基于改进模糊熵和证据推理的多属性决策方法

针对证据推理方法框架下属性权重难以获取的问题,提出一种基于改进模糊熵和证据推理的多属性决策方法。首先,定义证据推理信度决策矩阵框架下的三角函数模糊熵公式,并证明了其满足熵的四个公理化定义。其次,所提方法能够同时处理属性权重完全未知和属性权重信息部分已知两种情况：当属性权重完全未知时,基于信度框架下的改进模糊熵和熵权法的基本思想计算属性权重;当属性权重信息部分已知时,定义加权模糊熵,建立期望模糊熵最小的线性规划模型求解最优属性权重。最后,利用证据推理算法融合方案属性值,结合期望效用理论得到方案排序结果。通过实例计算,并与传统模糊熵计算方法进行比较分析,验证了所提方法能够更加充分地反映原始决策信息,更具客观性和一般性。     

基于扩展原理的混合型证据推理不确定决策方法

提出一种基于扩展原理的混合证据推理不确定决策模型.通过α截集将同一决策问题中各属性使用的精确数、区间数和模糊数等异构评估信度统一分解为区间结构,采用区间证据推理方法求解各隶属度下的效用区间,并按隶属度次序重组方案效用;化简模糊数质心公式,并用于模糊定量评估的信度计算和方案模糊效用的排序;最后,通过具体实例验证了所提出方法的有效性和可行性.将该方法在算例中的适用情况进行比较和分析,结果表明所提出的方法具有良好的适应性.     

概率不确定语言熵及其多属性群决策

针对概率不确定语言集的多个不确定语言术语和其概率各不相同的特点,提出基于概率不确定语言熵的多属性决策方法。定义四种新的概率不确定语言熵：模糊熵、犹豫熵、不完全信息熵和总熵,以分别测量概率不确定语言集的模糊性、犹豫性、信息不完全性和整体不确定性。给出了四种熵测度的公理化定义和表达式,根据概率不确定语言集的四种熵,构建能够解决属性权重未知的多属性决策模型,并通过案例和对比分析验证了该模型的有效性和合理性。     

基于前景理论和证据推理的区间灰数多属性决策

针对不确定背景下的多属性决策问题,提出基于前景理论和证据推理的区间灰数多属性决策方法.首先,考虑区间灰数在区间内取值概率不相等的特性,提出一种改进的区间灰数距离公式,在此基础上,以方案的正负理想解为参考点,计算属性值与正负理想解之间的距离集.其次,将决策者的风险心理因素引入区间灰数多属性决策中,结合前景理论构建基于区间灰数距离的前景价值函数.再次,通过证据推理算法和区间数可能度大小比较规则对方案做出排序.最后,通过算例分析验证所提方法的有效性.     

基于相对相似度关系的三角模糊数型不确定多属性决策法

针对属性权重未知的三角模糊数型不确定多属性决策问题, 提出一种新的规范三角模糊数与决策方案的相对相似度定义和三角模糊数相对相似度关系理论; 借鉴合作博弈中可能度最大化算法提出一种基于三角模糊数相对相似度关系的属性权重确定方法; 利用备选方案对象在方案集中的总体相对相似度值大小选取最优对象并排序, 以此给出三角模糊数型不确定多属性决策的相对相似度关系算法, 最后通过算例分析表明了所提出算法的可行性和有效性.     

基于D-S证据理论的多属性多人决策方法及其应用

针对多人多属性决策问题,提出了一种新的基于DS证据理论的方法。该方法综合考虑了多个决策者的主观偏好,并将主观信息与客观信息进行集成。最后,给出一个应用实例和计算结果。     

基于Pythagorean不确定语言的扩展VIKOR多属性群决策方法

针对属性值为Pythagorean不确定语言变量,属性权重和专家权重完全未知的群决策问题,提出一种扩展VIKOR多属性群决策方法.首先,给出Pythagorean不确定语言变量的概念,提出考虑语义变化的Pythagorean不确定语言变量运算规则、大小比较方法和Hamming距离测度;其次,提出基于Pythagorean 不确定语言模糊熵的属性权重确定方法和基于相似度的专家权重确定方法,进而提出一种新的扩展VIKOR方法;最后,通过国内航空公司服务质量评估实例验证所提出方法的有效性和可行性.     

