An extended TODIM method for multiple attribute group decision‐making based on 2‐dimension uncertain linguistic Variable

The significant characteristic of the TODIM (an acronym in Portuguese of Interactive and Multiple Attribute Decision Making) method is that it can consider the bounded rationality of the decision makers. However, in the classical TODIM method, the rating of the attributes only can be used in the form of crisp numbers. Because 2‐dimension uncertain linguistic variables can easily express the fuzzy information, in this article, we extend the TODIM method to 2‐dimension uncertain linguistic information. First of all, the definition, characteristics, expectation, comparative method and distance of 2‐dimension uncertain linguistic information are introduced, and the steps of the classical TODIM method for Multiple attribute decision making (MADM) problems are presented. Second, on the basis of the classical TODIM method, the extended TODIM method is proposed to deal with MADM problems in which the attribute values are in the form of 2‐dimension uncertain linguistic variables, and detailed decision steps are given. Its significant characteristic is that it can fully consider the bounded rationality of the decision makers, which is a real action in real decision making. Finally, a numerical example is provided to verify the developed approach and its practicality and effectiveness. © 2014 Wiley Periodicals, Inc. Complexity 21: 20–30, 2016     

Extension of VIKOR method for multi-criteria group decision making problem with linguistic information

A new method is proposed to solve multi-criteria group decision making problems in which both the criteria values and criteria weights take the form of linguistic information based on the traditional idea of VIKOR method. Firstly, the linguistic criteria weights given by all decision makers are transformed into trapezoidal fuzzy numbers, and then aggregated and defuzzified to crisp values. Secondly, the individual linguistic decision matrix given by each decision maker (DM) is transformed into 2-tuple linguistic decision matrix, and then aggregated into collective 2-tuple linguistic decision matrix by 2-tuple linguistic arithmetic mean operation. Thirdly, the 2-tuple linguistic values (_Si,_αi),$(S_i\text{,}{\alpha }_i)\text{,}$(_Ri,_αi)$(R_i\text{,}{\alpha }_i)$ and (_Qi,_αi)$(Q_i\text{,}{\alpha }_i)$ are calculated by defining the 2-tuple linguistic positive ideal solution (TL-PIS) and 2-tuple linguistic negative ideal solution (TL-NIS). Furthermore, the compromise solution can be obtained. Finally, a numerical example is used to illustrate the application of the proposed approach, and the method is verified by comparing the evaluation result with that of 2-tuple linguistic TOPSIS (TL-TOPSIS) method.     

基于区间值直觉模糊不确定语言变量的灰色关联度分析方法

给出了区间值直觉模糊不确定语言环境下的灰色关联度分析方法。首先确定了区间值直觉模糊不确定语言正负理想解, 然后计算每个评价值与正负理想解的灰色关联度, 利用属性的权重向量, 计算方案与正负理想解的灰色关联度, 最后计算出方案的相对关联度, 并根据方案的相对关联度对方案进行排序。如果属性权重部分可知, 则需要根据与正理想解有最大的灰色关联度而与负理想解有最小的关联度的原则建立数学规划确定属性的权重。最后, 为了说明算法的可行性和有效性, 将其应用到房地产开发项目的风险评价上。 实例说明了算法的可行性和有效性。     

A new method for multiple criteria group decision making with incomplete weight information under linguistic environment

A new method is proposed to solve multiple criteria group decision making (MCGDM) problems, in which both the criteria values and criteria weights take the form of linguistic information, and the information about linguistic criteria weights is partly known or completely unknown. Firstly, to get reasonable decision result, instead of assigning the same weight to the decision maker (DM) for all criteria, we propose a method to determine the weight of DM with respect to each criterion under linguistic environment by calculating the similarity degree between individual 2-tuple linguistic evaluation value and the mean given by all decision makers (DMs). Secondly, for the situations where the information about the criteria weights is partly known or completely unknown, we establish optimization models to determine the criteria weights by defining 2-tuple linguistic positive ideal solution (TL-PIS), 2-tuple linguistic right negative ideal solution (TL-RNIS) and 2-tuple linguistic left negative ideal solution (TL-LNIS) of the collective 2-tuple linguistic decision matrix. Thirdly, we propose a new method to solve MCGDM problems with partly known or completely unknown linguistic weight information. Finally, an illustrative example is given to demonstrate the calculation process of the proposed method.     

