两类层次分析法的转换及在应用中的比较

模糊层次分析法是层次分析法的一种,用于处理含有模糊性的决策问题。通过研究一致互反判断矩阵与模糊互补判断矩阵的转换关系,给出把一致互反矩阵转换成模糊互补矩阵且权向量排序不变的方法,基于这种转换的保序性,提出了一种介于层次分析法与模糊层次分析法之间的新的层次分析方法,这种方法简化了层次分析法的计算。作为这种新方法的应用,通过实例验证了该方法的合理性。     

基于模糊层次分析法的信息安全风险评估

依据模糊决策理论,提出了一种结合三角模糊数和层次分析法(AHP)定量评估信息安全风险的方法。在构建信息安全风险因素递阶层次结构模型基础上,用三角模糊数表示信息安全专家判断信息,同时采用一种基于可能度的模糊互补判断矩阵排序方法对风险因素进行重要度排序,从而确定了各层次风险因素的相对权重系数和整体绝对权重系数,为信息安全风险管理决策和安全工程建设提供了依据。最后通过实例说明了算法的应用。     

基于FAHP的信息安全风险评估方法

提出基于模糊层次分析法的信息安全风险综合评估模型,从主观评测和工具检测两方面对各个风险因素分别评价其重要程度。利用模糊偏好法求出各个风险因素在系统风险评估中的优先级排序,给出目标系统在不同安全侧面上的量化风险,增强评估准确性。实例分析表明,该模型可方便地应用于信息安全风险评估,具有实用性。     

一种基于GA-FAHP的软件漏洞风险评估方法

针对软件系统中漏洞的风险等级确定等问题,提出了一种利用遗传模糊层次分析法(GA-FAHP)评估软件漏洞风险的方法。该方法首先利用改进的模糊层次分析法求出各风险因素权重,并建立模糊判断矩阵;其次将模糊判断矩阵的一致性检验与修正计算过程转化为带约束的非线性系统优化问题,并利用遗传算法求解;最后,通过GA-FAHP算法求出软件漏洞的风险值。实验结果表明,该方法具有较好的准确性和有效性,为软件漏洞风险评估提供了一种可行的途径。     

改进的三角模糊数互反判断矩阵排序算法研究

研究了模糊层次分析法中以三角模糊数为元素的互反判断矩阵排序方法问题,提出一种改进模糊概率算法。采用改进的满意一致性判断指标对互反判断矩阵判断与修正;用模糊概率算法将判断矩阵特征向量中的三角模糊数转换成准确值,最终得出排序向量。实例分析结果表明,排序向量更加趋近理想判断,算法更具准确性。     

FAHP方法在信息安全风险评估中的研究

本文在分析影响信息安全风险的因素的基础上构建了信息安全风险分析的层次结构模型，提出了采用模糊层次分析法（Fuzzy-AHP）对风险进行量化分析的方法。该方法采用三角模糊数来表示基于群组决策的信息安全风险各因素的判断矩阵，并用层次分析法来对专家判断结果进行处理，为决策提供了更合理的数据。     

基于粒子群算法的模糊层次分析模型

针对模糊层次分析法中存在的模糊判断矩阵一致性检验和修正困难、元素权重计算繁琐的问题,从模糊判断矩阵的定义角度出发,构建了基于粒子群算法的模糊层次分析模型(PSO-FAHP),提出了包含模糊判断矩阵一致性修正及各元素排序过程的非线性带约束优化问题,引入粒子群算法实现了问题的求解,并分析了模型的合理性。最后通过数值算例对比了模型的计算结果,验证了模型的正确性。对模糊层次分析法的实践应用具有一定的指导意义。     

基于ISM与AHP组合的需求优先级排序方法

当前需求优先级排序方法将用户需求放在同一层次上进行比较,然后设定优先级,而对需求层次性考虑不 多。对此,从需求的层次性出发,提出以解释结构模型和层次分析法相结合的需求优先级排序方法,其中用解释结构 模型对需求进行分层处理,然后对最上层的需求使用层次分析法进行需求优先级排序,最后给出案例分析。结果表 明,该方法能够提高需求优先级设定的合理性,明显降低需求的比较次数,降低因需求导致项目失败的风险。     

