2-tuple语言直觉模糊多属性决策方法研究
发布时间：2018-07-25 17:50
【摘要】：多属性决策主要研究有限个决策方案关于离散评估值的决策问题,一般是指多个专家利用现有的决策信息,通过共同决策分析,对可供选择的备选方案进行排序或择优。由于实际决策问题的复杂性、不精确性以及人类思维的含糊性,决策者很难给出精确的评估值,因此人们提出许多不确定多属性决策方法。模糊多属性决策是经典多属性决策在理论上的拓展和延伸,是不确定多属性决策的一个重要组成部分,已广泛应用于资源管理、采购与外包、供应商选择、技术选择等各个领域。作为模糊集的推广,直觉模糊集从“属于”、“不属于”和“犹豫”三个方面对不确定问题进行评估,能更加深刻地描述客观对象的模糊本质。对定性属性,决策者对于“属于”、“不属于”很难给出精确值,通常是使用粗糙或不精确的语言给出评价信息。作为语言表示方法中的一种,2-tuple语言直觉模糊集(2TLIFSs)结合了2-tuple语言值和直觉模糊数的优点,由语言值隶属度和语言值非隶属度构成。本文主要针对2-tuple语言直觉模糊集多属性群决策问题进行探讨,主要内容如下:(1)结合2-tuple语言直觉模糊集与语言幂均(LPA)算子,提出语言直觉模糊幂均(LIFPA)算子并将之应用于语言直觉模糊环境下决策者权重已知的多属性群决策。为了得到LIFPA算子中两个2-tuple语言直觉模糊集的支持度,定义了2-tuple语言直觉模糊集之间的海明距离。并证明了该算子具有交换性、有界性和幂等性。(2)基于LIFPA算子和OWA算子,提出语言直觉模糊有序加权幂均(LIFPOWA)算子并将之应用于语言直觉模糊环境下决策者权重未知的多属性群决策。证明了该算子具有交换性、有界性和幂等性。(3)提出2-tuple语言直觉模糊理想点法(TOPSIS)。为了得到方案与正负理想解的距离,定义了2-tuple语言直觉模糊决策矩阵以及两个2-tuple语言直觉模糊矩阵之间的海明距离。并与语言偏好信息下的TOPSIS方法进行实例对比分析。(4)提出基于多粒度语言直觉模糊集的TOPSIS决策方法。为了能有效处理多粒度语言评价信息,给出多粒度语言直觉模糊集的转换方法。并与基于不确定语言变量的TOPSIS法进行实例对比分析。
[Abstract]:Multi-attribute decision making is mainly concerned with the decision problem of discrete evaluation values for finite decision schemes. It is generally referred to that multiple experts make use of the existing decision information and analyze the common decision to sort or select the alternatives available for decision making. Due to the complexity, imprecision and ambiguity of human thinking, it is difficult for decision makers to give accurate evaluation values, so many uncertain multi-attribute decision making methods are proposed. Fuzzy multi-attribute decision making is an extension and extension of classical multi-attribute decision making in theory. It is an important part of uncertain multi-attribute decision making. It has been widely used in resource management, procurement and outsourcing, supplier selection. Technical selection and other fields. As a generalization of fuzzy sets, intuitionistic fuzzy sets evaluate uncertainty from three aspects: "belonging", "not belonging" and "hesitancy", which can describe the fuzzy essence of objective objects more deeply. For qualitative attributes, it is difficult for decision-makers to give accurate values for "belong" and "not belong", usually using rough or imprecise language to give evaluation information. As a linguistic representation method, the 2-tuple intuitionistic fuzzy set (2TLIFSs) combines the advantages of 2-tuple and intuitionistic fuzzy numbers, and consists of linguistic value membership degree and language value non-membership degree. This paper mainly discusses the problem of 2-tuple language intuitionistic fuzzy set multi-attribute group decision making. The main contents are as follows: (1) combined with 2-tuple language intuitionistic fuzzy set and (LPA) operator, A linguistic intuitionistic fuzzy power-average (LIFPA) operator is proposed and applied to the multi-attribute group decision making in which the weight of the decision-maker is known in the linguistic intuitionistic fuzzy environment. In order to obtain the support degree of two 2-tuple intuitionistic fuzzy sets in LIFPA operator, the hamming distance between 2-tuple intuitionistic fuzzy sets is defined. It is proved that the operator is commutative, bounded and idempotent. (2) based on LIFPA operator and OWA operator, This paper presents a linguistic intuitionistic fuzzy ordered weighted equal-power (LIFPOWA) operator and applies it to multi-attribute group decision making with unknown weights for decision makers in linguistic intuitionistic fuzzy environments. It is proved that the operator has commutativity, boundedness and idempotent. (3) the intuitionistic fuzzy ideal point method (TOPSIS). For 2-tuple language is proposed. In order to obtain the distance between the positive and negative ideal solutions, the 2-tuple language intuitionistic fuzzy decision matrix and the hamming distance between two 2-tuple language intuitionistic fuzzy matrices are defined. The method is compared with the TOPSIS method based on linguistic preference information. (4) the TOPSIS decision making method based on multi-granularity language intuitionistic fuzzy sets is proposed. In order to deal with the evaluation information of multi-granularity language effectively, the transformation method of intuitionistic fuzzy set of multi-granularity language is presented. And compared with the TOPSIS method based on uncertain language variables.
