Interactive group decision making procedure based on uncertain multiplicative linguistic preference relations

Group decision making problems are investigated with uncertain multiplicative linguistic preference relations.An unbalanced multiplicative linguistic label set is introduced,which can be used by the experts to express their linguistic preference information over alternatives.The uncertain linguistic weighted geometric mean operator is utilized to aggregate all the individual uncertain multiplicative linguistic preference relations into a collective one,and then a simple approach is developed to determine the experts＇ weights by utilizing the consensus degrees among the individual uncertain multiplicative linguistic preference relations and the collective uncertain multiplicative linguistic preference relations.Furthermore,a practical interactive procedure for group decision making is proposed based on uncertain multiplicative linguistic preference relations,in which a possibility degree formula and a complementary matrix are used to rank the given alternatives.Finally,the proposed procedure is applied to solve the group decision making problem of a manufacturing company searching the best global supplier for one of its most critical parts used in assembling process.

Pythagorean Uncertain Linguistic Variable Hamy Mean Operator and Its Application to Multi-attribute Group Decision Making

Pythagorean fuzzy set(PFS) can provide more flexibility than intuitionistic fuzzy set(IFS) for handling uncertain information, and PFS has been increasingly used in multi-attribute decision making problems. This paper proposes a new multiattribute group decision making method based on Pythagorean uncertain linguistic variable Hamy mean(PULVHM) operator and VIKOR method. Firstly, we define operation rules and a new aggregation operator of Pythagorean uncertain linguistic variable(PULV) and explore some properties of the operator.Secondly, taking the decision makers' hesitation degree into account, a new score function is defined, and we further develop a new group decision making approach integrated with VIKOR method. Finally, an investment example is demonstrated to elaborate the validity of the proposed method. Sensibility analysis and comprehensive comparisons with another two methods are performed to show the stability and advantage of our method.

Some interval-valued intuitionistic uncertain linguistic hybrid Shapley operators

Two interval-valued intuitionistic uncertain linguistic hybrid operators cal ed the induced interval-valued intuitionistic uncertain linguistic hybrid Shapley averaging （I-IIULHSA） operator and the induced interval-valued intuitionistic uncertain linguistic hybrid Shapley geometric （I-IIULHSG） operator are defined. These operators not only reflect the importance of elements and their ordered positions, but also consider the correlations among elements and their ordered positions. Since the fuzzy measures are defined on the power set, it makes the problem exponentially complex. In order to simplify the complexity of solving a fuzzy measure, we further define the induced interval-valued intuitionistic uncertain linguistic hybrid λ-Shapley averaging （I-IIULHλSA） operator and the induced interval-valued intuitionistic uncertain linguistic hybrid λ-Shapley geometric （I-IIULHλSG） operator. Moreover, an approach for multi-attribute group decision making under the interval-valued intuitionistic uncertain linguistic environment is developed. Finally, a numerical example is provided to verify the developed procedure and demonstrate its practicality and feasibility.

Multi-attribute group decision making method under 2-dimension uncertain linguistic variables

A method is proposed to deal with the uncertain multiple attribute group decision making problems,where 2-dimension uncertain linguistic variables(2DULVs)are used as the reliable way for the experts to express their fuzzy subjective evaluation information.Firstly,in order to measure the 2DULVs more accurately,a new method is proposed to compare two 2DULVs,called a score function,while a new function is defined to measure the distance between two 2DULVs.Secondly,two optimization models are established to determine the weight of experts and attributes based on the new distance formula and a weighted average operator is used to determine the comprehensive evaluation value of each alternative.Then,a score function is used to determine the ranking of the alternatives.Finally,the effectiveness of the proposed method is proved by an illustrated example.

