基于模糊数直觉模糊PG算子的多属性决策方法

针对决策信息为三角模糊数直觉模糊数(TFNIFN)且属性间存在相互关联的多属性群决策(MAGDM)问题,提出了一种基于三角模糊数直觉模糊PG(TFNIFPG)算子的决策方法.首先,基于TFNIFN的运算法则和PG(Power Geometric)算子,定义了TFNIFPG算子.然后,研究了该算子的一些性质,建立基于TFNIFPG算子的MAGDM模型,结合排序方法进行决策.最后通过某项目投资算例验证了该算子的有效性与可行性.     

梯形模糊数直觉模糊Bonferroni平均算子及其应用

本文研究决策信息为梯形模糊数直觉模糊数(TFNIFN)且属性间存在相互关联的多属性群决策(MAGDM)问题,提出一种基于梯形模糊数直觉模糊加权Bonferroni平均(TFNIFWBM)算子的决策方法.首先,介绍了TFNIFN的概念和运算法则,基于这些运算法则和Bonferroni平均(Bonferroni mean,BM)算子,定义了梯形模糊数直觉模糊Bonferroni平均算子和TFNIFWBM算子.然后,研究了这些算子的一些性质,建立基于TFNIFWBM算子的多属性群决策模型,结合排序方法进行决策.最后,将该方法应用在MAGDM中,算例结果表明了该方法的有效性与可行性.     

直觉三角模糊数密度算子及其决策应用

首先提出了一种直觉三角模糊数集聚类的方法,然后考虑到属性信息分布的疏密程度,针对属性值为直觉三角模糊数的多属性决策问题提出了直觉三角模糊数密度算子,给出了密度算子与已有几种信息集结算子合成的形式,并研究了直觉三角模糊数密度算子的性质.最后通过一个决策算例说明了直觉三角模糊数密度算子的有效性.     

基于Choquet积分的区间直觉梯形模糊多属性群决策

针对决策信息为区间直觉梯形模糊数(IVITFN)且属性间存在相互关联的多属性群决策问题,提出了基于Choquet积分理论的区间直觉梯形模糊关联平均(IVITFCA)算子.首先,基于IVITFN的运算法则和Choquet积分,定义了IVITFCA算子,并研究了该算子的相关性质.然后,提出了基于IVITFCA算子的多属性群决策方法.最后,通过供应商选择算例证明了所提方法的有效性与可行性.     

权重为直觉模糊数的直觉模糊多属性群决策方法

针对属性权重以直觉模糊数形式给出的直觉模糊多属性群决策问题,提出了一种新的集成算子,首先证明了该算子具有诸如单调性等良好的性质,然后将该算子应用到权重为直觉模糊数的直觉模糊多属性群决策方法中,给出了决策方法的一般步骤,最后用实例说明了该方法的有效性和实用性.     

区间直觉正态模糊数集成算子及其在决策中的应用

研究了区间直觉正态模糊数(IVINFN)决策信息及其集成算子。首先,定义了区间直觉正态模糊数的概念,提出了运算法则;其次,给出了区间直觉正态模糊数诱导有序加权平均(IVINFN-IOWA)算子和区间直觉正态模糊数诱导有序加权几何(IVINFN-IOWGA)算子的概念,探讨了其性质;在此基础上,分别定义了基于均值和标准差的区间直觉正态模糊数的得分函数和精确函数,给出其排序方法。最后,针对属性值为区间直觉正态模糊数且权重已知的多属性决策问题,给出了其决策方法,并进行了实例分析,结果表明该决策方法是有效的。     

基于新型区间直觉三角模糊熵的多属性决策方法

在进行区间直觉模糊多属性决策时,有时属性权重是未知的,针对这一问题,提出一种新型区间直觉三角模糊熵的决策方法.首先,给出该新型区间直觉三角模糊熵定义和相关定理,应用该区间直觉三角模糊熵确定属性的权重.然后,基于逼近理想解排序法(TOPSIS)的思想,采用改进的加权欧几里得距离,进行区间直觉模糊群决策,并给出决策步骤.最后,将该方法应用在供应链选择的群决策问题中,通过算例实验验证了该方法的有效性与可行性.     

