Generalized ordered weighted averaging operators based methods for MADM in intuitionistic fuzzy set setting

Multiattribute decision making（MADM） problems, in which the weights and ratings of alternatives are expressed with intuitionistic fuzzy（IF） sets, are investigated.Firstly, the relative degrees of membership and the relative degrees of non-membership are formulated as IF sets, the weights and values of alternatives on both qualitative and quantitative attributes may be expressed as IF sets in a unified way.Then a MADM method based on generalized ordered weighted averaging operators is proposed.The proposed method is illustrated with a numerical example.

Linear goal programming approach to obtaining the weights of intuitionistic fuzzy ordered weighted averaging operator

The multiple attribute decision making problems are studied, in which the information about attribute weights is partly known and the attribute values take the form of intuitionistic fuzzy numbers. The operational laws of intuitionistic fuzzy numbers are introduced, and the score function and accuracy function are presented to compare the intuitionistic fuzzy numbers. The intuitionistic fuzzy ordered weighted averaging （IFOWA） operator which is an extension of the well-known ordered weighted averaging （OWA） operator is investigated to aggregate the intuitionistic fuzzy information. In order to determine the weights of intuitionistic fuzzy ordered weighted averaging operator, a linear goal programming procedure is proposed for learning the weights from data. Finally, an example is illustrated to verify the effectiveness and practicability of the developed method.

Interval-valued intuitionistic fuzzy aggregation operators

The notion of the interval-valued intuitionistic fuzzy set （IVIFS） is a generalization of that of the Atanassov＇s intuitionistic fuzzy set. The fundamental characteristic of IVIFS is that the values of its membership function and non-membership function are intervals rather than exact numbers. There are various averaging operators defined for IVlFSs. These operators are not monotone with respect to the total order of IVIFS, which is undesirable. This paper shows how such averaging operators can be represented by using additive generators of the product triangular norm, which simplifies and extends the existing constructions. Moreover, two new aggregation operators based on the t.ukasiewicz triangular norm are proposed, which are monotone with respect to the total order of IVIFS. Finally, an application of the interval-valued intuitionistic fuzzy weighted averaging operator is given to multiple criteria decision making.

Entropy-based procedures for intuitionistic fuzzy multiple attribute decision making

The class of multiple attribute decision making （MADM） problems is studied, where the attribute values are intuitionistic fuzzy numbers, and the information about attribute weights is completely unknown. A score function is first used to calculate the score of each attribute value and a score matrix is constructed, and then it is transformed into a normalized score matrix. Based on the normalized score matrix, an entropy-based procedure is proposed to derive attribute weights. Furthermore, the additive weighted averaging operator is utilized to fuse all the normalized scores into the overall scores of alternatives, by which the ranking of all the given alternatives is obtained. This paper is concluded by extending the above results to interval-valued intuitionistic fuzzy set theory, and an illustrative example is also provided.

Consensus intuitionistic fuzzy group decision-making method for aircraft cockpit display and control system evaluation

A novel group decision-making （GDM） method based on intuitionistic fuzzy sets （IFSs） is developed to evaluate the ergonomics of aircraft cockpit display and control system （ACDCS）. The GDM process with four steps is discussed. Firstly, approaches are proposed to transform four types of common judgement representations into a unified expression by the form of the IFS, and the features of unifications are analyzed. Then, the aggregation operator called the IFSs weighted averaging （IFSWA） operator is taken to synthesize decision-makers’ （DMs’） preferences by the form of the IFS. In this operator, the DM’s reliability weights factors are determined based on the distance measure between their preferences. Finally, an improved score function is used to rank alternatives and to get the best one. An illustrative example proves the proposed method is effective to valuate the ergonomics of the ACDCS.

I-FIFOWA算子及其在群决策中的应用

对模糊数直觉模糊信息的集结算子进行了进一步研究,引入了模糊数直觉模糊的一些运算法则、模糊数直觉模糊的得分函数,并基于这些运算法则,提出了一些新算子:模糊数直觉模糊加权平均(FIFWA)算子、模糊数直觉模糊有序加权平均(FIFOWA)算子和诱导的模糊数直觉模糊有序加权平均(I-FIFOWA)算子,然后分析了它们的性质。针对属性权重和专家权重为实数,属性取值为模糊数直觉模糊数的多属性群决策问题,给出了一种基于FIFWA算子和I-FIFOWA算子的模糊数直觉模糊多属性群决策方法。最后,进行了实例分析,说明了该方法的实用性和有效性。

Three methods for generating monotonic OWA operator weights with given orness level

Based on the properties of ordered weighted averaging (OWA) operator and regular increasing monotone (RIM) quantifier, three methods for generating monotonic OWA operator weights are proposed. They are geometric OWA operator weights, equidifferent OWA operator weights and the modified RIM quantifier OWA weights. Compared with most of the common OWA methods for generating weights, the methods proposed in this paper are more intuitive and efficient in computation. And as there are more than one solution in most cases, the decision maker can set some initial condition and chooses the appropriate solution in the real decision process, which increases the flexibility of decision making to some extent. All these three OWA methods for generating weights are illustrated by numerical examples.