Dombi-Normalized Weighted Bonferroni Mean Operators with Novel Multiple-Valued Complex Neutrosophic Uncertain Linguistic Sets and Their Application in Decision Making

Although fuzzy set concepts have evolved,neutrosophic sets are attractingmore attention due to the greater power of the structure of neutrosophic sets.The ability to account for components that are true,false or neither true nor false is useful in the resolution of real-life problems.However,simultaneous variations render neutrosophic sets unsuitable in specific circumstances.To enable the management of these sorts of issues,we combine the principle of multi-valued neutrosophic uncertain linguistic sets and complex fuzzy sets to develop the principle of multivalued complex neutrosophic uncertain linguistic sets.Multi-valued complex neutrosophic uncertain linguistic sets can contain grades of truth,abstinence,and falsity,and uncertain linguistic terms,which are expressed as complex numbers whose real and imaginary parts are limited to the unit interval.Some important Dombi laws are elaborated along with Bonferroni mean operators,which offer a flexible general structure with modifiable factors.Bonferroni means aggregation operators perform a significant role in conveying the magnitude level of options and characteristics.To determine relationships among any number of attributes,we develop multi-valued complex neutrosophic uncertain linguistic Dombi-normalized weighted Bonferroni mean operators and discuss their important properties with some special cases.By using these laws,we can deploy themulti-attribute decisionmaking(MADM)technique using the novel principle of multi-valued complex neutrosophic uncertain linguistic sets.To determine the power and flexibility of the elaborated approach,we resolve some numerical examples based on the proposed operator.Finally,the work is validated with the help of comparative analysis,a discussion of its advantages,and geometric expressions of the elaborated theories.

Multi-attribute decision-making approach dealing with uncertain linguistic assessment information

An approach is presented to deal with a multi-attribute decision-making problem in which the attribute weights are unknown and the attribute values take the form of uncertain linguistic variables. First, a linguistic assessment standard is set up to deal with the uncertain linguistic attributes, and the operation laws of uncertain linguistic variables and the uncertain linguistic weighting average(ULWA)operator are introduced. Then a ranking formula of uncertain linguistic variables based on expectation-variance is proposed. As for the case without weight information, a goal program based on a warp function is constructed to determine the attribute weights, and the ULWA operator is utilized to aggregate the assessment information of uncertain linguistic variables, and the corresponding alternatives are ranked by a formula based on expectation-variance. Finally, a numerical example is given, and the results demonstrate that it is much easier and faster for the ranking method based on expectation-variance when compared to the existing methods.

A Method for Determining the Importance of Critical Emergency Indicators Based on Multi-granularity Uncertain Language

In view of the complexity of emergencies and the subjectivity of decision-makers,a method of determining key emergency indicators based on multi-granularity uncertainty language is proposed.Firstly,decision members use preferred uncertain language phrases to represent the importance of each key indicator and use transformation functions to carry out the consistent transformation of this multi-granularity uncertain language information.Secondly,the group evaluation vector is obtained by using the extended weighted average operator of uncertainty,and then the weight vector of each key index is obtained by using the decision theory of uncertain language.Finally,an example is given to verify the practicability and effectiveness of the proposed method.

新型犹豫不确定Z-Numbers熵及其多准则群决策分析

犹豫不确定语言型Z-Numbers的语言尺度函数是由两种不同语义的集合构成,分别度量两种语言尺度函数,确定其三个基本性质。结合语言尺度函数和犹豫不确定语言型Z-Numbers的模糊因子及犹豫因子,构造了犹豫不确定语言型Z-Numbers的交叉熵和熵,引入求解决策者权重和准则权重的两种最优化模型,通过求解最优化模型确定综合熵决策矩阵,由排序值公式给出多准则群决策问题的最优方案。通过一个实例分析比较得出相同的最优方案和不同排序,验证了该决策方法的有效性与可行性。

On Normalization of Comprehensive Evaluation System with Complex Uncertain Information

This paper systematically proposes basic requirements on normalization of comprehensive evaluation system with complex uncertain information due to human participation. Four basic academic ideas are as follows: 1) It is necessary to normalize conditions of information acquisition. 2) The effectiveness of comprehensive evaluation depends on the correctness of information acquisition. 3) Any evaluation results can be transformed into linguistic satisfactory degrees. 4) Linguistic values can include a great deal of information. This paper mainly deals with how to select objects to be evaluated, evaluators (panelists) and the methods of information processing, how to construct criteria of evaluation, how to normalize terms of evaluation, the results of evaluation, and the procedure of evaluation.

