A comparative study of ranking fuzzy numbers based on regular weighted function

Fuzzy systems have gained more and more attention from researchers and practitioners of various fields. In such systems, the output represented by a fuzzy set sometimes needs to be transformed into a scalar value, and this task is known as the defuzzification process. Several analytic methods have been proposed for this problem, but in this paper, the researchers suggest a modified approach to the problem of defuzzification, using the bi-symmetric weighted distance between two fuzzy numbers. This defuzzification can be used as a crisp approximation with respect to a fuzzy quantity. By considering this and with benchmark between fuzzy numbers, we can present a method for ranking, which can effectively rank variou s fuzzy numbers and their images and overcome the shortcomings of the previous techniques. After illustrating many numerical examples, following our procedure, the ranking results become valid.     

基于质心和破碎度的模糊数排序

定义模糊数的破碎度概念,并且结合模糊数的质心给出模糊数排序的新指标。这种排序指标能够在一定程度上克服已有排序方法的某些缺陷,并且有效地实现各种模糊数的排序;文章最后通过算例分析,证明基于质心和破碎度的模糊数排序是完全可行的。     

基于模糊数整体和局部特征的一种新排序方法

利用反映模糊数整体和局部特征的三个重要指标:模糊数的均值,截集的中点和扩展,本文提出一种新的模糊数排序方法.该方法将每个模糊数独立地映射到实数轴上,得到一个以数字大小为基准的自然顺序,不仅体现决策者对各排序指标的偏好,而且无需对模糊数进行两两比较,计算简便,易于理解,尤其是对三角和梯形模糊数而言,数值实验表明该方法在一定程度上克服了已有方法的缺陷.     

基于Hausdorff距离的模糊数互补判断矩阵排序研究

基于Bonissone近似计算、Hausdorff距离和模糊折衷型决策方法,给出带有梯形模糊数互补判断矩阵的一种排序方法。同时给出精确值、三角模糊数的互补判断矩阵转化为梯形模糊数互补判断矩阵的方法,因此本文方法同样适合于处理精确值、三角模糊数的互补判断矩阵的排序问题。最后用算例说明了计算过程。     

Comparison of fuzzy numbers using a fuzzy distance measure

A new approach for ranking fuzzy numbers based on a distance measure is introduced. A new class of distance measures for interval numbers that takes into account all the points in both intervals is developed first, and then it is used to formulate the distance measure for fuzzy numbers. The approach is illustrated by numerical examples, showing that it overcomes several shortcomings such as the indiscriminative and counterintuitive behavior of several existing fuzzy ranking approaches.     

Selecting IS personnel use fuzzy GDSS based on metric distance method

In this paper we propose a new approach to rank fuzzy numbers by metric distance. For showing our method is a good ranking method, we give two examples to compare with other methods. The paper also developes a computer-based group decision support system, FMCGDSS, to increase the recruiting productivity and to easily compare our method with other fuzzy number ranking methods. The FMCGDSS includes three ranking methods: intuition ranking, Lee and Li's fuzzy mean/spread and our metric distance method to help manager make better decision under fuzzy circumstance. The result indicates that the new method is coincident with the intuition ranking and the Lee and Li's fuzzy mean/spread method on each type weight.     

模糊多属性群体决策模糊距离折中比值法及应用

为解决复杂条件下的模糊多属性群体决策问题,利用模糊距离的概念,提出了模糊距离折中比值法(FCRM)。在FCRM中,属性权重和定性属性评估值由语言变量和三角模糊数描述,并用模糊距离度量模糊数之间的距离。FCRM的决策原则是所选择的最优解在尽可能地贴近正理想解的同时尽可能地远离负理想解,同时充分考虑多个决策者的主观态度。文中详细阐述了FCRM的决策过程,通过实例将其应用于军事航线优选问题并与其他相关方法进行了比较分析,证实了该方法的有效性。     

On the nearest parametric approximation of a fuzzy number

Many nearest parametric approximation methods of fuzzy sets are proposed in the literature. It is clear that the specific approximations may lead to the loss of information about fuzziness. To overcome this problem, most of these methods rely on the minimization of the distance between the original fuzzy set and its approximation. But these approximations mostly are not flexible to the decision maker's choice. Hence, in this paper, we offer a parametric fuzzy approximation method based on the decision maker's strategy as an extension of trapezoidal approximation of a fuzzy number. This method comprises the selection of the form of the parametric membership function and its evaluation.     

