 共識強度修正後之意見偏向集中度指標值77
表5.12 共識強度修正後之指標值78
表5.13 個別專家屬性權重值彙整78
表5.14 個別專家之模糊決策矩陣79
表5.15 個別專家標準化決策矩陣80
表5.16 個別專家加權標準化決策矩陣81
表5.17 個別專家之模糊正負理想解83
表5.18 個別專家之模糊分離度量83
表5.19 個別專家之模糊正理想解之相對接近度85
表5.20 個別專家之方案優劣排序85
表5.21 Borda函數矩陣86
表5.22 各方案之群體模糊評估值彙整86
表5.23 方案整體評價值 (λ=1)87
表5.24 方案整體評價值 (λ=0.7)88
表5.25 方案整體評價值 (λ=0.5)88
表目錄(續)
表5.26 方案整體評價值 (λ=0.2)89
表5.27方案整體評價值 (λ=0.0)89
表5.28 決策評選方法比較90
圖目錄
圖1.1 研究流程4
圖2.1 變革的力量:環境、組織與管理者8
圖2.2 決策與問題解決關係圖9
圖2.3 多屬性決策方法之分類10
圖2.4 模糊數 23
圖3.1 專家表達之二維權重向量29
圖3.2 專家意見表達內涵30
圖3.3 促進群體共識步驟(NGT)31
圖3.4 兩三角模糊數相乘積示意圖39
圖3.5 與 及 與 距離40
圖3.6 與 距離40
圖3.7 兩模糊數相似度量圖41
圖3.8模糊相似度量之資訊損失42
圖4.1 群體決策評選流程對應決策制定程序49
圖4.2 群體決策評選流程對應新模式之步驟50
圖4.3 不準確多屬性特質之群體決策模式52
圖4.4 群體決策階段步驟之技術基礎57
圖5.1 意見分歧之關鍵屬性分析圖73
圖5.2 方案整體評價值 (λ=1)87
圖5.3 方案整體評價值 (λ=0.7)88
圖5.4 方案整體評價值 (λ=0.5)88
圖5.5 方案整體評價值 (λ=0.2)89
圖5.6 方案整體評價值 (λ=0.0)89
參考文獻
一、中文部分:
王東琪 (民87),航空站營運績效評估之研究─以亞太地區國際機場為例,國立成功大學交通管理研究所碩士論文。
王政彥 (民80),團體式教育決策參與之研究。國立政治大學教育研究所博士論文。
朱斌妤 (民84),組織決策理論與科技觀,第六屆 國際資訊管理學術研討會論文集,539-546。
周君銓譯 (民88),MBA研修讀本,台北:遠流。譯自 日本Globis株式會社(1995)。
林建煌譯 (民88),現代管理學,台北:華泰。譯自Robbins, S. P. & D. A. De Cenzo(1998)。
唐麗英 (民87),台灣筆記型電腦產品整體品質標竿學習流程之構建及分析,國立交通大學工業工程與管理研究所碩士論文。
徐村和 (民87),模糊德菲層級分析法,模糊系統學刊,第四卷 第一期,59-72。
張有恆與徐村和 (民82),模糊度量AHP法─交通運輸計畫評估新模式,中華民國第一屆Fuzzy理論與應用研討會,365-371。
許錫美與陳振東 (民83),多準則之模糊層級模糊權重分析模式,中華民國工業工程學刊,11,129-136。
陳振東 (民84),研究發發展計劃評選之模糊多準則群體決策模式構建,國立交通大學工業工程研究所博士論文。
陳振東與許鍚美 (民82),模糊TOPSIS模式之研究,中國工業工程學會論文集,348-354。
彭真悌 (民87),國內航空公司競爭力之研究─多準則評估方法之比較分析。國立成功大學交通管理研究所碩士論文。
曾國雄、陳君杰及鄧金地 (民86),適合台灣地區電動機車電池之評選─模糊多屬性決策之應用,中國工業工程期刊,14,319-331。
曾國雄與王榮祖 (民83),公車系統績效評估之研究─AHP法與FMADM之應用,中山管理評論,2,1-17。
曾國雄與王榮祖 (民83),公車系統績效評估之研究─AHP法與FMADM之應用,中山管理評論,第二卷 第二期,1-17。
二、英文部分
Bardossy, A., L. Duckstein and I. Bogardi (1993), Combination of fuzzy numbers representing expert opinions, Fuzzy Sets and Systems, 57, 173-181.