基于语言值2元组的多属性决策方法

利用2元组方法建立了一个语言值决策模型和LOW A算子模型,这两个模型具有可操作性强和语义明确等优点,特别是充分利用了语言值所含的信息,提高了决策结果的精度.最后,利用这两个模型给出了基于语言值的多属性群决策方法,同时给出一个应用实例.     

基于综合权重的理想模糊物元多属性决策法及应用

研究了属性指标具有不相容性和模糊性及其指标的权重完全未知的模糊多属性决策问题.分析了目前广泛采用的模糊物元分析法以及仅有主观赋权法或客观赋权法确定其指标权重的缺点.根据物元可拓理论和理想解法的思想,定义了理想模糊物元和负理想模糊物元的概念.利用兼顾主观偏好和客观信息的综合权重赋值法,提出了基于综合权重的理想模糊物元多属性决策方法.该法既能充分利用指标本身所包含的客观信息,又能充分发挥决策者的主观能动性.实例研究结果表明该法能反映出决策方案间的细微差别,能对决策方案的优劣做出更准确有效的评价.     

基于区间直觉模糊不确定语言变量的VIKOR方法及其在房地产开发风险评价中的应用

采用区间值直觉模糊不确定语言变量建模决策中存在的不确定信息,给出了一个新的不确定环境下的VIKOR方法.首先采用区间直觉模糊不确定语言变量对方案进行评价,然后将VIKOR方法进行推广到新的不确定环境下,给出新的方案排序方法.最后为了说明方法的有效性和合理性,将所给的方法应用于房地产开发方案的风险评价中.     

A consensus-based probabilistic linguistic gained and lost dominance score method

This paper proposes a comprehensive Multiple Criteria Group Decision Making (MCGDM) method with probabilistic linguistic information based on a new consensus measure and a novel outranking method, Gained and Lost Dominance Score (GLDS). Firstly, new operations of the probabilistic linguistic term sets are introduced based on the adjusted rules of probabilistic linguistic term sets and the linguistic scale functions for semantics of linguistic terms. After defining a new consensus measure based on the correlation degree between probabilistic linguistic term sets, we develop a consensus reaching method to improve the consensus degree of a group. To rank alternatives reasonably, we further propose the GLDS method which considers both the “group utility” and the “individual regret” values. The core of the GLDS is to calculate the gained and lost dominance scores that the optimal solution dominates all other alternatives in terms of the net gained dominance flow and the net lost dominance flow. Then, we integrate the GLDS ranking method with the consensus reaching process and develop a consensus-based PL-GLDS method to solve the MCGDM problems with probabilistic linguistic information. Finally, the proposed method is validated by a case study of selecting optimal green enterprises. Some comparative analyses are given to show the efficiency of the proposed method.     

模糊熵与距离测度的相互诱导及其应用

模糊信息论就是利用模糊数学这一工具来研究带有模糊不确定性的信息的．模糊熵和距离测度是模糊信息论中两个重要的度量方法．本文主要讨论模糊熵和距离测度之间的相互关系,由此得到几个由模糊熵诱导的距离测度公式和几个由距离测度诱导出的模糊熵公式,说明了模糊熵和距离测度是可以相互诱导的．最后,举例说明距离测度公式在模式识别中的应用．     

基于距离测度及支持度的混合评价信息供应商选择决策

新零售模式的推进迫使企业不断加强供应链节点上的供应商选择优化,是企业新时代发展面临的新课题。针对供应商选择优化提出一种基于距离测度及支持度的群决策方法,根据不同类型属性评价信息的距离测度定义,得到不同决策者之间关于单一属性指标的相互支持度,从而确定单个供应商各属性的群体综合评价值,并采用灰关联法对备选供应商进行排序择优。     

Projection method for multiple criteria group decision making with incomplete weight information in linguistic setting