基于OWA算子的模糊n-cell数排序方法

针对基于模糊n-cell数的多属性排序问题,提出了一种基于有序加权平均算子(OWA算子)的模糊n-cell数排序方法。该方法首先根据样本数据对评估对象的属性构造模糊n-cell数,其次根据均值将属性按照从大到小排列,然后选取合适的权重向量,应用OWA算子进行信息聚合得到综合模糊n-cell数,接着根据各分量均值得到排序结果。最后,将该方法运用到实例中,并与传统的均值方法进行了比较。结果表明该方法不仅灵活有效,可根据具体情况选择不同的OWA权重来消除部分不合理的情况,使结果更有说服力,还弥补了传统均值方法的不足。

改进综合因子法的数控伺服刀架可靠性分配方法

针对可靠性分配过程中影响因素和专家打分的不确定性问题,提出一种将灰色关联理论、模糊集理论和有序加权平均算子结合的基于改进综合因子法的数控伺服刀架可靠性分配方法。综合考虑技术水平、重要度、复杂度、运行环境、维修性、费效比等多种影响因素,将各因素细化并分层,建立分层的综合因子评价模型,并给出评价标准。综合现场试验得到的统计数据,建立子系统的全局指标模型,得到每个子系统的全局指标,以故障率为分配指标将数控刀架系统的总体故障率分配到各子系统,实现数控伺服刀架的可靠性分配,得到的可靠度分配结果为驱动系统2.193×10-5、传动装置1.645×10-5、锁紧松开及定位装置2.547×10-5、刀盘信号装置盘1.345×10-5、密封与紧固装置4.589×10-5和连接线与连接界面4.544×10-5,与数控伺服刀架的工程实际情况相符。

改进二维云模型的信息工程监理风险评估

针对传统信息工程监理风险评估具有随机性与模糊性,提出了改进二维云模型的风险评估模型。通过三角模糊层次分析理论确定各风险因素权重,以可能性和严重度为基础变量,构建基于二维云模型的风险云图,在加权有序几何平均算子(order weighted geometric averaging operator,OWGA)的基础上引入情境参数,根据决策者的风险偏好优化各准则层风险云与云标尺的贴近度排序。经过实例仿真,表明所提模型可以在融合专家智慧的同时,避免定性云转换为定量值的损失,将风险以蕴含随机性和模糊性的形式可视化,经改进贴近度确定风险等级,验证了其有效性及优越性。

改进直觉模糊集TOPSIS在防波堤运营期健康状态评价中的应用

为了准确评价防波堤运营期健康状态的等级,建立了基于改进直觉模糊集逼近理想解排序法(Technique for Order Preference by Similarity to Ideal Solution,TOPSIS)的防波堤健康状态评价模型。首先,通过最小熵原理对多种组合权重方法进行最优化处理,以改进直觉模糊集TOPSIS法。其次,以安全性、适用性、耐久性3个维度建立防波堤运营期健康状态评价指标体系,该指标体系采用3个定性指标和8个定量指标进行表征。最后,将改进直觉模糊集TOPSIS模型应用到渤海基地港池护岸防波堤运营期健康状态评价中,并与改进前模型计算结果、实际情况进行对比分析。结果表明,改进模型计算结果与实际情况比较一致,优于改进前评价结果,为防波堤运营期健康状态评价提供了一种新的途径。

基于改进SLIM方法的管制移交人误概率预测

基于模糊有序加权平均算子(Fuzzy Ordered Weighted Averaging Operator,FOWA)对成功似然指数法(Success Likelihood Index Methodology,SLIM)进行了改进,实现了对管制移交人误概率实施定量评估的目的。相比SLIM基本方法,改进方法可使评估过程更符合人的模糊判断特性,还能显著提升评估效率,在数据处理过程中及时过滤不良的判断信息。通过实际应用中的对比分析可知,虽然两种方法均能得出管制移交人误概率,但改进SLIM方法对专家知识的挖掘更充分。使用Delphi法对管制移交过程中的人误行为触发概率可能性进行排序,排序结果与改进SLIM方法一致度更高,由此验证了改进SLIM方法的优势与可行性。