Bellman, R.E. and L.A. Zadeh (1970), Decision-making in a fuzzy environment. Management Science, 17, 141-164.
Belton, V. and A.E. Gear (1983), On a shortcoming of Saaty''s method of analytic hierarchies, Omega, 11, 227-230.
Bovee et al. (1993), Management,McGraw-Hill.
Buckley J.J.(1984), The multiple judge, multiple criteria ranking problem: a fuzzy set approach , Fuzzy Sets and Systems, 13, 25-37.
Buckley J.J.(1985), Fuzzy hierarchical analysis, Fuzzy Sets and Systems, 17, 233-247.
Chang, P.T. and E.S. Lee (1994), The estimation of normalized fuzzy weights, Computers and Mathematics with Applications 29, 21-42.
Chen, S.J. and C.L. Hwang (1992), Fuzzy Multiple Attribute Decision Making: methods and applications, Springer-Verlag, Berlin.
Chen, S.M. (1988), A new approach to handling fuzzy decisionmaking problems, IEEE Transactions on Systems, Man,and Cybernetics, 18(6), 1012-1016.
Coombs, C.H. (1967), Inconsistency of preferences: a test of unfolding theory, in B.M. Fass (ed.), Decision Making, Penguin Books, Middlesex, England, 319-333.
Delbecq, A.L., A.H. Van de Ven, and D.H. Gustafson (1975), , Scott, Goresman and Company, Glenview, Illinois.
Deng, H., C.H. Yeh, and R.J. Willis (2000), Inter-company comparision using modified TOPSIS with obhective weights, Computers & Operations Research, 27, 963-973.
Dimitrov,V. (1983), Group choice under fuzzy information. Fuzzy Sets and Systems, 9, 25-39.
Feng,Y. (1995), Application of TOPSIS in investment decision making of oil-field development. Journal of Xi’an Petroleum Institute, 10, 64.
Fisher, B.A. (1981), Small group decision making, 2th ed., McGraw-Hall, U.S.A.
Forsyth, O.R. (1990), Group dynamics, 2th ed.,.Pacific Grove,Ca.: Brooks/Cole Publishing Company.
Golden, B.L., E.A. Wasil, and P.T. Harker (eds.) (1989), The Analytic Hierarchy Process. Springer-Verlag, Berlin.
Gray, J.L. and F. Starke (1984), Organizational behavior: concepts and applications, Columbus, Ohio: Charles E. Merrill Publishing Company.
Han,Y. (1995), Application of TOPSIS to measuring the international market competitive pattern. Journal of University of Electronic Science and Technology of China, 24, 210.
Harrison, E.F. (1975), The Managerial Decision-Making Process, Houghton Mifflin, Boston.
Hsu, H.M. and C.T. Chen (1996), Aggregation of fuzzy opinions, under group decision marking, Fuzzy Sets and Systems, 79(3), 279-285.
Huber, G.P. and R.R. McDaniel (1986), The decision-making paradigm of organization design, Management Science, 32, 527-589.
Huber,G.P. (1980), Managerial decision making, Glenview, Il.:Scott, Foreman and Company.
Hwang, C.L. and K. Yoon (1981), Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag, Berlin.
Hwang, C.L. and M.J. Lin (1987), Group Decision Making under Multiple Criteria. Springer-Verlag, Berlin.
Ivancevich, J.M. and M.T. Matteson (1981), Organizational behavior & management, Plano, Texas: Business Publications.
Klir,G.J.and B. Yuan, (1995), fuzzy sets and fuzzy logic theory and applications, Prentice Hall, New Jersey.
Lai, Y.J., T.Y. Liu, and C.L. Hwang (1994), TOPSIS for MODM. European J. of Operational Research, 76, 486-500.
