基于直觉不确定语言评价的群决策方法

针对直觉不确定语言评价的群决策问题,定义了直觉二元不确定语言数及其运算法则、期望值和精确值.提出了直觉二元不确定语言和(IBULS)算子以及加权平均(IBULWA)算子,并验证了IBULWA算子的性质,如单调性、幂等性和介值性.在此基础上,提出一种属性权重已知且属性值为直觉不确定语言信息的群决策方法.最后通过实例说明决策方法的有效性.     

直觉不确定纯语言信息的集结方法及在群决策中的应用

直觉不确定纯语言标度变量是直觉模糊数和不确定纯语言标度变量的拓展,本文定义了直觉不确定纯语言标度变量的运算法则,提出了一些基于直觉不确定纯语言评估标度及其运算法则的信息集结算子,在此基础上,给出了一种专家权重、属性权重及属性值均以语言标度形式给出的直觉不确定纯语言信息的集结方法,并将此方法应用到群决策中,通过实例分析说明了该方法的有效性和可行性。     

不确定隶属度语言Einstein算子及其应用

在不确定隶属度语言变量和Einstein算子的基础上,提出了一种新的算子—不确定隶属度语言Einstein算子,并将其应用到多属性群决策中.首先定义了不确定隶属度语言Einstein算子的概念、相应的运算规则、大小比较方法.之后提出了几种新的不确定隶属度语言Einstein算子,比如:不确定隶属度语言Einstein加权算术平均算子(UMLEWA)、不确定隶属度语言Einstein加权几何平均算子(UMLEWG)、不确定隶属度语言Einstein有序加权算术平均算子(UMLEOWA)、不确定隶属度语言Einstein有序加权几何平均算子(UMLEOWG)、广义不确定隶属度语言Einstein加权算术平均算子(GUMLEWA)、广义不确定隶属度语言Einstein加权几何平均算子(GUMLEWG),以及算子的相应性质(幂等性,有界性,单调性),并证明了性质的正确性.其次在不确定隶属度语言Einstein加权算术平均算子(UMLEWA)和不确定隶属度语言Einstein加权几何平均算子(UMLEWG)基础上,提出了两种不同的方法来处理多属性群决策问题,并给出了具体的群决策步骤.最后,通过实例验证了所提方法的有效性和可行性.     

直觉不确定语言Frank集结算子及其应用

基于直觉不确定语言变量和Frank算子,提出了直觉不确定语言Frank集结算子的概念,给出了直觉不确定语言Frank集结算子的运算规则、期望函数、大小比较方法;定义了直觉不确定语言Frank加权算术平均算子、加权几何平均算子、有序加权算术平均算子、有序加权几何平均算子、广义加权平均算子以及算子具有的幂等性、单调性、有界性等性质.并基于这些算子提出两种属性权重确知且属性值以直觉不确定语言形式给出的决策方法,最后通过实例验证了方法的可行性.     

导出的纯语言OWGA算子及其在的群决策中的应用

研究属性权重、专家权重和属性值均为纯语言变量的多属性群决策问题,利用纯语言变量的运算规律,提出一种新的数据信息集成算子:导出的纯语言有序加权几何平均(IPLOWGA)算子。并且给出纯语言环境下基于IPLOWGA算子和PLOWGA算子的一种群决策方法。最后,进行实例分析,说明该方法的实用性和有效性。     

纯语言信息下基于PLHAA算子的多属性群决策法

本文给出了建立在纯语言加权算术平均(PLWAA)算子和推广的有序加权平均(EOWA)算子基础上的纯语言混合算术平均(PLHAA)算子,研究了专家权重、属性权重及属性值均以语言形式给出的纯语言多属性群决策问题,提出了一种纯语言多属性群决策方法.该方法计算简洁方便且能充分利用已有的决策信息.最后将该方法应用于解决供应链管理领域中的合作伙伴选择问题.     

