基于IFN 输入的复杂系统关联MCGDM方法

考虑现有直觉模糊熵公理化定义存在的不足,提出改进直觉模糊熵的公理化定义及其计算公式;同时,定义广义幂均算子,验证其相关性质,给出确定幂方参数的方法,并将其推广至广义直觉模糊幂均算子;在以直觉模糊数(IFN)为信息输入的复杂系统框架内,针对决策者及准则之间均存在交互关联关系且权重信息完全未知的多准则群决策(MCGDM)问题,提出基于直觉模糊熵与广义直觉模糊幂均算子的关联MCGDM方法。案例分析表明,所提出的方法是可行且有效的。     

专家权重完全未知的区间直觉不确定语言多属性群决策方法

针对专家权重信息完全未知且属性值为区间直觉不确定语言数的模糊多属性群决策问题,提出一种基于混合权重信息及决策者风险态度的群决策分析方法。在定义区间直觉不确定语言数差异度的基础上,分别利用专家在方案评价值上的贴近度以及方案排序上的一致度来计算两类专家权重,并基于均衡度得到专家的客观综合权重。进而通过融合专家客观综合权重以及基于相似度的个体综合评价值权重,提出一种混合加权集结方法,从而得到方案的群体综合评价值,并通过定义带有风险态度因子的期望值与精确函数实现对方案的比较和排序。最后,通过实例分析证明所提方法的有效性和合理性。     

模糊语言多属性群决策的客观综合赋权方法

针对一类属性及专家权重完全未知且评价值为直觉不确定语言数的多属性群决策问题,提出一种基于客观综合赋权模型的模糊群决策方法。通过定义直觉不确定语言数的不确定度和距离测度,对单个专家内部以及专家群体之间的评价值进行分析,分别建立基于离差最大化和熵值的属性综合赋权模型以及基于不确定度和偏离度的专家综合赋权模型,提出一种基于客观综合权重的直觉不确定语言多属性群决策方法。通过实例分析表明了该方法的可行性和实用性。     

基于改进直觉模糊熵和信息集成算子的多准则群决策方法

针对直觉模糊环境下准则权重和决策者权重完全未知的群决策问题,提出了一种基于改进直觉模糊熵和信息集成算子的多准则群决策方法.首先,借助直觉模糊数、语言变量法和定量指标值转化公式,将决策者的初始评价准则值规范化;其次,引入改进的直觉模糊熵度量方法确定准则权重和决策者权重;进一步对直觉模糊决策矩阵用直觉模糊加权平均算子和直觉模糊有序加权平均算子进行信息集成,利用新的得分函数对备选方案排序择优.从理论上论证了该方法的可行性,结合算例验证了该方法的有效性.     

区间直觉模糊决策中专家与属性权重确定方法

针对评价信息为区间直觉模糊的多属性群决策问题中,决策者与属性的权重均未知的情况,提出一种排序方法。为求解属性值权重,从区间直觉模糊数的几何意义出发,基于熵值最大化原理,求出属性的权重,得到每位专家对每个方案的综合评价值。基于专家个体与专家群体意见之间的灰色关联度以及熵最大化原理,建立模型求出各决策者的权重。在此基础上综合所有专家意见得到评价值,并对方案比较排序。算例验证了此方法的合理有效性。     

基于粗糙集技术的压缩近邻规则

针对各决策时段的时间权重及属性权重已知情况下属性值以直觉模糊数形式给出的动态多属性决策问题,提出了一种基于多准则妥协解排序(VIKOR)拓展的决策分析方法。首先利用给出的动态直觉模糊加权平均(DIF-WA)算子集成各时段的评价值,以获取各方案的综合评价值。然后依据传统VIKOR法的基本思想,结合直觉模糊数的距离公式,对整个方案集进行排序并择优。最后给出一个实例分析,所得结果表明了该方法的可行性和有效性。     

基于广义直觉语言算子的多属性群决策方法

针对属性权重未知,属性值为直觉语言数的多属性决策问题,提出了一种基于直觉语言熵和广义直觉语言算子的群决策方法.定义了直觉语言熵,并利用直觉语言熵确定属性权重,提出了三种直觉语言算子:广义直觉语言加权几何平均(GILWGA)算子、广义直觉语言有序加权几何(GILOWG)算子及广义直觉语言混合几何(GILHG)算子.利用GILWGA和GILHG算子集结信息,采用基于直觉语言数的得分函数及精确函数进行方案排序与择优,最后通过一个算例说明了该方法的有效性和合理性.     

