多目标模糊决策的Vague软集法

在智能领域中对Vague集和软集的研究已越来越广泛和深入,两者均已应用于决策问题中。为了更加有效地进行模糊决策,提出了一种基于Vague软关系的模糊决策方法。定义Vague软关系,构造Vague软集间的关系表格,利用一个新的评分函数对目标进行排序,选出最优目标。通过实例阐明该方法的有效性和实用性。     

基于Vague集的多目标模糊决策方法

提出了一种新的基于Vaguc集的多目标模糊决策算法,解决了文献[1]和[2]所存在的缺陷,并通过实例验证,而且定义的函数涵义明确。     

Vague集的多目标模糊决策方法

在进行了阐述Vague集的相关概念和运算后,对多目标模糊决策进行了定义,给出多目标模糊决策的基本思路,并对已有的基于Vague集的多目标模糊决策方法进行了分析,得出现有Vague集的多目标模糊决策方法存在着缺陷,从而提出了一种新的多目标模糊决策的Vague集方法,该方法利用一个新的评分函数对方案进行排序,选出最优方案.最后给出其相关性质,证明其解决了现有方法的缺陷,并通过实例阐明本文方法的有效性和优越性.     

基于Vague集模糊一致关系的多目标模糊决策

基于Vague集理论和模糊一致关系理论,提出了一种新的多目标模糊决策方法。这种决策方法综合考虑方案满足目标条件的可能性、不满足的可能性和未知的可能性三个方面的因素,分别对每个目标条件建立模糊优先关系矩阵和模糊一致矩阵,最后得出用于评估每种方案的真、假两方面的优度值,从支持和反对两方面来进行综合评估,给出方案的优劣程度排序,从而选出最优的方案。     

基于Vague集的多目标决策

通过研究Vague集合转化为Fuzzy集的不同方法,采用将Vague集转化为Fuzzy集的方法来研究多目标决策问题,提出了基于Vague集的简化的模糊多目标决策算法,并通过实例验证了算法的有效性。     

基于预处理的Vague集多目标决策研究

针对目前Vague集中记分函数选择困难问题,提出了一种新的Vague值方案比较方法,在此基础上提出了基于预处理的Vague集最优多目标决策算法,并通过实例验证了该算法的有效性。     

基于Vague集的多准则模糊决策方法

基于Vague集的模糊决策方法的提出，为决策系统提供了一个有用的工具．对模糊条件下的多准则决策问题，指出了采用Vague集进行多准则模糊决策的现有计分函数的不足，根据Vague集的性质提出了二种新的方案选择方法：记分函数法和加权记分函数法。对已有的Vgue集记分函数法进行了分析与联系，并通过例子阐明本文方法的有效性和优越性．     

基于Vague集的模糊决策方法

目前在智能领域中对Vague集的研究已越来越广泛与深入．并运用于决策问题中．为了更加有效地进行模糊决策，提出了一个基于Vague集的模糊决策方法．在这个方法中，对约束条件，从它出现的可能性和不出现的可能性以及未知是否出现的可能性三个方面去综合处理．使得决策更加准确和有效．还给出了一个实例说明这种基于Vague集的模糊决策方法．这个基于Vague集的模糊决策方法的提出，为决策系统提供了一个有用的工具．     

Vague软集的新模糊熵及其应用

依据软集、Vague集、Vague软集现有理论,参考Vague集模糊熵度量方法,对Vague 软集模糊熵的公理化定义进行了补充,修正了原有公理化定义中不完整的地方;提出了一种新的计算Vague 软集模糊熵的公式,并给出了其在决策中的应用实例及分析。实例分析表明该Vague 软集模糊熵公式具有良好的应用效果。     

多准则模糊决策的区间值Vague集方法

区间值（i-v）模糊集合和Vague集是不精确知识表达的两种新理论。他们已被广泛地应用于决策系统中对不确定决策数据的描述。因此在Vague集基础上给出i-v Vague集的相关概念及性质,并将实数型Vague集群决策上的记分函数方法扩展到i-v Vague集上,提出新的记分函数,并用实例比较改进的记分函数与各种记分函数方法的优劣性。     

Multicriteria fuzzy decision-making methods based on intuitionistic fuzzy sets

In this paper, a new method for handling multicriteria fuzzy decision-making problems based on intuitionistic fuzzy sets is presented. The proposed method allows the degrees of satisfiability and non-satisfiability of each alternative with respect to a set of criteria to be represented by intuitionistic fuzzy sets, respectively. Furthermore, the proposed method allows the decision-maker to assign the degrees of membership and non-membership of the criteria to the fuzzy concept “importance.” The method proposed here can provide a useful way to efficiently help the decision-maker to make his decision.     

