研究生: |
吳明璇 Wu, Ming-Hsuan |
---|---|
論文名稱: |
發展直覺式二元模糊語意模型於群體決策問題 Developing Intuitionistic 2-Tuple Fuzzy Linguistic Representation Models for Group Decision-Making Problems |
指導教授: |
陳梁軒
Chen, Liang-Hsuan |
學位類別: |
碩士 Master |
系所名稱: |
管理學院 - 工業與資訊管理學系 Department of Industrial and Information Management |
論文出版年: | 2016 |
畢業學年度: | 104 |
語文別: | 中文 |
論文頁數: | 84 |
中文關鍵詞: | 群體決策 、直覺式二元模糊語意模型 、直覺式語意尺度集合 、直覺式三角模糊數 |
外文關鍵詞: | Group decision-making, Intuitionistic 2-tuple fuzzy linguistic representation models, Intuitionistic linguistic term sets (ILTS), Intuitionistic triangular fuzzy numbers |
相關次數: | 點閱:116 下載:0 |
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二元模糊語意模型(2-Tuple Fuzzy Linguistic Representation Models)為一項對語意評估值進行運算、整合,避免資訊流失的決策工具。目前的研究當中,所有語意詞皆以三角模糊數表達。然而,若是在評估階段,專家對於選擇語意詞存在不同的不確定性,原本的三角模糊數將不足以表達專家內在之主觀評估。因此,本研究在群體偏好決策問題中,以加入不確定性的直覺式三角模糊數來表達直覺式語意尺度集合的語意詞,除了有歸屬度函數外,亦包含非歸屬度函數及猶豫資訊,擴大語意詞所能表示的不確定性及猶豫程度。而一般群體決策中,不同領域的專家,皆由同一個語意尺度集合取得語意詞來評定全部方案,可能對某些專家造成評估上的困難。
針對上述問題,本研究建構直覺式二元模糊語意模型,運算、整合專家對各評選方案的語意偏好關係(linguistic preference relations),目的在於考量專家對於語意詞之選擇存在不確定性,且讓各專家可採用不同直覺式語意尺度集合挑選語意偏好值評估,再整合到同一個直覺式基本語意尺度集合。本研究所設定之決策流程包含四階段,第一階段中,允許專家各自使用不同直覺式語意尺度集合評估方案,得到的語意偏好評估值須轉到相同的直覺式基本語意尺度集合(Intuitionistic Basic Linguistic Term Set, IBLTS),而得到一組表達歸屬及非歸屬IBLTS中所有語意詞程度的直覺式模糊集合。在第二階段中,將多個專家轉換後的直覺式模糊集合,運用整合運算子整合,得到表達整體意見的決策矩陣。在第三階段中,將表達整體意見的集體直覺式模糊集合轉換成二元模糊語意值,以表示兩兩方案間偏好值在IBLTS中的語意落點。第四階段會使用選擇函數,決定出最佳方案。本研究期望利用直覺式語意尺度集合,使語意詞能夠表達專家對選擇語意詞之不確定性,以期更完整傳達專家內在之主觀評估。本研究以案例說明求解步驟,並分析整合專家意見之順序不同,對於方案排序之影響。
The 2-tuple fuzzy linguistic representation models are considered to be a decision approach intended to calculate and aggregate linguistic evaluations without the loss of information. In current research, all linguistic terms are represented by triangular fuzzy numbers. However, if experts choose linguistic terms with different degrees of uncertainty, the triangular fuzzy numbers are not enough to represent the internally subjective evaluations of experts. As a result, this thesis uses the intuitionistic triangular fuzzy numbers to represent the linguistic terms in the intuitionistic linguistic term set. The intuitionistic triangular fuzzy numbers are composed of membership function, non-membership function and hesitancy information, expanding the information the linguistic terms contain. In a decision-making problem with multiple experts, the use of one linguistic term set may cause problems for some experts.
To address these problems, this thesis develops the intuitionistic 2-tuple fuzzy linguistic representation models for group decision-making problems. The aim of this thesis is to consider that experts have different levels of uncertainty related to choosing linguistic terms and to allow them to use intuitionistic linguistic term sets with different granularity. The models consist of the following four stages: (1) We allow experts to use different intuitionistic linguistic term sets (ILTS) to obtain the linguistic preference values for each pair of alternatives. All the linguistic preference values are transformed into a specific linguistic term set, called the intuitionistic basic linguistic term set (IBLTS). Each linguistic preference value is expressed by means of an intuitionistic fuzzy set on the IBLTS, . (2) We use an aggregation operator for combining the intuitionistic fuzzy sets on the IBLTS to obtain the collective preference values for each pair of alternatives. (3) In this phase, we transform the intuitionistic fuzzy sets on the IBLTS into linguistic 2-tuple linguistic values over the IBLTS, a numerical value in the IBLTS granularity interval. (4) To facilitate the rank process, this phase uses a choice function to obtain the best alternative. This thesis looks forward to the use of intuitionistic linguistic term sets to express experts’ uncertainty in choosing linguistic terms and to convey more information in the internally subjective evaluations of experts. An example is used to demonstrate each step of our proposal models. Subsequently, the influence of both different order in which expert opinions are aggregated and different degrees of uncertainty among experts on the ranking results is analyzed.
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