考虑时间序列的动态大群体应急决策方法

针对专家权重和属性权重未知、阶段权重未知且与时间序列有关的动态大群体应急决策问题,提出一种考虑时间序列的动态大群体应急决策方法.首先,提出一个考虑区间直觉模糊数犹豫度的距离公式,定义区间直觉模糊数贴近度,综合考虑贴近度和相似度,用模糊聚类法对大群体专家偏好信息进行聚类;其次,基于现有区间直觉模糊熵公式的不足,提出一个新的区间直觉模糊熵公式,基于此公式考虑专家之间知识水平的差异和各个阶段偏好信息不具遗传性等特点,计算得出专家在不同属性下的权重和属性在各阶段下的权重;再次,考虑时间序列对各阶段权重的影响,构建相对熵模型,对阶段权重进行合理确定,进而利用加权平均算子得到整个决策过程中各方案的综合决策偏好;然后,利用区间直觉模糊数的得分函数和精确函数对方案进行排序,选出最优方案;最后,通过与以往文献的方法对比分析验证所提出方法的有效性和优越性.     

二元语义粗算子及其语言多属性决策中的应用

针对语言多属性决策,提出一种基于二元语言信息处理和粗糙集理论的求解方法。利用规范的语言评价信息建立决策信息表,提出了一种由属性依赖度和信息度来形成属性客观权重的方法,通过二元语义集成算子计算属性的主观权;根据决策者的偏好,将各属性的主客观权重信息集成,得到属性综合权重;将规范化的语言评价信息转化为二元语言形式,并与已有的信息集结算子合成,得到二语义粗算子;举例说明二元语义粗算子的应用。     

多属性群决策的直觉梯形模糊数法

采用直觉梯形模糊数刻画专家的评价信息,提出一种新的多属性群决策方法.定义了直觉梯形模糊数的期望值、预期得分、有序加权集成算子和混合集成算子;建立了基于直觉梯形模糊数的多属性群决策模型;通过混合集成算子得到方案的群体综合评估值,根据期望值和预期得分给出群决策结果.实例分析验证了所提出方法的有效性.     

Developing dynamic intuitionistic normal fuzzy aggregation operators for multi-attribute decision-making with time sequence preference

In allusion to dynamic intuitionistic normal fuzzy multi-attribute decision-making (MADM) problems with unknown time weight, a MADM method based on dynamic intuitionistic normal fuzzy aggregation (DINFA) operators and VIKOR method with time sequence preference was presented. In this method, two information aggregating operators were first proposed and proved, including dynamic intuitionistic normal fuzzy weighted arithmetic average (DINFWAA) operator and dynamic intuitionistic normal fuzzy weighted geometric average (DINFWGA) operator. Meanwhile, we constructed a multi-target nonlinear programming model, which fused time degree theory that was based on subjective preference and information entropy principle based on objective preference, to obtain time weight. Based on which, according to the algorithm of intuitionistic normal fuzzy number, intuitionistic normal fuzzy information under different time sequences were aggregated by using the proposed DINFA operators, and formed a dynamic intuitionistic normal fuzzy comprehensive decision-making matrix; then, obtained the optimal solution that was the closest to ideal solution via VIKOR method. Finally, the feasibility and significance of the presented method over existing methods were verified via analysis of numerical examples.     

区间直觉二元语言集成算子及其群决策方法

基于下标以零为中心对称的语言评估标度,将区间不确定二元语言集与区间直觉模糊集结合,提出区间直觉二元语言集及变量的概念;讨论区间直觉二元语言变量的运算及可能度;提出区间直觉二元语言加权算术平均算子、区间直觉二元语言有序加权平均算子,并在此基础上,通过可能度矩阵对区间直觉二元语言变量进行排序提出区间直觉二元语言混合加权平均算子;最后基于这些算子构建了一种新的直觉模糊多属性群决策方法,并将其运用于供应商选择过程中。     

基于动态P-模糊语言算子的VIKOR决策方法

针对直觉模糊信息解决动态多属性决策问题时存在的不足,将Pythagorean模糊语言信息引入到动态多属性决策问题,提出一种基于Pythagorean模糊语言信息集成算子的多准则妥协排序（VIKOR）决策方法。引入Pythagorean模糊语言得分函数、精确函数、距离计算公式等概念,提出动态 Pythagorean模糊语言加权平均（DPFLWA）算子,并研究DPFLWA算子的基本性质。最后,基于DPFLWA算子和VIKOR方法,构建一种动态 Pythagorean模糊语言多属性决策方法。通过第三方逆向物流服务商的选择实例,表明该方法的可行性和有效性。     