基于SAHP和需求模式的需求优先级排序方法

针对当前需求优先级排序方法中,将用户需求放在同一层次上进行比较,设定优先级,而对需求层次性考虑得不多。从系统的整体性和需求的层次性出发,提出以解释结构模型和层次分析法相结合的需求优先级排序方法,其中用解释结构模型对需求进行结构分析和分层处理,对最上层的需求使用层次分析法进行需求优先级排序,将该方法命名为SAHP。在案例分析中,借助需求模式,对推广后的案例进行优先级排序,来说明该方法具有很好的通用性,给出案例分析和与AHP进行了比较。结果表明性能总体上好于AHP方法,该方法能够提高需求优先级设定的合理性,降低因需求导致项目失败的风险。     

直觉模糊层次分析法处理医院用药风险评价

基于直觉模糊集的模糊逼近理论,给出了将直觉模糊互补判断矩阵转换为模糊逼近矩阵的方法,提出了直觉模糊环境下的AHP方法,简称为直觉模糊层次分析法,将其应用于对医疗机构的用药风险的评价问题,给出了各子风险类别的权重。经检验,是一种实用性较强的医疗机构用药风险评价方法。     

供应链失效风险识别与评估*

供应链风险是影响供应链实践应用的关键因素之一,供应链风险管理是供应链管理的重要内容。采用故障树理论和模糊理论对供应链风险进行了分析,构造了供应链失效风险故障树,该故障树由供应商、制造商、分销商三部分组成;分析了各个部分的失效原因,设计了正态模糊算子,阐述了供应链风险概率计算方法。针对一个供应链实例,采用上述方法对各个要素失效风险进行了定量计算,确定了供应链失效风险等级。     

Consistency control and expert consistency prioritization for FFTA by using extent analysis method of trapezoidal FAHP

The purpose of this study is to enable consistency control along with expert consistency prioritization for direct fuzzy inputs as basic events (BEs) assigned to the fault tree analysis (FTA) method. In the recent literature, fuzzy fault tree analysis (FFTA) applications have no consistency check for the expert judgments. In this study, as a multi criteria decision making method, fuzzy analytic hierarchy process (FAHP) is applied for checking the consistency by centric consistency index (CCI). Expert consistency prioritization is also implemented for FFTA by using extent analysis method of trapezoidal FAHP. An analytic comparison between with and without consistency control is obtained. The numerical results for collapse of an offshore platform are presented to illustrate the applicability of the approach.     

A directed failure causality network (DFCN) based method for function components risk prioritization under interval type-2 fuzzy environment

Failure risk prioritization of function components plays a key role in the process to redesign a mechanical product. However, the failure causality relationships (FCRs) among failure modes of components are often ignored in the existing design risk assessment methods, leading to inaccurate risk prioritization results. A failure mode in one component can be the cause of a failure mode in another component, and a failure mode with low chance of failure may result in another failure mode with high chance of failure through propagation among failure modes. Thus, the ultimate effects of each failure mode should be determined by considering the effects of failure propagations. In this research, a directed failure causality network (DFCN) model considering FCRs is proposed to describe the FCRs and to predict risks of the designed product. In addition, uncertainties of linguistic terms in evaluation are also considered in the developed model, because linguistic terms are more suitable and natural than quantitative numbers for design engineers to assess design risks based on their knowledge. To describe these uncertainties, interval type-2 fuzzy set is employed to model the designers’ subjective linguistic terms for determining the weights of edges and weights of vertices in the DFCN. A case study for failure risk prioritization of components in redesign of a large tonnage crawler crane (LTCC) is implemented to demonstrate the effectiveness of the proposed method.     

基于模糊理论的漏洞危害等级评估

针对安全漏洞危害难以量化评估的问题, 提出一种基于模糊理论的漏洞危害等级评估方法。使用层次分析法建立漏洞等级评估体系并计算漏洞评估影响因素的权重。利用模糊综合判断法对漏洞危害等级进行定量评价, 综合可利用性和安全影响两方面因素实现对漏洞危害的评估。实验结果表明该方法对于漏洞危害能够得到更加准确的评估结果。     

An approach for ranking of fuzzy numbers

In order to rank all fuzzy numbers, we modify the method of “a new approach for ranking of trapezoidal fuzzy numbers” by Abbasbandy and Hajjari (2009). Our proposed method is used for ranking symmetric fuzzy numbers. The advantage of this method is illustrated by some comparative examples.     

