Scale transitivity in the AHP

Transitivity is important in multicriteria decision-making. The analytic hierarchy process (AHP), as one of the widely used decision analysis tools, is criticized since it suffers from scale intransitivity. This paper first reviews and compares different scales from different aspects, then discusses the transitivity of AHP scales and derives a scale based on the transitivity, so it is naturally transitive. Besides, two approaches are provided to determine the scale parameter for the derived transitive scale. In order to deal with the transitivity problem, the AHP provides a consistency index for testing pairwise comparison consistency. So, finally, this paper proposes a consistency measure to reflect the judgmental inconsistency.     

A simple method to improve the consistency ratio of the pair-wise comparison matrix in ANP

Tests of consistency for the pair-wise comparison matrices have been studied extensively since AHP was introduced by Saaty in 1970s. However, existing methods are either too complicated to be applied in the revising process of the inconsistent comparison matrix or are difficult to preserve most of the original comparison information due to the use of a new pair-wise comparison matrix. Those methods might work for AHP but not for ANP as the comparison matrix of ANP needs to be strictly consistent. To improve the consistency ratio, this paper proposes a simple method, which combines the theorem of matrix multiplication, vectors dot product, and the definition of consistent pair-wise comparison matrix, to identify the inconsistent elements. The correctness of the proposed method is proved mathematically. The experimental studies have also shown that the proposed method is accurate and efficient in decision maker’s revising process to satisfy the consistency requirements of AHP/ANP.     

数控车床可靠性分配中的单准则排序方法

数控车床可靠性分配模型是一个层次结构,可靠性分配的关键技术是确定结构底层指标关于顶层目标的重要度排序,其前提条件是单准则排序已知.AHP通过构造"两两比较"的"1~9"比例标度判断矩阵A_n为单准则排序提供了合理的数据条件;但是基于A_n一致性检验的特征根排序法因临界值的确定缺乏必要理论基础而受到质疑.改进AHP的FAHP因为没有摆脱"一致性检验"的干扰所以改进并不成功.为了建立与"一致性"无关的单准则排序方法定义具有可加性的评分标度概念,通过标度转换将比例标度判断矩阵A_n转化为评分标度判断矩阵B_n,利用评分标度的可加性在准则C下对n个比较对象排序.因为B_n不是正矩阵所以不存在"一致性概念",因此基于评分标度判断矩阵的排序与"一致性"无关.     

AHP的检验方法及其比较分析

介绍了目前较有影响的三种ＡＨＰ一致性检验算法,并对其作了比较分析,最后提出了一种检验算法的选择准则     

层次分析法中判断矩阵不一致性调整方法研究

针对层次分析中判断矩阵的不一致性,提出了次序一致性与绝对一致性的概念,给出了不一致性的检验准则和修正方法。     

AHP方法一致性检验的新标准

在层次分析法中判断矩阵是否具有满意的一致性是一个重要的问题.对一致性差的判断矩阵,首先利用F-范数定义了s_k,然后讨论了s_k的单调性,从而随着对判断矩阵元素的调整,对判断矩阵一致性度量给出一个新的参考标准.     

AHP一致性的概率检验法

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.     

Estimation of missing judgments in AHP pairwise matrices using a neural network-based model

Selecting relevant features to make a decision and expressing the relationships between these features is not a simple task. The decision maker must precisely define the alternatives and criteria which are more important for the decision making process. The Analytic Hierarchy Process (AHP) uses hierarchical structures to facilitate this process. The comparison is realized using pairwise matrices, which are filled in according to the decision maker judgments. Subsequently, matrix consistency is tested and priorities are obtained by calculating the matrix principal eigenvector. Given an incomplete pairwise matrix, two procedures must be performed: first, it must be completed with suitable values for the missing entries and, second, the matrix must be improved until a satisfactory level of consistency is reached. Several methods are used to fill in missing entries for incomplete pairwise matrices with correct comparison values. Additionally, once pairwise matrices are complete and if comparison judgments between pairs are not consistent, some methods must be used to improve the matrix consistency and, therefore, to obtain coherent results. In this paper a model based on the Multi-Layer Perceptron (MLP) neural network is presented. Given an AHP pairwise matrix, this model is capable of completing missing values and improving the matrix consistency at the same time.     

