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1.
决策个体之间的共识达成是提升群决策可信性的重要保证. 为处理极端值导致的决策失效问题,首先将信息进行预处理,然后应用定义的个体与群体之间的共识测度, 构建可以定位与修正非共识决策信息的直觉模糊共识模型, 并建立一种多属性群决策方法,以确保个体信息集结之前达成阈值条件下的共识.通过对投资对象选择的实例研究, 证明了该方法的有效性并选出最优方案.  相似文献   

2.
本文提出了基于语言分布评估加权平均(DAWA)算子的多属性群决策方法;定义了个体决策者评价结果与决策群体评价结果的次序一致性和数值一致性测度,以此分析决策群体评价结果的可靠性;最后,通过具体实例验证了群决策方法的有效性和实用性,分析了个体决策者评价结果与决策群体评价结果的次序一致性和数值一致性。  相似文献   

3.
AHP一致性的概率检验法   总被引:2,自引:0,他引:2  
Saaty的层次分析决策方法(AHP)是目前较为流行的多属性目标决策方法.AHP方法的一致性问题是其理论研究中心之一.通过Saaty的判断属性集合和一致性水平,很容易验证判断矩阵的一致性程度是否满足.但是对于Saaty的一致性水平,要求C.R≤0.1的内涵还需要进一步的揭示.研究Saaty的一致性原理,并给出检验矩阵一致性的概率方法,简称α一致性方法.  相似文献   

4.
多属性群决策算法及一致性分析研究   总被引:8,自引:1,他引:7  
在多属性群决策中 ,集结群体意见之前必须先对群体的决策数据进行一致性分析 ,以确保群体作出的决策符合客观实际 .提出了群决策的三种三维层次模型 ;用欧几里得距离 ( Euclidean Distance)表示个人决策中方案的评价值 ;然后设置一致性指标值α,作为群体数据一致性的判断依据 ;提出了满足一致性基础上的一种群决策方法 ;最后用实例说明了算法的使用步骤 .  相似文献   

5.
在区间犹豫模糊多属性决策问题中,针对区间犹豫模糊元中人为添加元素从而影响最终决策结果客观性的问题,文章提出一种基于群体一致性的区间犹豫模糊多属性决策方法.首先,根据区间犹豫模糊元中的元素个数以及元素间的差异定义区间犹豫度,并基于犹豫度定义了区间群体一致性;然后,基于群体一致性构建属性权重确定模型,并确定各属性的权重.最后,计算各备选方案到理想点的距离,运用TOPSIS方法对备选方案进行排序,并通过一个算例证明文章方法的可行性和有效性.  相似文献   

6.
针对基于Vague集信息的多属性群决策专家水平评判问题提出了两种评判方法.首先引进了基于Vague集信息的多属性群决策信息体(即决策信息体)的相关概念,通过决策信息体构造了基于Vague集信息的一致性决策矩阵及模糊熵,其次利用Vague集信息的相似度量以及Vague集信息的模糊熵两种信息不确定性度量方法,对基于Vague集信息的多属性群决策专家水平评判问题提出了两种评判方法,即统计分析方法和模糊熵分析方法,对专家的评判水平进行排序.最后,通过一个算例说明两种方法的一致性、有效性和实用性.  相似文献   

7.
一种新的无结构决策方法—属性层次模型AHM.与Saaty提出的层次分析法AHP是不同的.AHM既不需要计算特征向量,也不需要进行一致性检验,运算量小,科学性强.通过对一个质量评估问题的分析,说明属性层次模型AHM是简便易行、行之有效的决策方法.  相似文献   

8.
一致性检验是犹豫模糊集领域的一个热点问题,数据的一致性直接影响到犹豫模糊集评价的科学性和有效性.论文采用距离测度的方法研究犹豫模糊集的一致性问题,通过分析每个模糊元与其对应的属性综合决策值之间的差异,得出各属性的综合距离测度.同时,充分考虑专家意见在犹豫模糊集中的影响效应,以相对可信度为权重对犹豫模糊集的一致性进行分析.最后,利用数值案例验证了所提方法的有效性和可靠性.  相似文献   