Ranking fuzzy numbers by distance minimization

In this paper, we proposed a defuzzification using minimizer of the distance between the two fuzzy numbers. Then, we obtain the nearest point with respect to a fuzzy numbers and by considering the nearest point, we can present a ranking method for the fuzzy numbers. Also we give two new properties for ordering. Theorems and remarks are proposed for existence and uniqueness of the nearest point. The method is illustrated by numerical examples and compared with other methods.     

梯形模糊数的有序表示及中心平均排序方法

模糊数的排序在决策分析和优化问题中占有十分重要的地位,而一般模糊数均可近似分解为若干分片小梯形的叠加形式,故梯形模糊数的排序问题至关重要!本文首先引入等距分片方法对梯形模糊数实施纵向分割,进而获得梯形模糊数的有序表示。其次,依中心平均加权准则改进梯形模糊数的横向和纵向中心坐标公式,并提出新的指标排序准则。最后,通过实例分析考证了新的排序方法的有效性。     

Total ordering for intuitionistic fuzzy numbers

Intuitionistic fuzzy set plays a vital role in decision making, data analysis, and artificial intelligence. Many decision‐making problems consist of different types of datum, where fuzzy set theoretical approaches may fail to obtain the optimal decision. Numerous approaches for intuitionistic fuzzy decision‐making problem have been introduced in the literature to overcome these short comings. But there is no single approach that can be used to solve all kinds of problems because of the partial ordering defined on the collection of intuitionistic fuzzy numbers (IFNs). Even though ranking of fuzzy numbers have been studied from early seventies in the last century, a total order on the entire class of fuzzy numbers has been introduced by Wang and Wang (Fuzzy Sets Syst 2014, 243, 131–141) only on 2014. A total order on the collection of all IFN is an open problem till today. In this article, a total order on the entire class of IFN using upper lower dense sequence in the interval [0, 1] is proposed and compared with existing techniques using illustrative examples, further an algorithm (which is problem independent) for solving any intuitionistic fuzzy multicriteria decision‐making problem (Intuitionistic fuzzy MCDM) is introduced. This new total ordering on IFNs generalizes the total ordering defined in Wang and Wang ( 22 ) for fuzzy numbers. © 2016 Wiley Periodicals, Inc. Complexity 21: 54–66, 2016     

具有模糊信息的多目标运输问题求解

提出一种求解具有模糊信息的多目标运输问题的方法。利用专家意见通过模糊算法集给从各产地到各目的地运送单位物资的模糊综合指标值,运用一种对模糊数排序的方法,将模糊多目标运输问题转化为单目标的运输问题进行求解,最后给出了一个数值例子。     

A new parametric method for ranking fuzzy numbers

Ranking fuzzy numbers is important in decision-making, data analysis, artificial intelligence, economic systems and operations research. In this paper, to overcome the limitations of the existing studies and simplify the computational procedures an approach to ranking fuzzy numbers based on α$\alpha$-cuts is proposed. The approach is illustrated by numerical examples, showing that it overcomes several shortcomings such as the indiscriminative and counterintuitive behavior of existing fuzzy ranking approaches.     

一种基于散度的模糊数排序方法

引用一种距离测度及模糊数的权重面积,建立了一种基于散度的模糊数排序指标.新的排序指标不仅引入了两个参考对象,即两个模糊数的极大和极小(M),(N),同时还考虑了模糊数本身的影响和决策者的决策态度.排序方法不仅计算简单、易于操作,而且还具有良好的性质.算例分析表明本文所提出的排序方法在一定程度上克服了现有方法的缺陷.     

