群决策中多形式偏好信息的转换及一致性分析

描述序关系、效用值、互补判断矩阵、互逆判断矩阵4种形式的偏好信息,给出将前3种偏好信息转换到互补判断矩阵的公式。在集结前,对转换后的互补判断矩阵进行一致性分析,如果没有达到规定的一致性指标,找出该矩阵中一致性最差的元素,并提交给其决策者进行调整,直到达到一致性指标。通过一个算例说明该方法的应用过程。     

模糊互补判断矩阵一致性检验和改进方法研究

针对模糊互补判断矩阵的一致性修正问题,指出了模糊互补判断矩阵一致性修正方法的不足,从模糊一致矩阵传统定义出发,讨论了检验模糊判断矩阵是否满足完全一致性的方法,推导出模糊一致性指标,并给出了模糊判断矩阵一致性改进的方法,从理论上分析了该算法的可行性,这种算法不仅简便实用,而且为专家对原始判断信息进行针对性修正提供了参考依据.     

基于残缺互补判断矩阵的交互式群决策方法

研究基于残缺互补判断矩阵的群决策问题.首先利用残缺互补判断矩阵的积型一致性,将每个残缺互补判断矩阵拓展为完整的互补判断矩阵(简称拓展互补判断矩阵),并将所有个体拓展互补判断矩阵集成为群体互补判断矩阵;然后基于群体互补判断矩阵与个体拓展互补判断矩阵之间的偏离阈值同决策者进行交互,使得决策者的意见尽可能协调一致;最后给出一种基于残缺互补判断矩阵的交互式群决策方法,并进行了算例分析.     

基于一致性指标的两类不确定偏好信息集结

研究了两类区间数判断矩阵偏好信息的集结问题.首先,基于Saaty提出的数字互反判断矩阵一致性检验指标(CR),给出了区间数互反判断矩阵的满意一致性条件;然后利用互反与互补判断矩阵之间的关系求解出数字互补判断矩阵的一致性指标(CGCI),并在此基础上给出了区间数互补判断矩阵的满意一致性条件;最后建立了一致性指标最大的两类区间数判断矩阵偏好信息的集结模型,并用此模型解决了供应链中伙伴企业的选择问题.     

区间互反判断矩阵满意一致性的新定义

定义区间互反判断矩阵的区间一致性指标,计算 n 维的平均随机区间一致性指标的值。提出区间互反判断矩阵满意一致性的新定义,给出一种新的区间互反判断矩阵满意一致性的检验方法,用算例验证新的满意一致性定义的有效性。     

模糊互补判断矩阵一致性检验和改进方法研究

针对模糊互补判断矩阵的一致性修正问题,指出了模糊互补判断矩阵一致性修正方法的不足.从模糊一致矩阵传统定义出发,讨论了检验模糊判断矩阵是否满足完全一致性的方法,推导出模糊一致性指标,并给出了模糊判断矩阵一致性改进的方法.从理论上分析了该算法的可行性.这种算法不仅简便实用,而且为专家对原始判断信息进行针对性修正提供了参考依据.

     

直觉语义决策模型应用于区块链风险投资

为了全面且精确地表达和处理复杂风险投资决策问题中的评价信息,构建了直觉模糊语义决策模型,并将其应用于区块链风险投资过程。首先,给出了直觉模糊语义互补判断矩阵(IFLCJM)的加性一致性概念,并建立了加性一致性IFLCJM与规范化直觉模糊权重向量之间的转化关系;其次,构造最优化模型计算IFLCJM与其完全加性一致性IFLCJM之间的差距,并以此来衡量IFLCJM的一致性水平;最后,设计了基于一致性提升算法的直觉模糊语义决策模型,并将其应用于区块链风险投资问题,结果验证了模型的合理性和可靠性。     

三角模糊数互补判断矩阵的一致性及其排序研究

研究三角模糊数互补判断矩阵的性质和排序问题．建立了三角模糊数互反判断矩阵与互补判断矩阵之间的相互转化关系,给出了三角模糊数互补判断矩阵完全一致性、严格强传递性以及弱传递性的概念,并研究了它们之间的关系,论证了完全一致性等定义的合理性,构建了基于最小二乘的三角模糊数互补判断矩阵排序方法．算例分析表明,该方法是可行而有效的。     

基于一致性指标的两类不确定偏好信息集结

研究了两类区间数判断矩阵偏好信息的集结问题.首先,基于Saaty提出的数字互反判断矩阵一致性检验指标(CR),给出了区间数互反判断矩阵的满意一致性条件;然后利用互反与互补判断矩阵之间的关系求解出数字互补判断矩阵的一致性指标(CGCI),并在此基础上给出了区间数互补判断矩阵的满意一致性条件;最后建立了一致性指标最大的两类区间数判断矩阵偏好信息的集结模型,并用此模型解决了供应链中伙伴企业的选择问题.

     

区间数互补判断矩阵的一致性

研究了区间数互补判断矩阵的一致性;定义了区间数互补判断矩阵的完全一致性、强一致性、一致性和满意一致性的概念;讨论了定义之间的关系;给出了强一致性判别方法以及3种一致性和满意一致性的判别方法.最后用算例验证了所提出方法的有效性和适用性.     