Vague集多指标决策的模糊值线性序法

就Vague集的多指标决策问题,提出了一种新的多指标决策方法。该方法首先将Vague值转化为模糊值,从而建立模糊值矩阵,由模糊值矩阵按各指标对应值的大小对方案进行排序,形成多个线性序,进而由线性序来构造模糊优先矩阵,然后通过对模糊优先矩阵进行截割,得到方案的优劣程度排序,从而选出最优方案。最后通过一个实例说明此方法的具体决策过程。     

Multi-criteria decision-making method based on interval-valued intuitionistic fuzzy sets

Out of several generalizations of fuzzy set theory for various objectives, the notions introduced by Atanassov, 1983, Atanassov and Gargov, 1989 in defining intuitionistic fuzzy sets and interval-valued intuitionistic fuzzy sets are interesting and very useful in modeling real life problems. Ranking of interval-valued intuitionistic fuzzy sets plays a vital role in decision-making, data analysis, artificial intelligence and socioeconomic system and it was studied in Xu, 2007c, Xu and Chen, 2007a, Ye, 2009. In this paper a new method for ranking interval-valued intuitionistic fuzzy sets has been introduced and studied. The method is illustrated by numerical examples and compared with other methods. And then a new method for handling multi-criteria fuzzy decision-making problems based on interval-valued intuitionistic fuzzy sets is presented in which criterion values for alternatives are interval-valued intuitionistic fuzzy sets. The method proposed here can provide a useful way to efficiently help the decision-maker to make his decision. An illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.     

Multicriteria fuzzy decision making based on interval-valued intuitionistic fuzzy sets

In this paper, we present a new method for multicriteria fuzzy decision making based on interval-valued intuitionistic fuzzy sets, where interval-valued intuitionistic fuzzy values are used to represent evaluating values of the decision-maker with respect to alternatives. First, we propose a new method for ranking interval-valued intuitionistic fuzzy values. Based on the proposed fuzzy ranking method of interval-valued intuitionistic fuzzy values, we propose a new method for multicriteria fuzzy decision making. The proposed multicriteria fuzzy decision making method outperforms Ye’s method (2009) due to the fact that the proposed method can overcome the drawback of Ye’s method (2009), where the drawback of Ye’s method is that it can not distinguish the ranking order between alternatives in some situations. The proposed method provides us with a useful way for dealing with multicriteria fuzzy decision making problems based on interval-valued intuitionistic fuzzy sets.     

Improved method of multicriteria fuzzy decision-making based on vague sets

An improved method is presented, which provides improved score functions to measure the degree of suitability of each of a set of alternatives, with respect to a set of criteria presented with vague values. The improved algorithm for score functions is introduced by taking into account the effect of an unknown degree (hesitancy degree) of the vague values on the degree of suitability to which each alternative satisfies the decision-maker’s requirement. The meaning of the proposed function is more transparent than that of other existing functions, which are not reasonable in some cases. The proposed function illustrates that it has stronger discrimination in comparison with previous functions. The applicability of this improved multicriteria fuzzy decision-making approach is also demonstrated by means of examples. The improved method can be used to rank the decision alternatives according to the decision criteria. The functions proposed in this paper can provide a more useful technique than previous functions, in order to efficiently help the decision-maker.     

基于Vague软集的模糊群决策方法研究

运用传统的模糊集进行模糊型群决策时存在一定的困难,而Vague软集是一种处理不确定信息的重要工具。为此,给出了一种加权的Vague软集间相似度定义,并运用Vague软集对备选方案进行评判;在此基础上运用正态云模型进行群体一致性评判,将基于Vague软集的模糊群决策方法应用于供应商选择问题中,结果表明,Vague软集能极大地提高模糊群决策的科学性和有效性。     

基于软粗糙集的犹豫模糊三支决策方法

三支决策理论采取“三分而治”的处理思路,为复杂问题求解提供了一种简洁高效的解决方案.对此,借助软集理论研究犹豫模糊集和三支决策方法,通过定义犹豫模糊集的值空间和值陪集,引入犹豫模糊集的典范软集、单位区间参数化软集和导出犹豫模糊集等概念,解决犹豫模糊集和软集的相互表示问题.此外,利用软粗糙集理论建立一种基于犹豫模糊集的广义粗糙模型,借助给定的预决策集,计算软上近似集并确定评价函数,进而提出一种基于软粗糙集的犹豫模糊三支决策方法.最后,通过两个数值实例和相关对比分析,验证所提出三支决策方法的合理性和有效性.