9.
针对概率语言多属性群决策问题,提出了基于互动与反馈的概率语言多属性群决策模型。首先定义了概率语言的距离测度和概率语言矩阵的一致性测度,以决策者的总体一致性测度确定决策者的客观权重,结合决策者的主观权重以主客观组合赋权法确定决策者的最终权重;结合概率语言的距离测度改进灰色关联度法,以归一化的属性关联度确定属性权重;为达到群决策中决策者的最大共识度,建立了具有互动与反馈过程的决策模型;最后提出了基于互动与反馈的概率语言多属性群决策模型的决策步骤,并且通过算例分析证明了该模型的有效性与可行性。  相似文献   

10.
针对投影测度下的属性值和属性权重均为单值中智集的多属性群决策问题,提出了一种基于投影的群决策一致性合成方法。该方法以群体评价均值矩阵和群体评价正、负理想值矩阵为群体评价的参考基准,根据投影测度,构建了衡量决策者个体评价与群体评价一致性程度的投影贴近度公式;进而以决策者的相对一致性程度和决策者重要性合成得到策者权重,并构造加权规范化的群体最终决策矩阵;然后以单值中智集得分函数求解各方案的最终得分并排序;并给出详细的决策步骤,最后通过算例同其他方法进行了对比分析,表明本文方法的可行、有效。  相似文献   

11.
Preference relations are a powerful tool to address decision-making problems. In some situations, because of the complexity of decision-making problems and the inherent uncertainty, the decision makers cannot express their preferences by using numerical values. Interval linguistic preference relations, which are more reliable and informative for the decision-makers’ preferences, are a good choice to cope with this issue. Just as with the other types of preference relations, the consistency and consensus analysis is very importance to ensure the reasonable ranking order by using interval linguistic preference relations. Considering this situation, this paper introduces a consistency concept for interval linguistic preference relations. To measure the consistency of interval linguistic preference relations, a consistency measure is defined. Then, a consistency-based programming model is built, by which the consistent linguistic preference relations with respect to each object can be obtained. To cope with the inconsistency case, two models for deriving the adjusted consistent linguistic preference relations are constructed. Then, a consistency-based programming model to estimate the missing values is built. After that, we present a group consensus index and present some of its desirable properties. Furthermore, a group consensus-based model to determine the weights of the decision makers with respect to each object is established. Finally, an approach to group decision making with interval linguistic preference relations is developed, which is based on the consistency and consensus analysis. Meanwhile, the associated numerical examples are offered to illustrate the application of the procedure.  相似文献   

12.
Group decision making through the AHP has received significant attention in contemporary research, the primary focus of which has been on the issues of consistency and consensus building. In this paper, we concentrate on the latter and present a two-phase algorithm based on the optimal clustering of decision makers (members of a group) into sub groups followed by consensus building both within sub groups and between sub groups. Two-dimensional Sammon’s mapping is proposed as a tool for generating an approximate visualization of sub groups identified in multidimensional vector space, while the consensus convergence model is suggested for reaching agreement amongst individuals in and between sub groups. As a given, all decision makers evaluate the same decision elements within the AHP framework and produce individual scores of these decision elements. The consensual scores are obtained through the iterative procedure and the final scores are declared as the group decision. The results of two selected numerical examples are compared with two sets of results: the results obtained by the commonly used geometric mean aggregation method and also the results obtained if the consensus convergence model is applied directly without the prior clustering of the decision makers. The comparisons indicated the expected differences among the aggregation schemes and the final group scores. The matrices of respect values in the consensus convergence model, obtained for cases when the decision makers are optimally clustered and when they are not, show that in the latter case the decision makers receive lower weights of respect from other members in the group. Various tests showed that our approach is efficient in cases when no clusters can be visually and undoubtedly identified, especially if the number of group members is high.  相似文献   