混合信息融合策略下共享电单车绿色回收供应商选择方法

共享电单车具有的速度快、舒适度高等特点使其拥有大量用户,运营商以过度投放策略来抢占市场先机进而引发了电单车故障率高、停放难且不规范等现实问题,增大了回收管理的难度。为此,研究了一种共享电单车绿色回收供应商选择方法,为回收管理提供决策支撑。首先,分析了共享电单车的回收需求特征,构建供应商评价指标体系,并引入区间直觉模糊集提出混合评价信息统一量化方法;其次,为集结群体评价信息,提出内嵌双参数的连续区间直觉模糊有序加权平均算子,并以群体一致性为目标构建了参数求解模型;然后,以所提算子为基础,提出用于解决回收供应商选择问题的群体决策方法;最后,通过共享电单车回收案例分析验证了所提方法的适用性与有效性。

基于目标规划的语言值OWA算子及其在大学生综合测评的应用

针对大学生综合测评问题,设计一种基于高斯模糊集的有序加权平均(OWA)评价方法,方便评价者借助高斯模糊集对评价对象的各指标给出语言值评价.定义了高斯模糊集的数乘运算和排序方法,以评价者的乐观水平为参数,设计一种基于目标规划的权重优化方法,引导大学生全面发展或个性化发展.实验结果表明,设置合理的乐观水平,所提出的评价模型可以鼓励学生发挥自己的特长,得到与主观感觉一致的评价结果.

基于直觉模糊MULTIMOORA的改进FMEA风险评估方法

针对传统故障模式和影响分析(FMEA)方法中难以表征评估信息不确定性、未考虑风险因子权重和风险优先值模型不合理等问题,提出基于直觉模糊全乘比例分析多目标优化的改进FMEA方法。该方法运用可转化为直觉模糊数的语言变量表征故障模式和风险因子权重评估信息,结合直觉模糊优先加权平均(IFPWA)算子集结不同优先等级的专家评估信息,构建专家评估法和偏差最大化模型法相结合的综合赋权法求得风险因子权重,引入直觉模糊集成算子及改进Hamming距离对全乘比例分析多目标优化决策方法进行改进,确定故障模式风险顺序。以铁路线路维修FMEA为例,验证了所提方法的可行性和有效性。

基于直觉模糊VIKOR方法的装备优选群决策模型

针对属性权重完全未知且属性值为语言信息的装备优选与排序问题,提出了一种基于扩展多准则妥协解排序(VIKOR)的多属性群决策模型。该模型引入直觉模糊加权集结(IFWA)算子对所有个体的决策信息进行集成,以获取作战指挥员决策群组的直觉模糊决策矩阵。利用直觉模糊数熵权公式对评估属性进行客观赋权,通过将VIKOR法扩展到直觉模糊环境来得到待选装备的折衷可行方案。最后结合作战无人机(UCAV)空地导弹优选实例和灵敏度分析验证了该模型的有效性和稳定性,并通过与直觉模糊TOPSIS法的对比实验表明了所提出方法的优越性。

基于认知图和直觉模糊推理的态势评估方法

针对战场环境中信息的不确定性和交互关联性问题,将直觉模糊推理理论与认知图推理相结合,提出一种基于认知图和直觉模糊理论的态势评估方法。首先,分析当前认知图推理的特点与不足,建立基于直觉模糊集理论和有序加权平均算子的直觉模糊认知图模型;其次,提出直觉模糊认知图的态势评估推理过程;最后,用实例给出评估结果,验证方法的有效性和正确性。该方法能更准确地描述战场客观环境,为决策者提供更多的决策信息和决策偏好自由度。

直觉模糊层次分析法

为了解决传统模糊层次分析法难以处理的直觉模糊环境下的综合评判问题,利用直觉模糊数和模糊层次分析法建立了一种直觉模糊层次分析法。实验分析表明了该方法的有效性。

基于直觉模糊多属性决策的逆向物流供应商选择

逆向物流供应商选择是典型的多属性决策问题.针对逆向物流供应商选择问题的特点,提出一种基于直觉模糊熵的逆向物流供应商选择问题的直觉模糊多属性决策方法.在回顾相关基础理论知识基础上,建立了逆向物流供应商评价指标体系,给出了基于直觉模糊熵的评价指标权重的确定方法,然后运用直觉模糊加权平均算子对二级指标信息集结,得到逆向物流供应商选择问题的直觉模糊决策矩阵,提出了基于直觉模糊熵和TOPSIS法(逼近理想解的排序方法)的逆向物流供应商评价方法.最后通过数值分析验证了该方法的可行性与有效性.

基于GOWA算子的直觉模糊多属性决策方法

针对直觉模糊环境下的多属性决策问题,提出了一种基于广义有序加权平均(GOWA)算子的决策方法。首先构造了直觉模糊集相对隶属度和相对非隶属度计算公式,使得决策方案的定性、定量指标的属性评价值和权重都可以用直觉模糊集进行统一描述,然后提出能集结直觉模糊集的GOWA算子,进而建立了直觉模糊多属性决策问题的GOWA决策方法。最后利用一个实例对文中模型与方法进行了验证、说明。