Lee, E.S. and R.J. Li (1988), Comparison of fuzzy numbers based on the probability measure of fuzzy events, Computer and mathematics with applications, 15, 887-896.
Liu, X. (1992), Entropy, distance measure and similarity measure of fuzzy sets and their relations, 52, pp.305-318.
Lootsma, F.A. (1990), The French and the American School in Multi-criteria Decision Making. Recherche operationnelle, 24(3), 263-285.
Mon, D.L., C.H. Cheng, and J.C. Lin (1994), Evaluation weapon system using fuzzy analytic hierarchy process based on entropy weight, Fuzzy Sets and Systems, 62, 127-134.
Murnighan J.K. (1981), Group decision making: what strategies should you use? Management Review, 70, 55-62.
Negi, D.S. (1989), Fuzzy analysis and optimization, Unpublished PhD Thesis, Department of Industrial Engineering, Kansas State University.
Ngwenyama, O.K., N. Bryson and A. Mobolurin (1996), Supporting facilitation in group support systems: techniques of analyzing consensus relevant data, Decision Support Systems, 16, 155-168.
Nojiri, H. (1980), On the fuzzy team decision in a change environment, Fuzzy Sets and Systems, 3, 137-150.
Parkan, C. and W. Minglu (1996), Selection of a manufacturing process with multiple benefit attributes, IEEE International Engineering Management Conference , 18-20, 447-452.
Patteon, B.R. and K.Giffin. (1978), Decision-making group interaction, 2nd ed., Happer & Row, New York.
Ribeiro, R.A. (1996), Fuzzy multiple attribute decision making: a review and new preference elicitation techniques, Fuzzy Sets and Systems, 78, 155-181
Roy, B. (1990), The outranking approach and the foundations of ELECTRE methods. Theory and Decision, 31(1), 49-73.
Roy, B. and J.C. Hugonnard (1982), Ranking of suburban line extension projects on the Paris metro system by a multicriteria method, Transportation Research - A, 16A(4), 301-312.
Roy, B. and P. Vincke (1981), Multicriteria analysis: survey and new directions, European J. of Operational Research, 8, 207-218.
Roy, B., M. Present and D. Silhol (1986), A programming method for determining which Paris metro stations should be renovated, European J. of Operational Research, 24, 318-334.
Saaty (1990), The analytic hierarchy process, RWS Publications, Pittsburgh,2nd ed.
Saaty, T.L. and L.G. Vargas (1994), Decision Making in Economic, Political, Social and Technological Environment: The Analytic Hierarchy Process, RWS Publications, Pittsburgh.
Sage, A.P. (1981), Behavioral and organizational considerations in the design of information systems and process for planning and decision support, IEEE Transactions on Systems, Man, and Cybernetics, SMC-11,
Stelios H. Z., Nicole, A. S., Wishart, N. and Sandipa D. (1998), Multi-attribute decision making: a simulation comparison of select methods. European J. of Operational Research, 107, 507-529.
Ulschak, F.L., L. Nathanson, and G.P. Gillan (1981), Small Group Problem Solving─ an aid to organizational effectiveness, Addison-Wesley, Reading, MA
VanGundy, A.B. (1981), Techniques of structured problem solving, New York: Van Nostrand Reinhold Company.
Watson, S.R. and A.N.S. Freeling (1982), Assessing Attribute Weights, Omega, 10, 582-583.
Watson, S.R. and A.N.S. Freeling (1982), Comment on: assessing attribute weights by ratio, Omega, 11, 13.
Xu, R. and X. Zhai (1992), Extensions of the analytic hierarchy process in fuzzy environment, Fuzzy Sets and Systems, 52, 251-257.
Zadeh, L.A. (1965), Fuzzy sets, Information and Control , 8, 338-353.
Zahedi, F. (1986), The analytic hierarchy process─a survey of the method and its applications, Interfaces, 16, 91-116.
Zeleny, M.(1974) , A concept of compromise solutions and the method of the displaced ideal, Computers and operations research, 1, 479-496.
Zimmermann, H.J. (1978), Fuzzy programming and Linear Programming with several objective functions, Fuzzy Sets and Systems, 1, 45-55.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top