区间直觉模糊动态规划方法

基于直觉模糊集理论的思想与方法,探讨多阶段决策问题．运用分析技巧,构建直觉模糊集比较可能度公式及区间直觉模糊集比较可能度公式．在普通动态规划的基础上,提出区间直觉模糊动态规划及其最优解的概念,建立相应的数学模型及其最优解的算法,并指出直觉模糊动态规划是区间直觉模糊动态规划的特例．通过算例分析,说明了算法的合理性和可行性．为不确定动态规划和直觉模糊集理论的应用研究提供了新的思路．

     

区间直觉模糊粗糙集

将模糊粗糙集推广到区间直觉模糊粗糙集,基于区间直觉模糊等价关系和两个论域之间的一般区间直觉模糊关系,给出了区间直觉模糊粗糙集模型的不同形式,并讨论了一些相关性质。     

一种区间直觉模糊熵的构造方法

研究了区间直觉模糊熵。证明了三个直觉模糊熵公式的等价性。对直觉模糊熵公式进行推广,引入一个新的区间直觉模糊熵公式,该熵公式满足区间糊熵的公理化直觉模定义的4个条件。     

区间直觉模糊粗糙集的不确定性研究

对区间直觉模糊信息系统中近似集的不确定性进行了研究,给出了区间直觉模糊粗糙集的不确定性度量公式。首先在区间直觉模糊近似空间中,定义了一对具有对称性的新的区间直觉模糊上、下近似算子;其次给出了区间直觉模糊集粗糙隶属函数的定义并讨论了相关性质;最后利用区间直觉模糊粗糙隶属函数的区间直觉模糊熵,定义了区间直觉模糊粗糙集的模糊熵,并讨论了区间直觉模糊粗糙集的模糊熵为零的充要条件,证明了在区间直觉模糊近似空间中经典集合和它的余集的粗糙度量是相等的,以此说明定义的合理性。     

基于蕴涵的区间值直觉模糊粗糙集

提出一种基于区间值直觉模糊蕴涵的区间值直觉模糊粗糙集模型.首先,介绍了区间值直觉模糊集、区间值直觉模糊关系和区间值直觉模糊逻辑算子的概念;然后,利用区间值直觉模糊三角模和区间值直觉模糊蕴涵,在区间值直觉模糊近似空间中定义了区间值直觉模糊集的上近似和下近似;最后,给出并证明了这些近似算子的一些性质.     

区间直觉模糊连续熵及其多属性决策方法

提出了区间直觉模糊连续熵,并且研究了一种新的处理区间直觉模糊多属性决策问题的方法。基于连续有序加权平均（COWA）算子,给出了区间直觉模糊连续熵的概念,并且证明了区间直觉模糊连续熵满足区间直觉模糊熵的公理化定义的四个条件。在此基础上,针对属性权重信息完全未知的决策问题,通过衡量每一属性所含的信息量来确定属性权重。依据备选方案与理想方案间的加权相关系数,给出了一种新的区间直觉模糊多属性决策方法。实验结果验证了新的决策方法的可行性和有效性。     

基于覆盖的区间直觉模糊粗糙集

在经典的覆盖近似空间中,定义了区间直觉模糊概念的粗糙近似。通过区间直觉模糊覆盖概念,给出了一种基于区间直觉模糊覆盖的区间直觉模糊粗糙集模型。讨论了两种模型的一些相关性质。     

考虑未知属性权重的区间直觉模糊VIKOR方法

针对传统模糊集方法处理不确定性多属性决策问题时只考虑隶属度信息的缺点,提出了基于区间直觉模糊集的VIKOR决策方法。区间直觉模糊集用来处理区间语义评价信息。考虑属性权重未知的问题,基于区间直觉模糊数间的支持度确定属性权重,属性的支持度越高,则其权重越小。将区间直觉模糊交叉熵引入区间直觉模糊VIKOR方法用于计算区间直觉模糊数间的距离。最后以某手机设计方案评价为例,验证了所提方法的有效性。     