不确定语言多属性决策的组合方法

研究了属性权重完全未知、属性值以不确定语言变量形式给出的不确定语言多属性决策问题.首先引入了不确定语言变量的运算法则,以及不确定语言变量之间比较的可能度公式,给出了不确定语言变量间的距离的概念.针对属性权重完全未知的情形,给出了一个求解权重的组合公式.然后利用不确定语言加权平均(ULWA)算子,对不确定语言决策信息进行加权集成,并利用可能度公式构造可能度矩阵(互补判断矩阵),继而利用互补判断矩阵排序公式对决策方案进行排序和择优.最后进行了实例分析.     

考虑决策者行为的概率不确定语言决策方法

针对属性权重未知的不确定语言多属性群决策问题,提出一种考虑决策者行为的概率不确定语言决策方法.首先,定义概率不确定语言的海明距离,根据与负理想方案的距离偏差最大建立模型,从而确定属性权重.其次,改进经典TODIM方法适用于概率不确定语言决策环境中,得到了方案排序.最后,通过实例验证了所给方法的可行性,并对比传统的TOPSIS方法进行敏感度分析,进一步验证所提方法的有效性.     

基于二元语言评价的群决策方法

针对语言评价的群决策问题,定义了二元语言术语的概念及其运算法则,并给出二元语言和算子与二元语言加权平均算子,提出一种属性权重已知的语言评价群决策方法.方法首先利用二元语言和算子对专家给出的语言评价信息进行集成,得到方案关于属性的群体评价,然后利用二元语言加权平均算子集成方案各属性的群体评价,得到各方案综合评价.最后通过比较各方案综合评价的期望值和优势度,确定方案排序.     

基于不确定多属性群决策方法的装甲武器战力评估

针对方案的属性权重为实数、属性值为不确定语言,通过定义不确定语言的"依可能度不差于"关系和对影响装甲武器战斗潜力的几个属性进行分析,探讨了不确定语言之间"依可能度不差于"关系比较大小的充要条件,提出了一种基于该关系的多属性群决策方法,并给出了实例仿真.实例表明:方法进行评估步骤少,计算简单,容易施行.     

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.     

Uncertain linguistic Bonferroni mean operators and their application to multiple attribute decision making

In this paper, we investigate the multiple attribute decision making (MADM) problems with uncertain linguistic information. Motivated by the ideal of Bonferroni mean and geometric Bonferroni mean, we develop two aggregation techniques called the uncertain linguistic Bonferroni mean (ULBM) operator and the uncertain linguistic geometric Bonferroni mean (ULGBM) operator for aggregating the uncertain linguistic information. We study its properties and discuss its special cases. For the situations where the input arguments have different importance, we then define the uncertain linguistic weighted Bonferroni mean (ULWBM) operator and the uncertain linguistic weighted geometric Bonferroni mean (ULWGBM) operator, based on which we develop two procedures for multiple attribute decision making under the uncertain linguistic environments. Finally, a practical example is given to verify the developed approach and to demonstrate its practicality and effectiveness.     

A Direct Approach to Group Decision Making with Uncertain Additive Linguistic Preference Relations

In this paper, we study the group decision-making problem in which the preference information given by experts takes the form of uncertain additive linguistic preference relations. We define the concept of uncertain additive linguistic preference relation, and introduce a formula based on possibility measure for comparing two uncertain linguistic preference values. We introduce some aggregation operators such as the uncertain linguistic averaging (ULA) operator and uncertain linguistic weighted averaging (ULWA) operator, etc. Based on the ULA and ULWA operators, we develop a direct approach to group decision making with uncertain additive linguistic preference relations without loss of information. Finally, an illustrative numerical example is given to verify the developed approach.     