【学位授予单位】：西华大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：O159;O225
本文编号：2144575
[Abstract]:Multi-attribute decision making is mainly concerned with the decision problem of discrete evaluation values for finite decision schemes. It is generally referred to that multiple experts make use of the existing decision information and analyze the common decision to sort or select the alternatives available for decision making. Due to the complexity, imprecision and ambiguity of human thinking, it is difficult for decision makers to give accurate evaluation values, so many uncertain multi-attribute decision making methods are proposed. Fuzzy multi-attribute decision making is an extension and extension of classical multi-attribute decision making in theory. It is an important part of uncertain multi-attribute decision making. It has been widely used in resource management, procurement and outsourcing, supplier selection. Technical selection and other fields. As a generalization of fuzzy sets, intuitionistic fuzzy sets evaluate uncertainty from three aspects: "belonging", "not belonging" and "hesitancy", which can describe the fuzzy essence of objective objects more deeply. For qualitative attributes, it is difficult for decision-makers to give accurate values for "belong" and "not belong", usually using rough or imprecise language to give evaluation information. As a linguistic representation method, the 2-tuple intuitionistic fuzzy set (2TLIFSs) combines the advantages of 2-tuple and intuitionistic fuzzy numbers, and consists of linguistic value membership degree and language value non-membership degree. This paper mainly discusses the problem of 2-tuple language intuitionistic fuzzy set multi-attribute group decision making. The main contents are as follows: (1) combined with 2-tuple language intuitionistic fuzzy set and (LPA) operator, A linguistic intuitionistic fuzzy power-average (LIFPA) operator is proposed and applied to the multi-attribute group decision making in which the weight of the decision-maker is known in the linguistic intuitionistic fuzzy environment. In order to obtain the support degree of two 2-tuple intuitionistic fuzzy sets in LIFPA operator, the hamming distance between 2-tuple intuitionistic fuzzy sets is defined. It is proved that the operator is commutative, bounded and idempotent. (2) based on LIFPA operator and OWA operator, This paper presents a linguistic intuitionistic fuzzy ordered weighted equal-power (LIFPOWA) operator and applies it to multi-attribute group decision making with unknown weights for decision makers in linguistic intuitionistic fuzzy environments. It is proved that the operator has commutativity, boundedness and idempotent. (3) the intuitionistic fuzzy ideal point method (TOPSIS). For 2-tuple language is proposed. In order to obtain the distance between the positive and negative ideal solutions, the 2-tuple language intuitionistic fuzzy decision matrix and the hamming distance between two 2-tuple language intuitionistic fuzzy matrices are defined. The method is compared with the TOPSIS method based on linguistic preference information. (4) the TOPSIS decision making method based on multi-granularity language intuitionistic fuzzy sets is proposed. In order to deal with the evaluation information of multi-granularity language effectively, the transformation method of intuitionistic fuzzy set of multi-granularity language is presented. And compared with the TOPSIS method based on uncertain language variables.
【学位授予单位】：西华大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：O159;O225
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