属性权重动态更新的自适应群体共识决策方法

为了提高不确定语言环境下异构多属性群决策的质量、效率及可解释性,提出一种属性权重动态更新的自适应群体共识决策方法。首先,定义不确定语言变量与中间值之间的转换函数,发展多级共识测度,建立计算属性初始权重的双目标优化模型;进而,构建包含群体共识自动达成规则和属性权重动态更新机制的自适应共识模型,实现待调整值的精准定位和自动修改,在优化属性权重的同时进一步提升群体共识水平;然后,对于达成共识的群体决策矩阵,先利用转换函数将中间值转换为不确定语言变量,再使用属性权重和集结算子得到各方案的综合评价结果;最后,通过供应商选择实例和实验比较分析验证所提方法的有效性和可行性。本文研究结果为灵活、高效地求解复杂环境下的多属性群决策问题提供了有效途径。

Man-machine Function Allocation Based on Uncertain Linguistic Multiple Attribute Decision Making

Function allocation is one of the necessary stages in the design course of man-machine systems since appropriate function allocation makes the whole system more effective, reliable and inexpensive. Therefore, our research mainly focuses on the problems of function allocation between man and machine in man-machine systems, analyses each capability advantage of man and machine according to their respective inherent characteristics and makes a comparison between them. In view of highly uncertain characteristics of decision attribute value in the practical process, we introduce the uncertain linguistic multiple attribute decision making （ULMADM） method in the function allocation process. Meanwhile, we also use the uncertain extended weighted arithmetic averaging （UEWAA） method to determine the automation level range of the operator functions. Then, we eventually estab- lish the automation level of man-machine function allocation by using the multi-attribute decision making algorithm, which is combined by UEWAA and uncertain linguistic hybrid aggregation （ULHA） operators. Finally, an example about function allocation is given, that is, fault diagnosis in the cockpit of civil aircraft. The final result of the example demonstrates that the proposed method about function allocation is feasible and effective.

MCGDM model using uncertain linguistic consistency sets of single andinterval linguistic term multivalued sets

This paper presents hybrid linguistic expressions and operations for the hybridlinguistic multiple criteria group decision making (MCGDM) issue withidentical and/or different single and interval linguistic term values. First, wepropose a single and interval linguistic term multivalued set/element (SILTMS/SILTME) and develop a consistency measure of SILTMEs based on Shannonentropy to measure the consistency degree of single and interval linguistic termvalues in SILTME. Second, we converse SILTMS/SILTME into an uncertainlinguistic consistency set/element (ULCS/ULCE) in terms of the mean andconsistency measure of SILTMEs to reasonably perform operations betweendifferent information forms/sequence lengths in SILTMSs. Third, we definesome operations of ULCEs and the expected values and sorting rules ofULCEs. Fourth, we present the ULCE weighted mean and geometric operatorsand their characteristics. Finally, we develop a MCGDM model using theweighted mean operation of the two operators and apply it in the mine safetyassessment.

Probabilistic uncertain linguistic TODIM method based on the generalized Choquet integral and its application

Purpose-The purpose of this paper is to develop a probabilistic uncertain linguistic(PUL)TODIM method based on the generalized Choquet integral,with respect to the interdependencies between criteria,for the selection of the best alternate in the context of multiple criteria group decision-making(MCGDM).Design/methodology/approach-Owing to decision makers(DMs)do not always show completely rational and may have the preference of bounded rational behavior,this may affect the result of the MCGDM.At the same time,criteria interaction is a focused issue in MCGDM.Hence,a novel TODIM method based on the generalized Choquet integral selects the best alternate using PUL evaluation,where the generalized Choquet integral is used to calculate the weight of criterion.The generalized PUL distance measure between two probabilistic uncertain linguistic elements(PULEs)is calculated and the perceived dominance degree matrices for each alternate relative to other alternates are obtained.Furthermore,the comprehensive perceived dominance degree of each alternate can be calculated to get the ranking.Findings-Potential application of the PUL-TODIM method is demonstrated through an evaluation example with sensitivity and comparative analysis.Originality/value-As per author’s concern,there are no TODIM methods with probabilistic uncertain linguistic sets(PULTSs)to solve MCGDM problems under uncertainty.Compared with the result of existing methods,the final judgment value of alternates using the extended TODIM methodology is highly corroborated,which proves its potential in solving MCGDM problems under qualitative and quantitative environments.

