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.

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。

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.

民航安全复杂系统的关键成功因素识别--基于中国民航近10年安全管理工作的研究

为了探寻民航安全长周期运行的经验,即确定对实现安全运行起着决定性作用的关键因素,首先,收集了中国民航行业发布的航空安全工作报告、政策新闻、具有10 a以上工作经验的专家访谈等资料,运用扎根理论对其进行处理以识别民航安全复杂系统的影响因素。其次,利用提出的二维不确定语言变量(2-Dimension Uncertain Linguistic Variables,2DULVs)分层决策试验与评估实验室(DecisionMaking Trial and Evaluation Laboratory,DEMATEL)混合模型计算影响因素的中心度和原因度,以此识别民航安全复杂系统的关键成功因素。最后,将计算结果与传统DEMATEL方法的结果进行对比分析。结果表明,安全投入力度加大、安全意识的转变、安全监管与督导力度的加强、法律法规与管理机制的持续健全完善、科技创新引领智慧安全、安全风险分级管控和隐患排查的双重预防为实现民航安全复杂系统的关键成功因素。与传统DEMATEL方法相比,提出的混合模型有效减少了549次专家决策,识别结果更符合民航实际情况。

考虑中介平台收益的企业-投资商双边匹配决策方法

针对概率不确定语言环境下的企业-投资商双边匹配问题,提出了一种考虑中介平台收益的双边匹配模型.首先,定义了可信度,对匹配主体偏好信息的可靠度进行测量,进而根据可信度给出了概率不确定语言术语集得分值的计算公式;其次,通过改进的TODIM方法得到满意度矩阵;然后,给出了中介平台费用函数并规范化其函数,基于此,将企业与投资商匹配满意度最大化以及中介平台收益最大化作为目标,构建双边匹配优化模型并求解;最后,通过某投资理财平台的案例,证明了该方法的可行性及有效性.

不确定语言广义加权Heronian平均算子及决策应用

在实际多属性决策问题中,属性间有时会存在一定的关联关系,且属性值有时以不确定语言的形式给出.为解决不确定语言环境下属性间存在关联关系的多属性决策问题,首先给出不确定语言广义加权Heronian平均(uncertain linguistic generalized weighted Heronian mean,ULGWHM)算子,并研究该算子的性质,包括幂等性、有界性、单调性、置换性及极限性质,然后给出了基于该算子的多属性决策方法,最后通过实例说明了基于ULGWHM算子的多属性决策方法的可行性.

HULZNs环境下基于语义偏好参数的多准则群决策模型

针对语义分布不平衡环境下的语义偏好和决策信息的复杂性问题,为提高决策的准确性,提出了一个新型不平衡语言尺度函数.它可通过改变语义偏好参数来调节相邻语义之间的偏差,适用于不同的决策环境,并对相关性质进行了证明.在犹豫不确定语言型Z-numbers(hesitant uncertain linguistic Z-numbers,简称HULZNs)的环境下,定义了两个HULZNs之间的距离以及部分运算,建立了优先加权平均运算算子和一种新型多准则群决策模型.最后,对提出的新模型利用实例进行了分析,验证了方法的有效性和可行性.

异构偏好信息下的主客方协作式群体评价方法及应用

针对异构偏好信息下的主客方协作式群体评价问题,提出一种新的基于两次协作过程的群体评价方法。首先,分别使用不确定语言和区间灰数对主客双方的意见进行描述,并给出各评价值的协作初始得分;其次,由协作初始得分计算主方信息“完备度”和客方信息“诚信度”,并运用相应的调节因子实现对双方各评价值的修正,完成双方的“第一次协作”;再次,运用灰关联聚类和TDWA算子分别对修正后评价信息的TOPSIS综合贴近度进行聚类和集结,完成双方的“第二次协作”并得出评价对象的综合评价得分;最后,以一个实际例子验证所提方法的有效性与可行性。对比分析结果表明,两次协作过程可有效增强双方评价信息交互的精度与深度,稳步实现异构偏好意见的双向交互与有机融合,从而提升评价结果的合理性和稳定性。

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。

基于多粒度不确定语言和前景理论的应急方案选择

针对突发事件的复杂性和决策团队损失规避的心理行为特征,提出了基于多粒度不确定语言和前景理论的应急方案选择方法。首先,决策成员使用偏好的不确定语言短语表征各项关键指标的重要性,使用转换函数对这些多粒度不确定语言信息进行一致性转换;在此基础上,通过不确定的扩展加权平均算子得到群体评估向量,进而采用不确定语言决策理论得到各项关键指标的权重向量;引入前景理论的思想,计算采用不同备选方案情况时各项关键指标不同场景的价值和感知权重;进一步,将采用不同备选方案时关键指标的感知价值和权重向量集结,得到各个备选方案的综合感知价值,并据此确定最优的应急方案;最后,通过一个实例验证了所提方法的实用性和有效性。

基于不确定语言信息的群决策方法及其应用

对于属性权重和属性值均以不确定语言信息形式给出的多属性群决策问题进行了研究,提出了基于ULWM算子和ULHA算子的多属性群决策方法。首先定义了ULWM算子,并且讨论了该算子的一些性质。通过ULWM算子集结决策方案的综合属性评估值,ULHA算子集结决策方案的群体综合属性评估值。然后利用可能度公式对于所有决策方案综合评估值进行比较得到可能度矩阵,最后对模糊互补判断矩阵排序得到所有决策方案的排序信息。实例表明了该方法的有效性。