基于模糊判断矩阵的两阶段群决策方法

针对多属性群决策问题,提出一种两阶段决策分析方法。通过分析积型模糊一致性判断矩阵和模糊判断矩阵的排序向量之间的偏差,建立并求解一个规划模型,得到专家模糊判断矩阵的排序向量。由最小化专家模糊判断矩阵的排序向量与专家群组排序向量的偏差,再次建立并求解一个规划模型,得到反映专家群组偏好的排序向量,从而得出基于模糊判断矩阵的两阶段群决策方法。通过2个算例说明了该方法的可行性与有效性。     

AHP中群决策的几何平均超传递近似法

研究了层次分析法（AHP）群决策中判断矩阵的合并问题.首先,论证了层次分析法中m个判断矩阵的几何平均矩阵是判断矩阵,以及m个判断矩阵的加权几何平均复合判断矩阵是判断矩阵;然后,提出了层次分析法中简化的超传递近似法及群决策的几何平均超传递近似法,该方法不需要一致性检验,同时又保持了专家的原始意见;最后,通过一个实例验证了该方法的有效性和实用性.     

A Modified TOPSIS Method for Obtaining the Associated Weights of the OWA‐Type Operators

The ordered weighted averaging (OWA) operator proposed by Yager and its some extensions have been extensively utilized to perform the mean‐type aggregation of individual preference relations in group decision making. An important issue in the theory of the OWA‐type operators is the determination of the associated weights. In the present paper, the technique for order preference by similarity to ideal solution is modified to propose a new method for generating the associated weights under the environment of a group of additive reciprocal matrices. First, a consistent additive reciprocal matrix is obtained from each additive reciprocal matrix. It is further used to generate an ideal additive reciprocal matrix by using the arithmetic averaging operator. Then, a similarity degree between every additive reciprocal matrix and the ideal one is defined. Based on the similarity degree, the associated weights are determined by making use of an exponential function and they show that more importance is given to that with more similarity degree. Finally, a numerical example is carried out to illustrate the given method.     

群决策中两类三端点区间数判断矩阵的集结方法

研究群决策过程中三端点区间数互反判断矩阵和三端点区间数互补判断矩阵的集结. 采用OWA(Ordered weighted averaging) 方法将决策者的偏好信息集结为两个三端点区间数判断矩阵. 基于三端点区间数判断矩阵的完全一致性概念, 建立三端点区间数判断矩阵的权重求解模型. 根据群决策背景下专家群最大一致的目标, 建立求解专家群体偏好权重的模型. 在第二阶段建立群偏好权重分布范围估计模型, 最后通过可能度方法以排定各方案的最终优劣顺序.     

基于犹豫语言决策模型的数据产品服务商选择

针对属性值为犹豫模糊语言元的多属性决策问题,建立基于犹豫模糊语言可能度的线性分配决策模型。首先,基于犹豫模糊语言元的包络转化方法,分别定义了犹豫模糊语言元间的可能度和相对差异指数等概念;其次探究发现可能度矩阵和相对差异矩阵均为互补判断矩阵,并设计了犹豫模糊语言元的最优度计算公式;最后,在犹豫模糊语言信息环境下,构建了一种新的线性分配决策模型用以确定各备选方案的综合最优度,进而遴选出最优方案。实验结果表明,提出的决策模型是可行和有效的。     

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.     

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。     

基于前景理论的犹豫模糊多属性群决策方法

针对属性指标值为犹豫模糊信息且属性权重完全未知的多属性群决策问题,提出一种基于新的决策参考点和前景理论的多属性群决策方法。将犹豫模糊决策矩阵转变为区间模糊决策矩阵,并结合t-分布估计方法,构建期望得分函数值,将其作为决策参考点;基于属性值得分函数与决策参考点之间的差异,确定价值函数,进而得到前景价值综合矩阵;利用同一属性下的前景价值方差计算属性的权重,并基于前景理论计算各方案的加权前景价值,进而对决策方案进行优劣排序;通过对云计算产品的选择实例验证提出的决策方法的可行性与有效性。     

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。     

基于不同类型残缺判断矩阵的群决策方法

定义了一系列残缺不确定判断矩阵的概念,并且定义了一种连续区间数据有序加权几何（C-OWG）算子．利用连续区间数据有序加权平均（C-OWA）子和C-OWG算予等转化途径把不同类型的残缺不确定判断矩阵均一致化为残缺期望值互补判断矩阵,进而提出一种基于不同类型残缺判断矩阵的群决策方法．最后通过实例验证了方法的可行性和有效性．     