语言区间直觉模糊Frank算子

针对语言区间直觉模糊信息的集结问题,文中提出Frank集结算子,并构建解决供应商选择问题的群决策方法.首先引入拓展Frank t-模与s-模定义语言区间直觉模糊集的Frank运算法则,提出语言区间直觉模糊Frank加权平均(LIVIFFWA)算子与几何(LIVIFFWG)算子,证明算子的幂等性、封闭性、单调性等基本性质,剖析算子关于参数的退化性.然后,基于LIVIFFWA算子与LIVIFFWG算子构建语言区间直觉模糊多属性群决策方法,用于解决供应商决策问题.最后,通过共享单车回收供应商选择的案例分析验证文中决策方法的可行性和灵活性,讨论参数变化对决策结果的影响,并验证参数具有表征和反馈决策者态度的能力.     

支付值为区间直觉模糊集的矩阵对策的线性规划求解方法

提出了支付值为区间直觉模糊集的矩阵对策定义及其解的概念,将求解局中人的极大-极小与极小-极大策略问题转化为求解一对辅助的非线性多目标规划,进而转化为一对易于求解的原始-对偶线性规划.数值实例表明了所提方法的有效性和实用性.所提出的区间直觉模糊集矩阵对策理论与方法既是对经典矩阵对策理论的发展,又可为解决其他带有区间直觉模糊信息的对策问题提供新的途径.     

A method based on distance measure for interval-valued intuitionistic fuzzy group decision making

In this paper we introduce some relations and operations of interval-valued intuitionistic fuzzy numbers and define some types of matrices, including interval-valued intuitionistic fuzzy matrix, interval-valued intuitionistic fuzzy similarity matrix and interval-valued intuitionistic fuzzy equivalence matrix. We study their properties, develop a method based on distance measure for group decision making with interval-valued intuitionistic fuzzy matrices and, finally, provide an illustrative example.     

基于区间直觉模糊集的多准则决策方法

研究基于区间直觉模糊集的多准则决策方法.首先定义了区间直觉模糊点算子,并讨论了其性质;然后对区间直觉模糊集定义了一系列得分函数,并给出两种基于区间直觉模糊集的多准则决策方法.将该方法应用于区间直觉模糊集多准则决策问题,所得结果推广了有关直觉模糊集的相关结果.     

Some information measures for interval-valued intuitionistic fuzzy sets

A new information entropy measure of interval-valued intuitionistic fuzzy set (IvIFS) is proposed by using membership interval and non-membership interval of IvIFS, which complies with the extended form of Deluca-Termini axioms for fuzzy entropy. Then the cross-entropy of IvIFSs is presented and the relationship between the proposed entropy measures and the existing information measures of IvIFSs is discussed. Additionally, some numerical examples are given to illustrate the applications of the proposed entropy and cross-entropy of IvIFSs to pattern recognition and decision-making.     

Interval-valued intuitionistic fuzzy mathematical programming method for hybrid multi-criteria group decision making with interval-valued intuitionistic fuzzy truth degrees

As an important component of group decision making, the hybrid multi-criteria group decision making (MCGDM) is very complex and interesting in real applications. The purpose of this paper is to develop a novel interval-valued intuitionistic fuzzy (IVIF) mathematical programming method for hybrid MCGDM considering alternative comparisons with hesitancy degrees. The subjective preference relations between alternatives given by each decision maker (DM) are formulated as an IVIF set (IVIFS). The IVIFSs, intuitionistic fuzzy sets (IFSs), trapezoidal fuzzy numbers (TrFNs), linguistic variables, intervals and real numbers are used to represent the multiple types of criteria values. The information of criteria weights is incomplete. The IVIFS-type consistency and inconsistency indices are defined through considering the fuzzy positive and negative ideal solutions simultaneously. To determine the criteria weights, we construct a novel bi-objective IVIF mathematical programming of minimizing the inconsistency index and meanwhile maximizing the consistency index, which is solved by the technically developed linear goal programming approach. The individual ranking order of alternatives furnished by each DM is subsequently obtained according to the comprehensive relative closeness degrees of alternatives to the fuzzy positive ideal solution. The collective ranking order of alternatives is derived through establishing a new multi-objective assignment model. A real example of critical infrastructure evaluation is provided to demonstrate the applicability and effectiveness of this method.     