基于模糊数直觉模糊集的多属性决策方法

对属性权重信息完全未知且属性值为模糊数直觉模糊数的多属性决策问题进行了研究,定义了模糊数直觉模糊数的得分函数,进而提出了一种基于线性规划模型的模糊数直觉模糊多属性决策方法.最后通过实例对该决策途径的详细过程及有效性进行了说明.     

区间直觉梯形模糊Bonferroni平均算子及在多属性群决策中的应用

针对决策信息为区间直觉梯形模糊数(IVITFN)且属性间存在相互关联的多属性群决策(MAGDM)问题,提出一种基于加权区间直觉梯形模糊Bonferroni平均(WIVITFBM)算子的决策方法.首先,基于IVITFN的运算法则和Bonferroni平均(BM)算子,定义了区间直觉梯形模糊Bonferroni平均(VITFBM)算子和WIVITFBM算子.然后,研究了这些算子的一些性质,建立基于WIVITFBM算子的MAGDM模型,结合排序方法进行决策。最后通过MAGDM算例验证了该算子的有效性与可行性。     

一种基于不完备直觉模糊信息的TOPSIS方法

多属性决策过程中,每个方案的属性值有时体现为由直觉模糊数所刻划的语言变量,通过定义直觉模糊数间的距离,首先提出了基于直觉模糊数的TOPSIS方法;其次,考虑到在实际问题中往往会遇到不完备直觉模糊信息的事实,提出一种将不完备直觉模糊数完备化的方法,并建立了基于不完备直觉模糊信息的TOPSIS方法,同时通过实例说明该方法的有效性以及在多属性决策中的应用.     

Power average operators of trapezoidal intuitionistic fuzzy numbers and application to multi-attribute group decision making

Trapezoidal intuitionistic fuzzy numbers (TrIFNs) is a special intuitionistic fuzzy set on a real number set. TrIFNs are useful to deal with ill-known quantities in decision data and decision making problems themselves. The focus of this paper is on multi-attribute group decision making (MAGDM) problems in which the attribute values are expressed with TrIFNs, which are solved by developing a new decision method based on power average operators of TrIFNs. The new operation laws for TrIFNs are given. From a viewpoint of Hausdorff metric, the Hamming and Euclidean distances between TrIFNs are defined. Hereby the power average operator of real numbers is extended to four kinds of power average operators of TrIFNs, involving the power average operator of TrIFNs, the weighted power average operator of TrIFNs, the power ordered weighted average operator of TrIFNs, and the power hybrid average operator of TrIFNs. In the proposed group decision method, the individual overall evaluation values of alternatives are generated by using the power average operator of TrIFNs. Applying the hybrid average operator of TrIFNs, the individual overall evaluation values of alternatives are then integrated into the collective ones, which are used to rank the alternatives. The example analysis shows the practicality and effectiveness of the proposed method.     

Extension of the TOPSIS method for decision making problems under interval-valued intuitionistic fuzzy environment

TOPSIS is one of the well-known methods for multiple attribute decision making (MADM). In this paper, we extend the TOPSIS method to solve multiple attribute group decision making (MAGDM) problems in interval-valued intuitionistic fuzzy environment in which all the preference information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFNs), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and construct the weighted collective interval-valued intuitionistic fuzzy decision matrix, and then determine the interval-valued intuitionistic positive-ideal solution and interval-valued intuitionistic negative-ideal solution. Based on different distance definitions, we calculate the relative closeness of each alternative to the interval-valued intuitionistic positive-ideal solution and rank the alternatives according to the relative closeness to the interval-valued intuitionistic positive-ideal solution and select the most desirable one(s). Finally, an example is used to illustrate the applicability of the proposed approach.     