基于概率测度的不确定语言多属性决策方法及应用

针对具有不确定语言信息的多属性决策问题,给出了一种基于语言概率测度的决策分析方法。阐述了不确定语言变量的概念,提出了一种用于处理不确定语言变量的语言概率有序加权平均（linguistic probabilistic ordered weighted averaging,LPOWA）算子。采用LPOWA算子将不确定语言转化为二元语义,再通过ETOWA算子得到每个方案的综合评价值,进而可得到所有方案的排序结果。利用LPOWA算子和ETOWA算子,对辽宁省风险投资企业进行评估和优选。理论分析和计算结果表明：该方法简洁可行,便于应用。     

Some interval-valued intuitionistic uncertain linguistic Choquet operators and their application to multi-attribute group decision making

In this study a generated admissible order between interval-valued intuitionistic uncertain linguistic numbers using two continuous functions is introduced. Then, two interval-valued intuitionistic uncertain linguistic operators called the interval-valued intuitionistic uncertain linguistic Choquet averaging (IVIULCA) operator and the interval-valued intuitionistic uncertain linguistic Choquet geometric mean (IVIULCGM) operator are defined, which consider the interactive characteristics among elements in a set. In order to overall reflect the correlations between them, we further define the generalized Shapley interval-valued intuitionistic uncertain linguistic Choquet averaging (GS-IVIULCA) operator and the generalized Shapley interval-valued intuitionistic uncertain linguistic Choquet geometric mean (GS-IVIULCGM) operator. Moreover, if the information about the weights of experts and attributes is incompletely known, the models for the optimal fuzzy measures on expert set and attribute set are established, respectively. Finally, a method to multi-attribute group decision making under interval-valued intuitionistic uncertain linguistic environment is developed, and an example is provided to show the specific application of the developed procedure.     

Development of some linguistic aggregation operators with conservation of interaction between criteria and their application in multiple attribute group decision problems

Decision making problems with fuzzy linguistic information and Choquet integral is investigated in this paper, to introduce three new aggregation operators: 2-tuple choquet integral averaging operator (TCIA), 2-tuple ordered choquet integral averaging operator (TOCIA) and combined 2-tuple choquet integral averaging operator which can be used to aggregate preference information that takes not only the form of linguistic variables but also study some of its desirable properties. Also, we developed a practical method based on TCIA as well as TOCIA operators for multiple attribute group decision making. Furthermore, in this approach alternative assessments are computed by the aggregation of 2-tuple linguistic information. Therefore, ranking alternatives or selecting the most desirable ones will be the outcome of the comparison between the 2-tuple linguistic information. Ultimately, the demonstration of the developed approaches, its practicality and its effectiveness is proved by a numerical example and a comparison with results issued from Wan method (Knowl-Based Syst 45:31–40, 2013).     

On Method for Uncertain Multiple Attribute Decision Making Problems with Uncertain Multiplicative Preference Information on Alternatives

The uncertain multiple attribute decision making (UMADM) problems are investigated, in which the information about attribute weights is known partly and the attribute values take the form of interval numbers, and the decision maker (DM) has uncertain multiplicative preference information on alternatives. We make the decision information uniform by using a transformation formula, and then establish an objective-programming model. The attribute weights can be determined by solving the developed model. The concept of interval positive ideal point of alternatives (IPIPA) is introduced, and an approach based on IPIPA and projection to ranking alternatives is proposed. The method can avoid comparing and ranking interval numbers, and can reflect both the objective information and the DMs subjective preferences.     

一种基于梯形模糊语言变量的多属性决策方法

针对属性权重未知、属性值以梯形模糊语言变量形式给出的多属性决策问题,提出了一种扩展的VIKOR决策方法。首先介绍了梯形模糊语言变量的概念、运算法则,提出了梯形模糊语言变量值之间的距离公式,并进行了证明。在此基础上利用离差最大化方法确定了属性指标权重,并建立了基于梯形模糊语言变量的扩展VIKOR方法,给出了决策步骤。最后,通过一个算例说明该方法的有效性。     

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.