Multiple criteria group decision making (MCGDM) problems have become a very active research field over the last decade. Many practical problems are often characterized by MCGDM. The aim of this paper is to develop a new approach for MCGDM problems with incomplete weight information in linguistic setting based on the projection method. Firstly, to reflect the reality accurately, a method to determine the weights of decision makers in linguistic setting is proposed by calculating the degree of similarity between 2-tuple linguistic decision matrix given by each decision maker and the average 2-tuple linguistic decision matrix. By using the weights of decision makers, all individual 2-tuple linguistic decision matrices are aggregated into a collective one. Then, to determine the weight vector of criteria, we establish a non-linear optimization model based on the basic ideal of the projection method, i.e., the optimal alternative should have the largest projection on the 2-tuple linguistic positive ideal solution (TLPIS). Calculate the 2-tuple linguistic projection of each alternative on the TLPIS and rank all the alternatives according to the 2-tuple linguistic projection value. Finally, an illustrative example is given to demonstrate the calculation process of the proposed method, and the validity is verified by comparing the evaluation results of the proposed method with that of the technique for order preference by similarity to ideal solution (TOPSIS) method.     

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.     

基于累积前景理论的考虑群体参考点的多指标风险决策方法

针对考虑多个决策者给出不同的指标期望的多指标风险决策问题,提出一种基于累积前景理论的决策分析方法。在本文中,将决策者给出的指标期望视为参照点,通过构建基于参照点的价值矩阵和权重矩阵,进而构建前景决策矩阵,并基于前景决策矩阵来计算每个方案的综合前景值,然后依据综合前景值的大小对所有方案进行排序。最后,通过一个算例说明了该方法的可行性和有效性。     

Developing a straightforward approach for group decision making based on determining weights of decision makers

Group decision making is an active area of research within multiple attribute decision making. This paper assumes that all the decision makers (DMs) are not equally qualified to contribute equitably to the decision process. The aim of this paper is to develop an approach to determine weights of DMs, in which the decision information on alternatives with respect to attributes, provided by each DM, is represented in the form of interval data. We define the average of all individual decisions as the positive ideal decision (PID), and the maximum separation from PID as the negative ideal decision, which are characterized by a matrix, respectively. The weight of each DM is determined according to the Euclidean distances between the individual decision and ideal decisions. By using the obtained weights of DMs, all individual decisions are aggregated into a collective decision. Then the alternatives is ranked based on the collective decision. Meanwhile, this paper also gives a humanized decision method by using an optimistic coefficient, which is used in adjusting the relative importance between profit and risk. Finally, we give an example to illustrate the developed approach.     

基于不完全权重信息下模糊多属性决策的供应链合作伙伴选择

针对属性权重完全未知或只有部分权重信息且属性值为三角模糊数的供应链合作伙伴选择问题,给出了一种模糊多属性决策方法.提出了一种基于置信度的定性指标的量化方法,通过求解最优化决策模型确定属性的权重,然后根据各方案到模糊理想点的相对贴近度的大小选择最优的合作伙伴.     

基于预期方案求解多属性决策问题的新方法研究

章提出了基于预期方案求解多属性决策问题的一种新方法。该方法基于预期方案，利用指数效用曲线拟合指标数据，通过定义的偏差测度和指标一致度来确定相应的指标权重，最后通过动态调整预期方案进行多属性综合评价。     

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.     

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.     

基于区间型多属性决策的突发事件属性熵权的确定

突发事件的实时数据是应急决策的依据,提高对数据的处理能力,确定突发事件属性的熵权,筛选出反映事件发展趋势的重要属性,是提高决策效率和准确性的关键问题。利用共性知识模型结构化表示突发事件和属性,参考区间型多属性决策方法,把事件属性监测值转换为区间数型,在保持时序信息的同时降低数据维数,并通过定义精确数与区间的距离,使突发事件属性集均转化为成本型属性;继而利用基于熵权的区间型多属性决策方法计算事件的属性熵权值,权值越大,表示包含事件演化趋势的信息越多,在决策时就应被重点关注。最后,通过实例说明此方法的有效性和实用性。     

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。