Intuitionistic uncertain linguistic powered einstein aggregation operators and their application to multi-attribute group decision making

The intuitionistic uncertain fuzzy linguistic variable can easily expressthe fuzzy information, and the power average (PA) operator is a usefultool which provides more versatility in the information aggregation procedure.At the same time, Einstein operations are a kind of various t-normsand t-conorms families which can be used to perform the corresponding intersectionsand unions of intuitionistic fuzzy sets (IFSs). In this paper, wewill combine the PA operator and Einstein operations to intuitionistic uncertainlinguistic environment, and propose some new PA operators. Firstly,the definition and some basic operations of intuitionistic uncertain linguisticnumber (IULN), power aggregation (PA) operator and Einstein operationsare introduced. Then, we propose intuitionistic uncertain linguistic fuzzypowered Einstein averaging (IULFPEA) operator, intuitionistic uncertain linguisticfuzzy powered Einstein weighted (IULFPEWA) operator, intuitionisticuncertain linguistic fuzzy Einstein geometric (IULFPEG) operator and intuitionisticuncertain linguistic fuzzy Einstein weighted geometric (IULFPEWG)operator, and discuss some properties of them in detail. Furthermore, we developthe decision making methods for multi-attribute group decision making(MAGDM) problems with intuitionistic uncertain linguistic information andgive the detail decision steps. At last, an illustrate example is given to showthe process of decision making and the effectiveness of the proposed method.     

Correlation coefficient of interval-valued intuitionistic fuzzy sets and its application to multiple attribute group decision making problems

In this paper, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFN), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and then we use the obtained attribute weights and the interval-valued intuitionistic fuzzy weighted geometric (IIFWG) operator to fuse the interval-valued intuitionistic fuzzy information in the collective interval-valued intuitionistic fuzzy decision matrix to get the overall interval-valued intuitionistic fuzzy values of alternatives, and then rank the alternatives according to the correlation coefficients between IVIFNs and select the most desirable one(s). Finally, a numerical example is used to illustrate the applicability of the proposed approach.     

一种基于Choquet积分的多属性直觉模糊决策方法

研究了决策者对方案的主观偏好值以及属性值均为直觉模糊数的且属性间存在关联的多属性决策问题.利用Choquet模糊积分作为集结算子,构建了基于属性关联的M OD和SOD模型.通过求解模型获得属性的权重,进而给出了一种新的直觉模糊多属性决策方法.最后通过一个算例说明了该决策方法的有效性和可行性.     

Some geometric aggregation operators based on interval intuitionistic uncertain linguistic variables and their application to group decision making

With respect to multiple attribute group decision making (MAGDM) problems in which both the attribute weights and the expert weights take the form of crisp numbers, and attribute values take the form of interval-valued intuitionistic uncertain linguistic variables, some new group decision making analysis methods are developed. Firstly, some operational laws, expected value and accuracy function of interval-valued intuitionistic uncertain linguistic variables are introduced. Then, an interval-valued intuitionistic uncertain linguistic weighted geometric average (IVIULWGA) operator and an interval-valued intuitionistic uncertain linguistic ordered weighted geometric (IVIULOWG) operator have been developed. Furthermore, some desirable properties of the IVIULWGA operator and the IVIULOWG operator, such as commutativity, idempotency and monotonicity, have been studied, and an interval-valued intuitionistic uncertain linguistic hybrid geometric (IVIULHG) operator which generalizes both the IVIULWGA operator and the IVIULOWG operator, was developed. Based on these operators, an approach to multiple attribute group decision making with interval-valued intuitionistic uncertain linguistic information has been proposed. Finally, an illustrative example is given to verify the developed approaches and to demonstrate their practicality and effectiveness.     

基于交叉影响的IFWGA算子及其在多属性决策中的应用

不同直觉模糊数在信息集结过程中,其隶属度与非隶属度之间可能存在着相互影响.提出了直觉模糊数上的改进的乘法运算和幂运算,重新给出了直觉模糊加权几何平均算子和直觉模糊有序加权几何平均算子的表达式,并研究了他们的一些性质.最后通过实例说明了新的IFWGA集成算子在多属性决策中的应用是可行和有效的.     

基于核的区间直觉模糊信息集成的一类算子及其决策应用

定义了区间数核、区间直觉模糊数核的概念.并以此为基础,提出了区间直觉模糊数表示的模糊信息的几个集成算子:IIFKWA,IIFKWG,IIFKOWA IIFKOWG,IIFKHA,IIFKHG,研究了算子性质.探讨了集成算子在多属性决策中的应用,算例分析表明其具有可行性与有效性.