13.
针对不确定加型语言偏好信息下的群决策问题,提出一种基于累积共识贡献的自适应式语言共识决策方法。首先,将不确定加型语言偏好转化为不确定二元语义偏好,定义个体一致度与个体共识偏度,并利用它们构建确定专家初始权重的优化模型;然后,利用不确定二元语义的可能度构造集结模糊评价矩阵以及方案的集结群体偏好,提出专家累积共识贡献测度和群体共识测度,通过对拥有较少合作的专家权重进行惩罚让群体自适应地达成共识,无需强迫专家修改其观点,提出一种群体共识决策方法对方案排序择优。最后,通过一个算例说明方法的可行性和有效性。  相似文献   

14.
针对群决策中基于区间数偏好信息的共识性问题,给出了一种新的分析方法.首先给出了有关区间数和区间数决策矩阵的定义及若干性质;然后.通过定义有关专家群体判断关于方案针对指标的落影函数和专家群体关于方案针对指标的重心值,给出了群决策中基于区间数决策矩阵的共识性的分析方法和非共识的调整方法.最后,通过一个算例说明给出的分析方法.  相似文献   

15.
The consistency of the pairwise comparison matrix (PCM) has been extensively studied in the Analytic Hierarchy Process. Most of the existing approaches for the consistency test of the PCM are based on the consistency ratio threshold (0.1) introduced by Saaty (1977). To accurately measure the consistency level of the PCM, a statistical approach based on the significance level is proposed in this paper by combining the hypothesis test and the random consistency index. The proposed statistical approach is applied to an education evaluation problem in order to demonstrate the rationality and reliability of it.  相似文献   

16.
针对层次分析法判断矩阵一致性问题,提出了一种新的排序标度方法,证明了采用新方法形成的判断矩阵具有一致性,最后通过实例运用说明了此方法的可行性和有效性.  相似文献   

17.
Increasingly, fuzzy partitions are being used in multivariate classification problems as an alternative to the crisp classification procedures commonly used. One such fuzzy partition, the grade of membership model, partitions individuals into fuzzy sets using multivariate categorical data. Although the statistical methods used to estimate fuzzy membership for this model are based on maximum likelihood methods, large sample properties of the estimation procedure are problematic for two reasons. First, the number of incidental parameters increases with the size of the sample. Second, estimated parameters fall on the boundary of the parameter space with non-zero probability. This paper examines the consistency of the likelihood approach when estimating the components of a particular probability model that gives rise to a fuzzy partition. The results of the consistency proof are used to determine the large sample distribution of the estimates. Common methods of classifying individuals based on multivariate observations attempt to place each individual into crisply defined sets. The fuzzy partition allows for individual to individual heterogeneity, beyond simply errors in measurement, by defining a set of pure type characteristics and determining each individual's distance from these pure types. Both the profiles of the pure types and the heterogeneity of the individuals must be estimated from data. These estimates empirically define the fuzzy partition. In the current paper, this data is assumed to be categorical data. Because of the large number of parameters to be estimated and the limitations of categorical data, one may be concerned about whether or not the fuzzy partition can be estimated consistently. This paper shows that if heterogeneity is measured with respect to a fixed number of moments of the grade of membership scores of each individual, the estimated fuzzy partition is consistent.  相似文献   

18.
The Analytic Hierarchy Process (AHP) is a popular multicriteria decision-making approach but the ease of AHP paired comparison data collection entails the problem that consistency restrictions have to be fulfilled for the data evaluation task. Quite a lot of consistency improvement techniques are available, however, this note explains why consistency adjustments are not necessarily helpful for computing acceptable weights for the determination of the underlying overall objective function.  相似文献   

19.
The pair-wise comparison matrix (PCM) is widely used in multi-criteria decision making methods. If the PCM is inconsistent, the resulting priority vector is not reliable. Hence, it is necessary to measure the level of the inconsistency of the PCM. There are two approaches for testing the consistency of the PCM: deterministic approaches and statistical or stochastic approaches. In this paper, an improved statistical approach to test the consistency of the PCM is proposed, which combines hypothesis test and maximum likelihood estimation. The proposed statistical approach is flexible and reliable because it sets a suitable significance level according to different situations. Two numerical examples are introduced to illustrate the proposed statistical approach.  相似文献   

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