基于灰熵模型的区间型指标和权重的不确定多属性决策方法及其应用

区间型属性值及权重多属性决策问题的难点在于不确定权重信息的精确化和区间数的排序问题.灰熵模型中运用与理想解均衡接近的贴近度对方案排序的思想,不仅可以使多属性决策避开繁重的模糊数据精确化步骤,还可以有效解决方案排序时的点关联倾向问题.考虑到传统灰熵模型只适用于精确实数和指标权重缺失的缺陷,将灰关联熵引入传统灰熵模型,构建区间型权重属性值的灰熵模型,解决不确定数据精确化的难题.针对区间数排序难的难题,基于TOPSIS方法应用衍生变量接近度、均衡度再次逼近理想解的思想计算改进灰熵模型的均衡接近度对方案进行排序.最后,通过SG激光装置项目选择某种非标元器件供应商的算例验证了所提出模型的有效性.     

基于证据推理和第3 代前景理论的不确定性多属性决策方法

针对多状态不确定性多属性决策问题, 建立基于证据推理和第3 代前景理论的决策方法. 首先, 给出不确定性知识表示方法—– 确定因子结构及其构造方法; 然后, 将第3 代前景理论构造价值函数和确定权重函数引入决策方法中, 得到每个方案在各属性下的前景价值; 进一步, 根据证据推理方法对前景价值进行信息融合得到各方案的合成前景价值, 并依据合成前景价值对方案进行排序; 最后, 通过算例验证了所提出方法的可行性和有效性.

     

不确定性多属性决策中的ER方法改进

基于对不确定性多属性决策问题中ER方法的研究,提出一种不确定性多属性决策中的改进ER方法,井证明该方法完全满足证据合成的4个公理．通过实例运算,进一步验证了新方法的有效性和合理性．     

Fuzzy multiattribute group decision making based on intuitionistic fuzzy sets and evidential reasoning methodology

In this paper, we propose a new fuzzy multiattribute group decision making method based on intuitionistic fuzzy sets and the evidential reasoning methodology. First, the proposed method uses the evidential reasoning methodology to aggregate each decision maker’s decision matrix and the weights of the attributes to get the aggregated decision matrix of each decision maker. Then, it uses the obtained aggregated decision matrices of the experts, the weights of the experts and the evidential reasoning methodology to get the aggregated intuitionistic fuzzy value of each alternative. Finally, it calculates the transformed value of the obtained intuitionistic fuzzy value of each alternative. The smaller the transformed value, the better the preference order of the alternative. The proposed method can overcome the drawbacks of the existing methods for fuzzy multiattribute group decision making in intuitionistic fuzzy environments.     

基于MADM理论的网格信任模型

提出了一个针对开放网格市场的信任模型。在评价网格服务提供者的信用值时,该模型强调直接信任和间接信任两者的重要性。因为直接信任和间接信任与很多因素有关,基于多重属性决定（MADM）理论提出了一个创新的方法来决定直接和间接信任的客观权值。模拟结果说明该信任模型相比权值反馈模型和eBay信任模型更为准确地反映服务提供者的信用值,因此能够在开放网格环境中提高用户的满意度。     

单值中智信息熵及其多属性决策方法

针对评估信息为单值中智数的多属性决策问题,建立了基于单值中智熵的多属性决策方法。首先,针对现有单值中智熵定义的不足,引入了新的单值中智熵的公理化定义;其次,基于三角函数,设计了一种衡量单值中智数不确定性的信息熵公式,并证明其满足单值中智熵的四个公理化条件;然后,运用提出的熵公式,并结合Lagrange乘数法和贴近度,构建了一种新的单值中智多属性决策方法;最后,将提出的决策方法运用于数据产品服务商的选择问题验证该方法的合理性与有效性。     

Decision support framework for risk management on sea ports and terminals using fuzzy set theory and evidential reasoning approach

As sea ports and terminals are valuable assets, in today’s uncertain and complex environment further refinements are needed to assess risks and prioritise protective measures for these critical pieces of logistics infrastructure. The major problem that port professionals (e.g. port risk managers and port auditors) are facing is the lack of an appropriate methodology and evaluation techniques to support their risk management (RM) cycle. Therefore in response to the uncertainties and to provide continuous risk control assurance in port industry, this paper uses fuzzy set theory (FST) to describe and evaluate the associated risk factors within the ports and terminals operations and management (PTOM). An evidential reasoning (ER) approach is employed to synthesise the information produced. These processes constitute a decision support framework that will be used to conduct port-to-port risk evaluations or to assess a whole port’s and terminal’s overall risk level in order to facilitate continuous improvement strategies. The proposed framework along with a generic methodology and a risk evaluation model is tested by a case study. The case study analyses pieces of three Southern Iranian ports by using an illustrative operational risk hierarchy. The sensitivity analysis carried out in this paper prove pieces of the applicability of the proposed methodology and model for risk evaluation of the sea ports and terminals in real situations.     