基于方案偏好和部分权重信息的模糊多属性决策方法

研究了只有部分权重信息且决策者对方案的偏好信息以三角模糊数互反判断矩阵形式给出的模糊多属性决策问题.首先为得到属性权重,给出一种结合主观模糊偏好信息和客观决策信息的极小化极大偏差模型;然后,运用加性加权法求出各方案的模糊综合属性值,并利用已有的三角模糊数排序公式求得决策方案的排序;最后,通过算例说明了该方法的可行性和有效性.     

A common framework for deriving preference values from pairwise comparison matrices

Pairwise comparison is commonly used to estimate preference values of finite alternatives with respect to a given criterion. We discuss 18 estimating methods for deriving preference values from pairwise judgment matrices under a common framework of effectiveness: distance minimization and correctness in error free cases. We point out the importance of commensurate scales when aggregating all the columns of a judgment matrix and the desirability of weighting the columns according to the preference values. The common framework is useful in differentiating the strength and weakness of the estimated methods. Some comparison results of these 18 methods on two sets of judgment matrices with small and large errors are presented. We also give insight regarding the underlying mathematical structure of some of the methods.Scope and purposePairwise comparison is commonly used to estimate preference values of finite alternatives with respect to a given criterion. This is part of the model structure of the analytical hierarchy process, a widely used multicriteria decision-making methodology. The main difficulty is to reconcile the inevitable inconsistency of the pairwise comparison matrix elicited from the decision makers in real-world applications. We discuss 18 estimating methods for deriving preference values from pairwise judgment matrices under a common framework of effectiveness: the common concepts of minimizing aggregated deviation and correctness in error free cases. The common framework is useful in differentiating the strength and weakness of these methods. For each of these methods, we point out their individual strength in decisional effectiveness. Some comparison results of these 18 methods on two sets of judgment matrices with small and large errors are presented. We also give insight regarding the underlying mathematical structure of some of the methods. We recommend the simple geometric mean method with the stronger feature of distance minimization and the simple normalized column sum method that is based on the simple ideas of commensurate unit and column sum. These two methods have closed-form formulas for easy calculation and good performance on both sets of judgment matrices with small and large errors.     

基于犹豫语言判断矩阵的数据产品选择研究

犹豫语言判断矩阵作为一种新的判断矩阵,能够有效地处理决策信息为语言变量且决策者态度犹豫不行的决策问题。针对犹豫模糊语言信息环境下的数据产品选择问题,构建了一种基于犹豫语言判断矩阵的数据产品选择方法。该方法引入了犹豫语言判断矩阵的一些相关概念,包括加性一致性、一致性指数、可接受一致性;研究了犹豫语言判断矩阵一致性判定方法和特征矩阵的构造方法,并设计了一种收敛性算法用以改进犹豫语言判断矩阵的一致性;建立了基于犹豫语言判断矩阵的决策模型,并通过数据产品的选择实例说明提出的决策方法是合理和有效的。     

Classification of imprecise data using interval Fisher discriminator

In this paper, an imprecise data classification is considered using new version of Fisher discriminator, namely interval Fisher. In the conventional formulation of Fisher, elements of within‐class scatter matrix (related to covariance matrix between clusters) and between‐class scatter matrix (related to covariance matrix of centers of clusters) have single values; but in the interval Fisher, the elements of matrices are in the interval form and can vary in a range. The particle swarm optimization search method is used for solving a constrained optimization problem of the interval Fisher discriminator. Unlike conventional Fisher with one optimal hyperplane, interval Fisher gives two optimal hyperplanes thereupon three decision regions are obtained. Two classes with regard to imprecise scatter matrices are derived by decision making using these optimal hyperplanes. Also, fuzzy region lets us help in fuzzy decision over input test samples. Unlike a support vector classifier with two parallel hyperplanes, interval Fisher generally gives us two nonparallel hyperplanes. Experimental results show the suitability of this idea. © 2011 Wiley Periodicals, Inc.     