Entropy, similarity measure of interval-valued intuitionistic fuzzy sets and their applications

In this paper we propose an entropy measure for interval-valued intuitionistic fuzzy sets, which generalizes three entropy measures defined independently by Szmidt, Wang and Huang, for intuitionistic fuzzy sets. We also give an approach to construct similarity measures using entropy measures for interval-valued intuitionistic fuzzy sets. In particular, the proposed entropy measure for interval-valued intuitionistic fuzzy sets can yield a similarity measure. Several illustrative examples are given to demonstrate the practicality and effectiveness of the proposed formulas. We apply the similarity measure to solve problems on pattern recognitions, multi-criteria fuzzy decision making and medical diagnosis.     

Construction of admissible linear orders for interval-valued Atanassov intuitionistic fuzzy sets with an application to decision making

In this work we introduce a method for constructing linear orders between pairs of intervals by using aggregation functions. We adapt this method to the case of interval-valued Atanassov intuitionistic fuzzy sets and we apply these sets and the considered orders to a decision making problem.     

求解支付值为区间直觉模糊数的矩阵对策的线性规划方法

提出了支付值为区间直觉模糊集的矩阵对策定义及其解的概念, 将求解局中人的极大-极小与极小-极大策略问题转化为求解一对辅助的非线性多目标规划, 进而转化为一对易于求解的原始-对偶线性规划. 数值实例表明了所提方法的有效性和实用性. 所提出的区间直觉模糊集矩阵对策理论与方法既是对经典矩阵对策理论的发展, 又可为解决其他带有区间直觉模糊信息的对策问题提供新的途径.

     

区间直觉模糊信息的集成方法及其在决策中的应用

对区间直觉模糊信息的集成方法进行了研究.定义了区间直觉模糊数的一些运算法则,并基于这些运算法则,给出区间直觉模糊数的加权算术和加权几何集成算子.定义了区间直觉模糊数的得分函数和精确函数,进而给出了区间直觉模糊数的一种简单的排序方法.最后提供了一种基于区间直觉模糊信息的决策途径,并进行了实例分析.     

Choquet integrals of weighted intuitionistic fuzzy information

The Choquet integral is a very useful way of measuring the expected utility of an uncertain event [G. Choquet, Theory of capacities, Annales de l’institut Fourier 5 (1953) 131-295]. In this paper, we use the Choquet integral to propose some intuitionistic fuzzy aggregation operators. The operators not only consider the importance of the elements or their ordered positions, but also can reflect the correlations among the elements or their ordered positions. It is worth pointing out that most of the existing intuitionistic fuzzy aggregation operators are special cases of our operators. Moreover, we propose the interval-valued intuitionistic fuzzy correlated averaging operator and the interval-valued intuitionistic fuzzy correlated geometric operator to aggregate interval-valued intuitionistic fuzzy information, and apply them to a practical decision-making problem involving the prioritization of information technology improvement projects.     

A possibility degree method for interval-valued intuitionistic fuzzy multi-attribute group decision making

The ranking of interval-valued intuitionistic fuzzy sets (IVIFSs) is very important for the interval-valued intuitionistic fuzzy decision making. From the probability viewpoint, the possibility degree of comparison between two interval-valued intuitionistic fuzzy numbers (IVIFNs) is defined by using the notion of 2-dimensional random vector, and a new method is then developed to rank IVIFNs. Hereby the ordered weighted average operator and hybrid weighted average operator for IVIFNs are defined based on the Karnik–Mendel algorithms and employed to solve multi-attribute group decision making problems with IVIFNs. The individual overall attribute values of alternatives are obtained by using the weighted average operator for IVIFNs. By using the hybrid weighted average operator for IVIFNs, we can obtain the collective overall attribute values of alternatives, which are used to rank the alternatives. A numerical example is examined to illustrate the effectiveness and flexibility of the proposed method in this paper.