Ranking of fuzzy numbers by fuzzy mapping

In this work, the concepts of interval function, the mean value and α lower percentile of a fuzzy number are presented. Also, we defined a large family of fuzzy numbers. Then, we obtained a method to rank them. Herein, the approach proposed is relatively simple in terms of computational efforts and is efficient for ranking fuzzy numbers. Finally, the method is illustrated by numerical examples and compared with other methods.     

Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment

Failure mode and effects analysis (FMEA) is a widely used risk assessment tool for defining, identifying, and eliminating potential failures or problems in products, process, designs, and services. In traditional FMEA, the risk priorities of failure modes are determined by using risk priority numbers (RPNs), which can be obtained by multiplying the scores of risk factors like occurrence (O), severity (S), and detection (D). However, the crisp RPN method has been criticized to have several deficiencies. In this paper, linguistic variables, expressed in trapezoidal or triangular fuzzy numbers, are used to assess the ratings and weights for the risk factors O, S, and D. For selecting the most serious failure modes, the extended VIKOR method is used to determine risk priorities of the failure modes that have been identified. As a result, a fuzzy FMEA based on fuzzy set theory and VIKOR method is proposed for prioritization of failure modes, specifically intended to address some limitations of the traditional FMEA. A case study, which assesses the risk of general anesthesia process, is presented to demonstrate the application of the proposed model under fuzzy environment.     

A novel meta-heuristic based method for deriving priorities from fuzzy pairwise comparison judgments

This paper proposes a new method to derive the priority vector from fuzzy pairwise comparison matrices. Unlike several known methods, the proposed method derives crisp weights from consistent and inconsistent fuzzy comparison matrices. Therefore, the crisp weights obviate the need of additional aggregation and ranking procedures. To derive the priority vector, a Modified Fuzzy Logarithmic Least Square Model (MFLLSM) is proposed. In order to solve the MFLLSM, a framework based on genetic algorithm is proposed. In the proposed framework, a heuristic algorithm of population initialization, a heuristic algorithm for simulating fuzzy numbers and a heuristic algorithm of fitness evaluation are proposed.The solution of the prioritization problem requires finding priorities such that their ratio approximately satisfies the initial judgments. Computational results reveal the superiority of the proposed method in comparison with five well known methods of literature from the viewpoint of satisfaction of initial judgments by the obtained priority vector. It is shown by ten different examples that the deviation of the priorities ratio from initial judgments in the proposed method is less than five existing methods of literature. In addition, unlike several methods of literature, the proposed method considers fuzzy judgments represented by both triangular and trapezoidal fuzzy numbers. Furthermore, the proposed method for the first time considers judgments represented by triangular shaped fuzzy numbers and trapezoidal shaped fuzzy numbers which are discussed in the paper.     

A new type-2 fuzzy set of linguistic variables for the fuzzy analytic hierarchy process

The fuzzy analytic hierarchy process (FAHP) has been used to solve various multi-criteria decision-making problems where trapezoidal type-1 fuzzy sets are utilized in defining decision-makers’ linguistic judgment. Previous theories have suggested that interval type-2 fuzzy sets (IT2 FS) can offer an alternative that can handle vagueness and uncertainty. This paper proposes a new FAHP characterized by IT2 FS for linguistic variables. Differently from the typical FAHP, which directly utilizes trapezoidal type-1 fuzzy numbers, this method introduces IT2 FS to enhance judgment in the fuzzy decision-making environment. This new model includes linguistic variables in IT2 FS and a rank value method for normalizing upper and lower memberships of IT2 FS. The proposed model is illustrated by a numerical example of work safety evaluation. Comparable results are also presented to check the feasibility of the proposed method. It is shown that the ranking order of the proposed method is consistent with the other two methods despite difference in weight priorities.