A method based on distance measure for interval-valued intuitionistic fuzzy group decision making

In this paper we introduce some relations and operations of interval-valued intuitionistic fuzzy numbers and define some types of matrices, including interval-valued intuitionistic fuzzy matrix, interval-valued intuitionistic fuzzy similarity matrix and interval-valued intuitionistic fuzzy equivalence matrix. We study their properties, develop a method based on distance measure for group decision making with interval-valued intuitionistic fuzzy matrices and, finally, provide an illustrative example.     

基于语言判断矩阵的专家群体判断一致性分析

针对群决策中基于语言判断矩阵的专家群体判断一致性问题,提出了一种分析方法．首先给出有关语言判断矩阵,导出矩阵和相客性的若干定义,得出了语言判断矩阵具有完全一致性或满意一致性的充要条件,其相应的导出矩阵也具有同样的结论;然后通过定义有关专家群体判断各个方案以及专家群体判断的一致性指标,给出了专家群体判断一致性的判别方法及专家群体判断不一致的调整方法;最后通过一个算例说明了所提出方法的有效性。     

Analytic network process in risk assessment and decision analysis

In risk assessment and decision analysis, the analytical network process (ANP) is widely used to assess the key factors of risks and analyze the impacts and preferences of decision alternatives. There are lots of comparison matrices for a complicated risk assessment problem, but a decision has to be made rapidly in emergency cases. However, in the ANP, the reciprocal pairwise comparison matrices (RPCM) are more complicated and difficult than AHP. The consistency test and the inconsistent elements identification need to be simplified. In this paper, a maximum eigenvalue threshold is proposed as the consistency index for the ANP in risk assessment and decision analysis. The proposed threshold is mathematically equivalent to the consistency ratio (CR). To reduce the times of consistency test, a block diagonal matrix is introduced for the RPCM to conduct consistency tests simultaneously for all comparison matrices. Besides, the inconsistent elements can be identified and adjusted by an induced bias block diagonal comparison matrix. The effectiveness and the simplicity of the proposed maximum eigenvalue threshold consistency test method and the inconsistency identification and adjustment method are shown by two illustrative examples of emergent situations.     

基于集值决策属性的集值信息系统

定义了决策属性也是集合子集的集值决策信息系统,给出了基于集值决策属性的协调集值决策信息系统的定义,得到了协调集值决策信息系统属性约简的判定定理和辨识矩阵,并讨论了在属性约简中起不同作用的属性分类及其特征。定义了不协调集值决策信息系统的分配协调集,给出了基于集值决策属性的不协调集值决策信息系统属性约简的方法。     

Evidential reasoning‐based nonlinear programming model for MCDA under fuzzy weights and utilities

In a multiple‐criteria decision analysis (MCDA) problem, qualitative information with subjective judgments of ambiguity is often provided by people, together with quantitative data that may also be imprecise or incomplete. There are several uncertainties that may be considered in an MCDA problem, such as fuzziness and ambiguity. The evidential reasoning (ER) approach is well suited for dealing with such MCDA problems and can generate comprehensive distributed assessments for different alternatives. Many researches in dealing with imprecise or uncertain belief structures have been conducted on the ER approach. In this paper, both triangular fuzzy weights of criteria and fuzzy utilities assigned to evaluation grades are introduced to the ER approach, which may be incurred in several circumstances such as group decision‐making situation. The Hadamard multiplicative combination of judgment matrix is extended for the aggregation of triangular fuzzy judgment matrices, the result of which is applied as the fuzzy weights used in the fuzzy ER approach. The consistency of the aggregated triangular fuzzy judgment matrix is also proved. Several pairs of ER‐based programming models are designed to generate the total fuzzy belief degrees and the overall expected fuzzy utilities for the comparison of alternatives. A numerical example is conducted to show the effectiveness of the proposed approach. © 2009 Wiley Periodicals, Inc.     

基于权重集结和相对优势关系的多属性决策方法

分析多属性决策方法中决策矩阵规范化和属性权重计算等步骤可能对决策方法合理性造成的不良影响,为克服这些不良影响,提出一种新的多属性决策方法.该方法采用群决策模式进行赋权,在对专家意见进行一致性分析的基础上,集结各位专家给出的属性权重,通过定义备选方案在属性值为实数、区间数和语言值等不同类型属性上的相对优势关系构造判断矩阵,并以此建立方案效用值计算的线性目标规划模型,从而实现备选方案的评价和排序.实例研究表明了所提出方法的可行性和有效性.