本文選題：模糊多屬性決策　切入點：對偶猶豫模糊集　出處：《西安建筑科技大學》2017年碩士論文

【摘要】：隨著時代發(fā)展,決策過程中蘊含的信息量越來越大,決策問題也越來越復雜,這就使得決策者在對事物做出判斷的時候往往變得猶豫不決.決策結果僅僅依靠決策者經(jīng)驗和直覺得到的時代已經(jīng)成為歷史,采用科學的決策方法對各備選方案進行評價、權衡并選取最優(yōu)方案是亟不可待的.模糊信息條件下多屬性決策中的模糊理論在科技研究、社會生產(chǎn)、生活決策等領域都有廣泛的應用,故模糊信息條件下多屬性決策的出現(xiàn)填補了決策理論研究的空缺.但由于任何事物都是紛繁復雜的具有的模糊性并且人類認知結構也具有不確定性,決策者一般難以對決策信息給出精確的數(shù)值,最初的屬性值形式為三角模糊數(shù)、區(qū)間數(shù)、直覺模糊數(shù)等,現(xiàn)今人們?yōu)榱说玫礁_的決策結果則用區(qū)間三角模糊數(shù)、對偶猶豫模糊數(shù)、區(qū)間值對偶猶豫模糊數(shù)等不同形式的模糊信息給出屬性值.本文對不同屬性下的模糊多屬性決策問題做了如下研究:首先,研究了對偶猶豫模糊集的距離測度和相關系數(shù),并將其應用于屬性權重未給出的模糊信息條件下多屬性決策中.基于對偶猶豫模糊集,給出對偶猶豫模糊集的Hamming距離測度公式和兩個對偶猶豫模糊信息之間相關關系的相關系數(shù),并給出定義和加權相關系數(shù)計算公式,使決策運算更快捷有效.其次,探討區(qū)間三角模糊集的Hamming距離,結合TOPSIS方法對屬性權重部分已知的問題進行決策.由區(qū)間三角模糊數(shù)的定義,給出任意兩個區(qū)間三角模糊集的標準化的Hamming距離,將其與極大偏差法結合求部分已知的權重向量.最后結合經(jīng)典TOPSIS方法計算得到最優(yōu)方案.然后,研究了區(qū)間直覺模糊數(shù)的規(guī)范化方法和由區(qū)間直覺模糊加權幾何平均算子對動態(tài)多屬性決策問題的決策.建立屬性值為區(qū)間直覺模糊數(shù)的規(guī)范化方法,且把區(qū)間直覺模糊加權幾何平均算子推廣到了多階段的情形.最后,研究了區(qū)間值對偶猶豫模糊熵與相似性測度給出了其定義和公式,由此構造了熵權重模型;由距離與相似性測度的關系給出三種區(qū)間值對偶猶豫模糊集的距離公式.由以上給出一種區(qū)間值對偶猶豫模糊集的決策方法.最終給出區(qū)間值對偶猶豫模糊集多屬性決策方法的計算步驟,并驗證了該方法的應用性.
[Abstract]:With the development of the times, the amount of information contained in the decision-making process is increasing, and the decision-making problems are becoming more and more complex. As a result, the decision makers tend to hesitate when they judge things. The era when decisions are based solely on the experience and intuition of the decision makers has become a thing of the past, and scientific methods of decision making are used to evaluate the alternatives. It is very important to weigh and select the optimal scheme. Fuzzy theory in multi-attribute decision making under the condition of fuzzy information has been widely used in the fields of science and technology research, social production, life decision making and so on. Therefore, the emergence of multi-attribute decision making under the condition of fuzzy information fills the gap in the study of decision theory. However, because everything is complicated and fuzzy and human cognitive structure is uncertain, Decision makers generally find it difficult to give accurate values for decision information. The initial attribute values are triangular fuzzy numbers, interval numbers, intuitionistic fuzzy numbers, etc. Nowadays, people use interval triangular fuzzy numbers in order to obtain more accurate decision results. Attribute values are given for different forms of fuzzy information such as dual hesitation fuzzy number, interval value dual hesitation fuzzy number and so on. In this paper, the fuzzy multi-attribute decision making problem under different attributes is studied as follows: first, This paper studies the distance measure and correlation coefficient of dual hesitation fuzzy sets, and applies them to multi-attribute decision making under the condition of fuzzy information not given by attribute weights. The Hamming distance measure formula of dual hesitation fuzzy set and the correlation coefficient between two dual hesitation fuzzy information are given, and the definition and calculation formula of weighted correlation coefficient are given to make the decision operation more efficient. In this paper, the Hamming distance of interval triangular fuzzy sets is discussed, and the problem of known attribute weights is determined by TOPSIS method. Based on the definition of interval triangular fuzzy numbers, the standardized Hamming distance of any two interval triangular fuzzy sets is given. It is combined with the maximum deviation method to obtain the partial known weight vector. Finally, the optimal scheme is obtained by combining the classical TOPSIS method. In this paper, the normalization method of interval intuitionistic fuzzy numbers and the decision of interval intuitionistic fuzzy weighted geometric averaging operators for dynamic multi-attribute decision making problems are studied, and the normalization method of interval intuitionistic fuzzy numbers with attribute values as interval intuitionistic fuzzy numbers is established. The interval intuitionistic fuzzy weighted geometric averaging operator is extended to the multi-stage case. Finally, the definition and formula of interval valued dual hesitation fuzzy entropy and similarity measure are studied, and the entropy weight model is constructed. From the relation between distance and similarity measure, the distance formulas of three interval valued dual hesitation fuzzy sets are given. A decision method for interval valued dual dual hesitation fuzzy sets is given. Finally, the interval valued dual dual hesitation fuzzy sets are given. The calculation steps of the attribute decision method, The application of this method is verified.
【學位授予單位】：西安建筑科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：O159;O225

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