模糊判断矩阵排序向量的确定方法研究

首先给出模糊判断矩阵的两种一致性的定义。然后分析现有确定模糊判断矩阵排序向量的方法的特点及存在的问题，在此基础上，系统研究确定模糊判断矩阵排序向量的两类方法，第一类方法是先将模糊判断矩阵转化为AHP判断矩阵，然后将后者的排序向量作为前者的排序向量；另一类方法是直接由一致性或具有满意一致性的模糊判断矩阵计算排序向量。最后用算例说明所提出方法的应用。     

AHP中判断矩阵的满意的一致性的研究

对层次分析法(AHP)中的判断矩阵,给出了它具有满意的一致性的充分必要条件,也就是,给出了检验它是否有满意的一致性的一种方法,在否定的情况下,还给出了修正它的一种方法使得它的每个主子矩阵都有满意的一致性.     

A quality control approach to consistency paradoxes in AHP

The Analytic Hierarchy Process (AHP) requires a specific consistency check of the pairwise comparisons in order to ensure that the decision maker is being neither inconsistent nor random in his or her pairwise comparisons. However, there are many situations where the decision maker has been reasonable, logical and non-random in making the pairwise comparison and yet will fail the consistency check. This paper argues against the use of the standard consistency check. If a consistency test is to be done, a quality control approach is recommended.     

Deriving crisp and consistent priorities for fuzzy AHP-based multicriteria systems using non-linear constrained optimization

Fuzzy optimization models are used to derive crisp weights (priority vectors) for the fuzzy analytic hierarchy process (AHP) based multicriteria decision making systems. These optimization models deal with the imprecise judgements of decision makers by formulating the optimization problem as the system of constrained non linear equations. Firstly, a Genetic Algorithm based heuristic solution for this optimization problem is implemented in this paper. It has been found that the crisp weights derived from this solution for fuzzy-AHP system, sometimes lead to less consistent or inconsistent solutions. To deal with this problem, we have proposed a consistency based constraint for the optimization models. A decision maker can set the consistency threshold value and if the solution exists for that threshold value then crisp weights can be derived, otherwise it can be concluded that the fuzzy comparison matrix for AHP is not consistent for the given threshold. Three examples are considered to demonstrate the effectiveness of the proposed method. Results with the proposed constraint based fuzzy optimization model are more consistent than the existing optimization models.     

Fuzzified AHP in the evaluation of scientific monographs

Fuzzification of the analytic hierarchy process (AHP) is of great interest to researchers since it is a frequently used method for coping with complex decision making problems. There have been many attempts to fuzzify the AHP. We focus particularly on the construction of fuzzy pairwise comparison matrices and on obtaining fuzzy weights of objects from them subsequently. We review the fuzzification of the geometric mean method for obtaining fuzzy weights of objects from fuzzy pairwise comparison matrices. We illustrate here the usefulness of the fuzzified AHP on a real-life problem of the evaluation of quality of scientific monographs in university environment. The benefits of the presented evaluation methodology and its suitability for quality assessment of R&D results in general are discussed. When the task of quality assessment in R&D is considered, an important role is played by peer-review evaluation. Evaluations provided by experts in the peer-review process have a high level of subjectivity and can be expected in a linguistic form. New decision-support methods (or adaptations of classic methods) well suited to deal with such inputs, to capture the consistency of experts’ preferences and to restrict the subjectivity to an acceptable level are necessary. A new consistency condition is therefore defined here to be used for expertly defined fuzzy pairwise comparison matrices.     