Preference relations based on hesitant-intuitionistic fuzzy information and their application in group decision making

Preference relations are a powerful quantitative decision approach that assists decision makers in expressing their preferences over alternatives. In real-life applications, decision makers may not be able to provide exact preference information with crisp numbers. To solve this problem, a hesitant-intuitionistic fuzzy number (Hesitant-IFN) is proposed in this paper, and a proposal for the hesitant-intuitionistic fuzzy preference relation (Hesitant-IFPR) and its complementary form (Hesitant-IFCPR) for uncertain preference information are presented. Compared with other preference relations, the proposed relations use hesitant fuzzy elements (HFEs) to express the priority intensities of decision makers and produce the corresponding non-priority intensities by a conversion formula. In addition, we have deduced the operational laws and comparative methods of Hesitant-IFNs and used such information to investigate the corresponding aggregation operators and the approximate consistency tests. Next, we have constructed a group decision-making approach under a hesitant-intuitionistic fuzzy environment. Finally, two case studies are presented to illustrate the preference relations, the approximate consistency tests and the group decision method.     

三角模糊数互补判断矩阵排序的最小方差法

研究偏好信息为三角模糊数互补判断矩阵形式给出的方案排序方法.根据三角模糊数互补判断矩阵完全一致性的概念,建立了一个基于最小方差的非线性规划模型.通过求解该模型,得到三角模糊数互补判断矩阵的权重向量,并利用三角模糊数排序公式对决策方案进行排序.最后通过算例分析表明了所提出的方法是可行而有效的.     

FOWG算子在X射线检测方案选择中的应用

针对当前X射线数字化实时成像检测技术的广泛应用，研究了决策信息以三角模糊数互补判断矩阵形式给出的有限方案决策问题，给出了一种模糊有序加权平均（FOWA）算子，利用该算子对以三角模糊数互补判断矩阵形式给出的判断信息进行了集结。基于FOWG算子及互补判断矩阵排序公式，给出了一种对决策方案进行排序和择优的算法。利用该算法对长输管道钢质对接焊缝X射线数字化实时成像检测方案进行排序和择优，最后通过算例说明了该方法的有效性和实用性。     

Methods for fuzzy complementary preference relations based on multiplicative consistency

To improve the consistency of a preference relation is a hot topic in decision making. Wang and Chen (2008) gave a simple method to construct the complete fuzzy complementary preference relation from only n − 1 pairwise comparisons. However, some values may not be in the defined scope and need to be transformed, and thus some original information may be lost in the transformation process. In this paper, we propose a new method to avoid this issue based on the multiplicative consistency of the fuzzy complementary preference relation and apply it to fuzzy Analytic Hierarchy Process (AHP). An example is further given to illustrate our method.     

梯形模糊互反判断矩阵的一致性及修正

研究具有严格偏好关系的梯形模糊互反判断矩阵满意一致性的判定及其修正方法。首先,将梯形模糊互反判断矩阵转化为判断矩阵和排列矩阵;然后,根据梯形模糊互反判断矩阵的排列矩阵来判定是否具有满意一致性;基于梯形模糊数的类质心,给出将排列矩阵转化成上三角矩阵的方法,从而实现方案的排序;最后,通过项目评估问题验证了所提出方法的实用性。     

Group Decision Making With Consistency of Intuitionistic Fuzzy Preference Relations Under Uncertainty

Intuitionistic fuzzy preference relation (IFPR) is a suitable technique to express fuzzy preference information by decision makers (DMs). This paper aims to provide a group decision making method where DMs use the IFPRs to indicate their preferences with uncertain weights. To begin with, a model to derive weight vectors of alternatives from IFPRs based on multiplicative consistency is presented. Specifically, for any IFPR, by minimizing its absolute deviation from the corresponding consistent IFPR, the weight vectors are generated. Secondly, a method to determine relative weights of DMs depending on preference information is developed. After that we prioritize alternatives based on the obtained weights considering the risk preference of DMs. Finally, this approach is applied to the problem of technical risks assessment of armored equipment to illustrate the applicability and superiority of the proposed method.      

An interactive method for fuzzy multiple attribute group decision making

In this paper, we develop an interactive method for multiple attribute group decision making under fuzzy environment. The method can be used in situations where the information about attribute weights is partly known, the weights of decision makers are expressed in exact numerical values or triangular fuzzy numbers, and the attribute values are triangular fuzzy numbers. The method transforms fuzzy decision matrices into their expected decision matrices, constructs the corresponding normalized expected decision matrices by two simple formulas, and then aggregates these normalized expected decision matrices into a complex decision matrix. Moreover, the decision makers are asked to provide their preferences gradually in the course of interactions. By solving linear programming models, the method diminishes the given alternative set gradually, and finally finds the most preferred alternative. By using the method, the decision makers can provide and modify their preference information gradually in the process of decision making so as to make the decision result more reasonable. The method can not only reflect the importance of the given arguments and the ordered positions of the arguments, but also relieve the influence of unfair arguments on the decision result. Finally, a practical problem is used to illustrate the developed method.     

一种软件构件的非功能属性量化评价方法

针对软件构件的非功能属性因具有模糊性而难以量化评价的问题,提出了一种群决策多指标模糊评价方法。该方法通过分析构件的非功能属性的分层度量指标,将层次分析法应用于指标的权重计算以减少人为因素的干扰,利用群决策获取模糊评价矩阵,给出指标语气算子的对应数值以便真实和贴切地反映评价意图;引入模糊集重心概念,把以模糊数表示的综合评价结果转换为明晰数,以利于构件的选择与排序。最后,给出了应用实例,验证了方法的有效性。