Multiperiod multiattribute decision‐making method based on trend incentive coefficient

In this paper, we develop a method for multiperiod multiattribute decision‐making (MP‐MADM) problems, in which the decision information, including attribute weights and attribute values, is given at different periods. First, using the variation in attribute values of the various alternatives for unit time, we can obtain the trend incentive coefficient of variation that represents reward or punishment for the development tendency of alternatives. This paper proposes a method based on maximum entropy ordered weighted averaging (MEOWA) to determine the trend incentive coefficient. Second, considering the differences development tendency of the alternatives, we propose an approach that integrates the trend incentive coefficient and the original decision information to solve the MP‐MADM problems. Finally, two MP‐MADM cases are used to illustrate the effectiveness and practicability of the proposed method. Comparisons with previous research are also discussed.     

基于多属性决策的嵌入式操作系统识别技术研究2

针对嵌入式固件逆向解析过程中操作系统类型识别困难的问题,提出了一种基于多属性决策的嵌入式操作系统识别技术。对固件映像中反映出的嵌入式操作系统的多种特征进行综合分析并构建了相关的识别模型,利用向量夹角余弦计算与标准系统之间的相似度。阐述了识别的基本思想和具体实现流程。实验结果表明,该方法在某些特征缺失的情况下仍能得到较准确的识别结果。     

A method of determining attribute weights in evidential reasoning approach based on incompatibility among attributes

Decisions on attribute weights are important problems in multiple attribute decision making. Many methods have been proposed to create attribute weights which are used to aggregate attributes in a simple additive weighting way. In this paper, a method of deriving attribute weights from incompatibility among attributes and possible constraints on the weights is developed based on the evidential reasoning approach in which attribute aggregation is nonlinear rather than linear. The incompatibility is a flexible combination of deviation incompatibility and decision incompatibility with a relaxation coefficient. The deviation incompatibility measures differences between assessments of alternatives on each attribute and the decision incompatibility quantifies differences between assessments of alternatives on one attribute and the aggregated assessments of the alternatives. For a specific alternative, two pairs of optimization problems with a constraint on the difference between potential weights and the combination of deviation incompatibility and decision incompatibility are designed to generate the favorable intervals of attribute weights and those of utilities of assessment grades. A problem of car performance assessment is investigated to demonstrate the applicability of the proposed method. The method is validated by comparison with other methods of producing attribute weights using the problem.     

An interval difference based evidential reasoning approach with unknown attribute weights and utilities of assessment grades

In this paper, the concept of interval difference is firstly defined. Then, an interval difference based evidential reasoning approach is proposed to analyze multiple attribute decision making problems in three situations, including (1) unknown attribute weights and utilities of assessment grades, (2) unknown attribute weights, and (3) unknown utilities of assessment grades. Three optimization models are constructed to identify potentially optimal alternatives in the three situations. For each potentially optimal alternative, three pairs of optimization problems are constructed to generate the optimized intervals of attribute weights and utilities of assessment grades or one of them. By using the optimized intervals, the interval difference of potentially optimal alternatives is calculated and used to generate their rank-order. This process is repeated until all alternatives are identified as potentially optimal alternatives. A complete rank-order of all alternatives is then generated. The performance of six executive cars is assessed using the proposed approach to demonstrate its applicability and validity.     

基于主客观赋权的多属性空间节点选择算法

针对空间协作传输中单属性协作节点选择算法无法兼顾系统可靠性和生存时间的问题,引入多属性决策方法（MADM）,综合考虑信道衰落等级、协作节点剩余能量和误码率三个属性对空间协作节点进行多属性评估,提出一种基于主客观赋权的多属性空间协作节点选择（SOW-CNS）算法。首先,根据信道受阴影衰落影响程度,建立两状态无线信道模型,分别为无阴影Loo信道衰落模型和有阴影Corazza信道衰落模型;其次,引入基于主客观赋权的多属性决策策略,使用层次分析法和信息熵法建立空间协作节点的主观属性权向量和客观属性权向量;然后,使用最大熵原理和离差和最大法计算主客观属性权向量;最后,利用主客观属性权向量与各节点的属性值计算各潜在节点的评价值,进而选出最佳协作节点参与空间信息协作传输。仿真结果表明,与传统最佳质量协作节点选择算法（BQ-CNS）、能量公平性协作节点选择算法（EF-CNS）和随机协作节点选择算法（R-CNS）相比,基于主客观赋权的多属性决策算法不仅降低系统误码率,而且能够获得更长的系统生存期。