A Novel Dependent Aggregation Approach for Intuitionistic Uncertain Linguistic Multiple Attribute Group Decision Making

The multiple attribute group decision making problem in which the input arguments take the form of intuitionistic uncertain linguistic information is studied in the paper.Based on the operational principles of intuitionistic uncertain linguistic variables and the concept of the expected value and accuracy function,some new dependent aggregation operators with intuitionistic uncertain linguistic information including the dependent intuitionistic uncertain linguistic ordered weighted average(DIULOWA)operator,the dependent intuitionistic uncertain linguistic ordered weighted geometric(DIULOWG)operator,the generalized dependent intuitionistic uncertain linguistic ordered weighted aggregation(GDIULOWA)operator and so on are developed,in which the associated weights only depend on the aggregated arguments.Also,we study some desirable properties of the aggregation operators.Moreover,the approach of multiple attribute group decision making with intuitionistic uncertain linguistic information based on the developed operators is proposed.Finally,an illustrative numerical example is given to show the practicality and effectiveness of the proposed approaches.

Spherical uncertain linguistic Hamacher aggregation operators and their application on achieving consistent opinion fusion in group decision making

Purpose-The aim of this research is to establish a new type of aggregation operator based on Hamacher operational law of spherical uncertain linguistic numbers(SULNs).Design/methodology/approach-First,the authors define spherical uncertain linguistic sets and develop some operational laws of SULNs.Furthermore,the authors extended these operational laws to the aggregation operator and developed spherical uncertain linguistic Hamacher averaging and geometric aggregation operators.Findings-The authors were limited in achieving a consistent opinion on the fusion in group decision-making problem with the SULN information.Originality/value-In order to give an application of the introduced operators,the authors first constrict a system of multi-attribute decision-making algorithm.

对方案有偏好的不确定语言多属性决策方法

研究了属性权重完全未知、属性值和对方案的偏好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,给出了求解权重的公式。然后,利用不确定语言加权平均算子,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。

不确定语言环境下基于ULHGA算子的群决策方法(英文)

研究属性权重和专家权重为确定的实数,属性值为不确定语言变量的多属性群决策问题。提出了一种新的数据信息集成算子不确定语言混合几何集结(ULHGA)算子,并给出不确定语言环境下基于ULWGM算子和ULHGA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。

不确定语言信息下的大规模交互式群体评价方法及其应用

针对目前不确定语言信息下的交互式群体评价研究数量较少且大多只适合中小规模群体研究的不足,提出了一种新的不确定语言信息下的大规模交互式群体评价方法。对单轮大规模不确定群体意见进行合理的聚类分组,并运用二维不确定语言密度算子对其进行集结;给出了一个大规模群体意见的稳定性指标,以此来确定交互终止的条件;最后,在诱导不确定语言混合集成算子的基础上,对多轮评价结果进行了集结。实例分析验证了该方法的有效性和合理性。

基于二元语义的不确定性多属性决策的4种集成算子

由于二元语义的排序方法不能处理结果之间相互包含的情况,因此在不确定性语言环境下,文章给出了区间二元语义[20,21]的新的排序方法,并给出了不确定性二元组的4种集成算子,即不确定性语言二元组几何平均算子、不确定性语言二元组加权几何算子、不确定性语言二元组有序加权几何平均算子及不确定性语言二元组混合集成算子,4种集成算子解决了对集成结果只有细微差别时难以评价优劣的问题,并研究了算子的基本性质,通过应用实例对其实用性及优越性给出证明。

不确定条件下产品模块划分方案评价方法

针对模块化产品设计过程中模块划分结果的评价与决策问题,提出基于不确定语言变量多属性决策的评价方法。不同的模块划分方法、划分标准,可获得不同的模块划分方案,需对这些方案进行评价与决策。依据成本多属性评价体系,运用依赖型不确定语言有序加权几何(Dependent uncertain linguistic ordered weighted geometric,DULOWG)算子,对模块划分方案做出评价。由评价者对模块划分方案关于属性进行测度,构建多属性评价矩阵,借助不确定语言变量调整权重,从而降低评价者因主观性导致评价结果的不合理,从而提高评价方法的客观性和有效性。在此基础上对各方案进行评价计算得到成本多属性综合影响下的最优方案,并以开关柜为实例验证了该方法的可行性与有效性。同时,将本文方法与模糊层次分析法进行比较,指出本文方法的优越性。