层次分析中的一致性

讨论了层次分析中一致性检验的含义,并给出一种提高判断矩阵一致性的方法.     

Note on group consistency in analytic hierarchy process

We study the paper of Xu [Z. Xu, On consistency of the weighted geometric mean complex judgement matrix in AHP, European Journal of Operational Research 126 (2000) 683–687] for the group consistency in analytic hierarchy process of multicriteria decision-making. The purpose of this note is threefold. First, we point out the questionable results in this paper. Second, for three by three comparison matrices, we provide a patchwork for his method. Third, we constructed a counter example to show that in general his method is wrong. Numerical examples are provided to illustrate our findings. If there are four or more alternatives, then we may advise researchers to ignore his results to avoid questionable estimation of group consistency.     

层次分析法一致性指标的临界值研究

层次分析法中一致性检验的显著性水平(即判断矩阵偏离一致性的程度)问题在已有研究文献中尚未得到很好的解决。论文在现有一致性指标CI基础上,从随机过程的视角,采用蒙特卡罗模拟法构造一致性指标的随机样本,根据样本确定了显著性水平为0.05和0.01情形下对应的一致性指标的临界值,为评价和调整判断矩阵提供了理论标准。同时,本研究能够确定判断矩阵偏离一致性的程度,并给出决策制定的显著性水平。     

一种基于决策矩阵的DST-AHP多属性决策方法

针对层次分析法决策时存在两两判断、一致性检验次数过多和判断矩阵残缺性等问题,本文提出了一种基于决策矩阵的DST-AHP多属性决策方法。该方法结合决策矩阵的特征值,构建DST-AHP方法层次结构模型和判断矩阵,并根据判断矩阵定义不同属性下各焦元的基本概率分配函数;然后利用Dempster合成法则对基本概率分配函数值进行合成,依据合成后值对方案进行排序。最后对AHP和DST-AHP两种方法进行比较分析,说明该方法的有效性。     

Achieving matrix consistency in AHP through linearization

Matrices used in the analytic hierarchy process (AHP) compile expert knowledge as pairwise comparisons among various criteria and alternatives in decision-making problems. Many items are usually considered in the same comparison process and so judgment is not completely consistent – and sometimes the level of consistency may be unacceptable. Different methods have been used in the literature to achieve consistency for an inconsistent matrix. In this paper we use a linearization technique that provides the closest consistent matrix to a given inconsistent matrix using orthogonal projection in a linear space. As a result, consistency can be achieved in a closed form. This is simpler and cheaper than for methods relying on optimisation, which are iterative by nature. We apply the process to a real-world decision-making problem in an important industrial context, namely, management of water supply systems regarding leakage policies – an aspect of water management to which great sums of money are devoted every year worldwide.     

The analytic hierarchy process with stochastic judgements

The analytic hierarchy process (AHP) is a widely-used method for multicriteria decision support based on the hierarchical decomposition of objectives, evaluation of preferences through pairwise comparisons, and a subsequent aggregation into global evaluations. The current paper integrates the AHP with stochastic multicriteria acceptability analysis (SMAA), an inverse-preference method, to allow the pairwise comparisons to be uncertain. A simulation experiment is used to assess how the consistency of judgements and the ability of the SMAA-AHP model to discern the best alternative deteriorates as uncertainty increases. Across a range of simulated problems results indicate that, according to conventional benchmarks, judgements are likely to remain consistent unless uncertainty is severe, but that the presence of uncertainty in almost any degree is sufficient to make the choice of best alternative unclear.     

模糊矩阵的广义一致性变换及其性质

给出模糊矩阵广义一致性变换的定义,并论证模糊矩阵经广义一致性变换后所具有的性质;通过对比分析指出本文的研究结论具有更广的应用范围;从分辨率角度给出参数取值范围的一个合理区间;从而拓展基于模糊一致判断矩阵的层次分析法的应用范围。