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中文論文名稱 模糊評價系統應用在服務品質及生產批量之研究
英文論文名稱 SOME APPLICATIONS OF FUZZY EVALUATION SYSTEM FOR SERVICE QUALITY AND PRODUCT LOT-SIZING
校院名稱 淡江大學
系所名稱(中) 管理科學研究所博士班
系所名稱(英) Graduate Institute of Management Science
學年度 94
學期 1
出版年 95
研究生中文姓名 黃添財
研究生英文姓名 Tien-Tsai Huang
學號 889560032
學位類別 博士
語文別 英文
口試日期 2006-01-06
論文頁數 91頁
口試委員 指導教授-黃文濤
指導教授-楊維楨
委員-姚景星
委員-周青松
委員-江哲賢
委員-張揖平
委員-黃文濤
委員-張紘炬
委員-歐陽良裕
中文關鍵字 模糊評價  服務品質  生產批量  區間估計  三角模糊數 
英文關鍵字 Fuzzy Evaluation  Service Quality  Product Lot-sizing  Interval Estimation  Triangular Fuzzy Number 
學科別分類
中文摘要 許多學者已經利用統計方法進行服務品質的評估研究,然而面對包含語意變數的問題時,統計方法應用在此類服務品質的評估時有其困難。因此,我們引進模糊評價系統作為處理此類問題的方法。在生產批量方面,許多文獻均將彈性與生產批量模式中的三個變數:單位時間的平均需求、相對準備時間、單位生產成本,視為固定單一數值以求取最佳解。然而,在實際的生產計畫期間,這些變數會因為未來的不確定性及需求的變動而有些少許的波動。因此,應用模糊評價系統以求解此類問題比較能夠和實際情況相吻合。
本論文有三個相關連的目標:第一,建立模糊評價系統以處理服務品質評估的問題。第二,使用新的模糊區間方法以建立模糊總成本函數,並進而求取彈性與生產批量模式的最佳解。第三,比較使用模糊評價系統與普通未模糊化方法計算結果的差異。本論文包含五章:第一章簡介本論文的研究動機及架構。第二章建構可應用在服務品質評估的模糊評價系統。第三章則提出另一種模糊評價系統,同樣可應用在評估服務品質。在第四章中,考慮變數的不確定性,因此,使用新的模糊區間方法以建立模糊總成本函數,並求取模式的最佳解。在本章中,將參數經由統計方法轉換為區間,再由這些區間導出總成本函數的區間,並進而形成三角模糊數,最後則利用帶符號距離法及重心法分別求出模糊觀點下的最佳解。此方法有別於以往將函數內參數模糊化的方式。最後一章則為結論,主要是針對各章的內容加以比較並總結一些重要的觀點及提出未來的研究方向。
英文摘要 There are a lot of literatures investigating the problem of the evaluation of service quality by applying the statistical method. However, because of the problems that consist of linguistic variables, the statistical method becomes no more efficient for evaluating service quality; the fuzzy evaluation system is therefore introduced to deal with these problems. Many literatures considered the average demand of per unit time, relative duration of setup, and unit cost of production as fixed values in flexibility and product variety in lot-sizing model. However, in reality, these variables involve uncertainty due to the nature of future production processes and fluctuations in demand. Therefore, it is a good alternative way to apply the fuzzy evaluation system to consider the problems.
This dissertation has three folds of objectives that are correlated: Firstly, it establishes fuzzy evaluation system to handle the assessment of service quality. Secondly, this study formulates a fuzzy total cost function by using a new interval fuzzification method for solving the product lot-sizing problem. And thirdly, it compares the results of fuzzification method among the crisp and the statistical method. This dissertation comprises of five chapters. In chapter 1, an introduction about the study is given. Chapter 2 presents the fuzzy evaluation system applying on assessment service quality. While in chapter 3, another fuzzy evaluation system applying on evaluating service quality is proposed. It proposes the two-stage evaluation structure which differs from that of chapter 2. In chapter 4, a new fuzzification method for solving the product lot-sizing problems is given. Furthermore, an interval fuzzification method which totally differs from the parameter fuzzification method is introduced. In the last chapter, some comparisons among the differences of fuzzification methods given in chapters 2–4 are made and some essential conclusions are also given.