Linguistic hesitant intuitionistic fuzzy decision-making method based on VIKOR

Linguistic hesitant intuitionistic fuzzy set, which allows an element having several linguistic evaluation values and each linguistic argument having several intuitionistic fuzzy memberships, is a power tool to model uncertain information existing in multiple attribute decision-making problems. In this paper, we propose new methods by using TOPSIS and VIKOR for multiple attribute decision-making problems, in which evaluation values are in the form of linguistic hesitant intuitionistic fuzzy elements. Different situations of attribute weight information are considered. If attribute weights are partly known, a linear programming model is set up based on the idea that reasonable weights should make the relative closeness of each alternative evaluation value to the linguistic hesitant intuitionistic fuzzy positive ideal solution as large as possible. If attribute weights are unknown completely, an optimization model is set up based on the maximum deviation method. A numerical example is presented to illustrate feasibility and practical advantages of the proposed method. We compare the alternatives’ rankings derived from the linguistic hesitant intuitionistic fuzzy TOPSIS method with those derived from the hesitant fuzzy linguistic TOPSIS and the hesitant intuitionistic fuzzy TOPSIS approach to further illustrate their advantages.

     

Some power Maclaurin symmetric mean aggregation operators based on Pythagorean fuzzy linguistic numbers and their application to group decision making

The power average (PA) operator and Maclaurin symmetric mean (MSM) operator are two important tools to handle the multiple attribute group decision‐making (MAGDM) problems, and the combination of two operators can eliminate the influence of unreasonable information from biased decision makers (DMs) and can capture the interrelationship among any number of arguments. The Pythagorean fuzzy linguistic set (PFLS) is parallel to the intuitionistic linguistic set (ILS), which is more powerful to convey the uncertainty and ambiguity of the DMs than ILS. In this paper, we propose some power MSM aggregation operators for Pythagorean fuzzy linguistic information, such as Pythagorean fuzzy linguistic power MSM operator and Pythagorean fuzzy linguistic power weighted MSM (PFLPWMSM) operator. At the same time, we further discuss the properties and special cases of these operators. Then, we propose a new method to solve the MAGDM problems with Pythagorean fuzzy linguistic information based on the PFLPWMSM operator. Finally, some illustrative examples are utilized to show the effectiveness of the proposed method.     

A New Intuitionistic Fuzzy Linguistic Hybrid Aggregation Operator and Its Application for Linguistic Group Decision Making

The linguistic aggregation operator is an important decision‐making model that is proving effective for dealing with the input data that takes the form of uncertain information. In this paper, considering the principal component of the intuitionistic fuzzy linguistic variables, we develop a new intuitionistic fuzzy linguistic hybrid aggregation (NIFLHA) operator to solve group decision‐making problems under the situation with intuitionistic fuzzy linguistic information. Then, we study some of its main properties by utilizing some operational laws of intuitionistic fuzzy linguistic variables and the different families of the NIFLHA operator. Moreover, the multiperson NIFLHA (MP‐NIFLHA) operator is introduced to evaluate the opinions of experts. Finally, an illustrative example about a multiperson decision‐making problem is developed to reveal the applicability and the availability of the raised operator.     

基于模糊-两阶段超效率SBM的电网应急能力动态综合评价

首先,对电网应急能力进行基于时间维度和空间维度的拆解,构建基本电网应急能力评价指标体系;其次,考虑到指标评价标准具有动态性的问题,采用三角模糊数对指标进行量化处理,并建立可对多个模糊数集结的优化模型;然后,采用α-截集对三角模糊数进行处理并建立基于单一时间节点下的模糊-两阶段超效率SBM模型实现对电网应急能力的静态评价;最后,以时间维度拆解为基础,建立电网应急能力动态综合评价模型,实现对应急能力的整体评价、排序,使评价结果更加具有科学性和合理性.实例分析结果表明,所提出方法可有效区分应急能力仍需作出改善的区域,并在一定程度上克服评价标准需要动态变化的问题,具有较强的客观性.     

A Novel Approach for Linguistic Group Decision Making Based on Generalized Interval‐Valued Intuitionistic Fuzzy Linguistic Induced Hybrid Operator and TOPSIS

In the multiple attribute linguistic group decision making analysis with interval‐valued intuitionistic fuzzy linguistic information, seeking highly efficient aggregation method and order relation play a crucial role. In this paper, we redefine an interval‐valued intuitionistic fuzzy linguistic variable that considers principal component and propose generalized interval‐valued intuitionistic fuzzy linguistic induced hybrid aggregation (GIVIFLIHA) operator with entropic order‐inducing variable and interval‐valued intuitionistic fuzzy linguistic technique for order preference by similarity to an ideal solution (TOPSIS) order relation based on interval‐valued intuitionistic fuzzy linguistic distance measure. Then, some primary properties of the GIVIFLIHA operator are discussed, and a linguistic group decision‐making approach based on GIVIFLIHA operator and interval‐valued intuitionistic fuzzy linguistic TOPSIS order relation is proposed. Finally, a numerical example concerning the investment strategy is given to illustrate the validity and applicability of the proposed method, and then the method is compared with the existing method to further illustrate its flexibility.