RM approach for ranking of generalized trapezoidal fuzzy numbers

Ranking of fuzzy numbers play an important role in decision making, optimization and forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. In this paper, with the help of several counter examples, it is proved that ranking method proposed by Chen and Chen (Expert Systems with Applications 36 (3): 6833) is incorrect. The main aim of this paper is to propose a new approach for the ranking of generalized trapezoidal fuzzy numbers. The proposed ranking approach is based on rank and mode so it is named as an RM approach. The main advantage of the proposed approach is that the proposed approach provides the correct ordering of generalized and normal trapezoidal fuzzy numbers and also the proposed approach is very simple and easy to apply in the real life problems. It is shown that proposed ranking function satisfies all the reasonable properties of fuzzy quantities proposed by Wang and Kerre (Fuzzy Sets and Systems 118 (3): 375).     

A new method for solving linear multi-objective transportation problems with fuzzy parameters

There are several methods in the literature for solving transportation problems by representing the parameters as normal fuzzy numbers. Chiang [J. Chiang, The optimal solution of the transportation problem with fuzzy demand and fuzzy product, J. Inform. Sci. Eng. 21 (2005) 439-451] pointed out that it is better to represent the parameters as (λ, ρ) interval-valued fuzzy numbers instead of normal fuzzy numbers and proposed a method to find the optimal solution of single objective transportation problems by representing the availability and demand as (λ, ρ) interval-valued fuzzy numbers. In this paper, the shortcomings of the existing method are pointed out and to overcome these shortcomings, a new method is proposed to find solution of a linear multi-objective transportation problem by representing all the parameters as (λ, ρ) interval-valued fuzzy numbers. To illustrate the proposed method a numerical example is solved. The advantages of the proposed method over existing method are also discussed.     

区间值模糊线性规划在证券组合投资优化中的应用

针对期望收益率与风险损失率为区间值模糊数的特征,就证券组合投资问题建立了一种区间值模糊线性规划模型,运用一种对区间值模糊数排序的新算法,将模型转化为经典的线性规划问题进行求解,最后通过一个算例说明其有效性和可靠性,为证券组合投资优化问题的解决提供了一种新的方法,对证券组合的理性投资具有重要的指导意义.     

A new method for ranking fuzzy numbers and its application to group decision making

In this paper, a new method for comparing fuzzy numbers based on a fuzzy probabilistic preference relation is introduced. The ranking order of fuzzy numbers with the weighted confidence level is derived from the pairwise comparison matrix based on 0.5-transitivity of the fuzzy probabilistic preference relation. The main difference between the proposed method and existing ones is that the comparison result between two fuzzy numbers is expressed as a fuzzy set instead of a crisp one. As such, the ranking order of n fuzzy numbers provides more information on the uncertainty level of the comparison. Illustrated by comparative examples, the proposed method overcomes certain unreasonable (due to the violation of the inequality properties) and indiscriminative problems exhibited by some existing methods. More importantly, the proposed method is able to provide decision makers with the probability of making errors when a crisp ranking order is obtained. The proposed method is also able to provide a probability-based explanation for conflicts among the comparison results provided by some existing methods using a proper ranking order, which ensures that ties of alternatives can be broken.     

Ranking fuzzy numbers with integral value

Ranking fuzzy numbers is important in decision making. Since very often the alternatives are evaluated by fuzzy numbers in a vague environment, a comparison between these fuzzy numbers is indeed a comparison between alternatives. This paper proposes a method of ranking fuzzy numbers with integral value. The method, which is independent of the type of membership functions used and the normality of the functions, can rank more than two fuzzy numbers simultaneously. It is relatively simple in computation, especially in ranking triangular and trapezoidal fuzzy numbers. Further, an index of optimism is used to reflect the decision maker's optimistic attitude. Discussion on comparative advantages is included.     

基于模糊熵-熵权法的混合多属性决策方法

针对决策信息以区间数、直觉模糊数和语言变量给出的混合多属性决策问题,提出了基于模糊熵-熵权法的混合多属性决策方法。通过规范化的方法把区间数转化为直觉模糊数,建立了直觉模糊数与语言变量的对应关系,把混合多属性决策信息统一在同一决策框架下;然后利用熵权法确定属性的客观权重区间,通过求解属性信息模糊熵最小的线性规划模型得到属性客观权重;再与主观赋权方法相结合确定属性的组合权重;最后应用相对熵排序法得到方案的最终排序结果。算例分析表明方法的可行性和实用性。