論文目次 CONTENTS
LIST OF TABLES........................................ III
LIST OF FIGURES............................................... IV
CHAPTER 1. INTRODUCTION.......................................... 1
1.1 Motivation................................... 1
1.2 Fuzzy Set Theory................................................ 2
1.3 Dissertation Overview.............................................. 3
CHAPTER 2. FUZZY EVALUATION OF SERVICE QUALITY........ 5
2.1 Literature Review............................ 5
2.2 Preliminaries................................ 7
2.3 Methodology.................................. 16
2.4 Numerical Example............................ 22
2.5 Summary...................................... 25
CHAPTER 3. A MEASURE OF SERVICE QUALITY OF HOTEL...... 27
3.1 Evaluation Model............................. 28
3.1.1 Evaluation Factors of Service Quality of Hotel................................................. 28
3.1.2 Fuzzy Evaluation Procedure...................28
3.2 Numerical Example............................ 36
3.3 Discussion and Summary....................... 39
CHAPTER 4. FUZZY FLEXIBILITY AND PRODUCT VARIETY IN
LOT-SIZING................................... 45
4.1 Introduction................................. 45
4.2 Fuzzy Flexibility and Product Variety in Lot-sizing................................................ 47
4.2.1 Crisp Case................................... 47
4.2.2 Fuzzy Problem and Optimal Solution without Fuzzification of Crisp Total Cost Function............ 49
4.2.2.1 Defuzzification of Fuzzy Total Cost by Using Signed Distance....................................... 51
4.2.2.2 Defuzzification of Fuzzy Total Cost by Using Centroid...............................................56
4.3 Numerical Examples........................... 58
4.4 Discussion................................... 64
4.4.1 The Comparisons between Optimal Solutions by Using Signed Distance for Defuzzification with That of Defuzzification by Using Centroid..................... 64
4.4.2 The Problem (in Eqs. (4.8)–(4.9)) of Crisp Case Is a Special Case of Theorems 4.1, 4.2 and Theorems 4.3, 4.4....................................................65
4.4.3 Fuzzification of Fixed Cost.................. 66
4.5 Summary...................................... 66
4.5.1 The First Step of Fuzzification.............. 66
4.5.2 The Second Step of Fuzzification............. 67
4.5.3 The Defuzzification in Third Step of Fuzzification......................................... 68
CHAPTER 5. CONCLUSIONS AND FUTURE WORK................ 70
5.1 Conclusions....................................... 70
5.1.1 The Fuzzification Problems of Chapters 2 and 3..................................................... 70
5.1.2 The Fuzzification Problems of Chapter 4...... 74
5.2 Future Work....................................... 78
REFERENCES............................................ 80
APPENDIX.............................................. 85

LIST OF TABLES
Table 2.1 Linguistic Terms Correspond to Triangular Fuzzy Numbers................................................18
Table 2.2 The Assessment Results of Relative Importance of All Evaluation Factors from m Customers............... 19
Table 2.3 The Assessment Results of Relative Importance of All Evaluation Factors from 1000 Customers............ 23
Table 2.4 The Relative Weight of Each Evaluation Factor ..............................................24
Table 2.5 The Statistical Analysis of Rating the Score of Evaluation Factor..................................... 25
Table 2.6 The Aggregate Triangular Fuzzy Number of Evaluation Point and the Aggregate Evaluation Point in the Fuzzy Sense.......................................... 26
Table 3.1 Evaluation Factors of Hotel’s Service Quality ............................................ 30
Table 3.2 The Frequency of Assessment of Relative Importance of Evaluation Factors from 1000 Customers.. 38
Table 3.3 The Mean and Variance of Evaluation Factors from 1000 Customers....................................... 39
Table 3.4 The Related Quantifier of Point of Evaluation Factors.............................................. 40
Table 4.1(a) Illustration of Theorem 4.2 and Theorem 4.4 of Example 4.1.......................................... 60
Table 4.2(a) Illustration of Theorem 4.2 and Theorem 4.4 of Example 4.2.......................................... 61
Table 4.3(a) Illustration of Theorem 4.2 and Theorem 4.4 of Example 4.3........................................... 62
Table 4.1(b) The Relative Percentages for Table 4.1(a) 63
Table 4.2(b) The Relative Percentages for Table 4.2(a) 63
Table 4.3(b) The Relative Percentages for Table 4.3(a) 63

LIST OF FIGURES
Figure 2.1 Case 1.................................... 15
Figure 2.2 Case 2.................................... 15
Figure 2.3 Triangular Fuzzy Number L1, L2,...Ln...... 16
Figure 2.4 Fuzzy Numbers of q........................ 18
Figure 2.5 Fuzzy Numbers of VL, L, M, H, and VH...... 18
Figure 3.1 Statistical Data according to yij is skew to the Right................................................ 41
Figure 3.2 Statistical Data according to yij is skew to the Left................................................. 42
Figure 4.1 Change of L ............................... 56
Figure A1. Sets of L and U ........................... 86
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