共查询到18条相似文献,搜索用时 234 毫秒
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《模糊系统与数学》2016,(4)
以熵理论为基础,针对属性权重和时间权重完全未知的动态多属性区间直觉模糊决策问题,首先针对现有区间直觉模糊熵公理化定义的缺陷进行了分析,提出一种改进的区间直觉模糊熵的公理化定义,并据此构造了区间直觉模糊熵的一个新的计算公式;其次,利用改进的区间直觉模糊熵确定属性权重;再次,基于时间度体现对近期数据的重视程度的基础上,利用时间权向量的信息熵为优化目标来确定时间权重;然后,利用区间直觉模糊几何加权算子进行集结,并利用区间直觉模糊集的排序函数对决策方案进行排序和择优。最后,通过一个实例分析,表明本文提出的方法的可行性和有效性,为动态多属性区间直觉模糊决策问题提供了一种新的方法和思路。 相似文献
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直觉模糊熵是直觉模糊集理论中的一个重要概念,反映了直觉模糊集的模糊程度和不确定程度.首先给出一种新的直觉模糊熵,并运用到多属性直觉模糊决策问题中.决策时根据直觉模糊熵计算属性权重,再综合决策者的偏好对各属性权重进行修正,然后使用直觉模糊集结算子和得分函数对方案进行排序,从而获得最优方案. 相似文献
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《数学的实践与认识》2013,(16)
公路工程评标定标问题的实质是多属性决策问题,专家对参评标书给出了各指标的区间直觉模糊属性值和属性权重的部分信息后,先定义了区间直觉模糊数的得分函数及标准得分差,进而提出了一种基于线性规划模型的区间直觉模糊多属性决策方法,最后通过实例对该决策途径的详细过程及有效性进行了说明. 相似文献
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《数学的实践与认识》2020,(6)
考虑了决策者对方案具有一定偏好,且偏好信息和决策信息都为区间直觉模糊数的多属性决策问题.首先,基于偏差极小化的思想,利用区间直觉模糊得分函数构造优化模型,计算属性权重,然后将TOPSIS方法拓展到区间直觉模糊环境中对方案进行排序,进而提出了一种有方案偏好的TOPSIS区间直觉模糊多属性决策方法.最后,通过实例表明了所提方法的有效性和实用性. 相似文献
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Multi-person multi-attribute decision making models under intuitionistic fuzzy environment 总被引:1,自引:0,他引:1
Zeshui Xu 《Fuzzy Optimization and Decision Making》2007,6(3):221-236
Intuitionistic fuzzy numbers, each of which is characterized by the degree of membership and the degree of non-membership
of an element, are a very useful means to depict the decision information in the process of decision making. In this article,
we investigate the group decision making problems in which all the information provided by the decision makers is expressed
as intuitionistic fuzzy decision matrices where each of the elements is characterized by intuitionistic fuzzy number, and
the information about attribute weights is partially known, which may be constructed by various forms. We first use the intuitionistic
fuzzy hybrid geometric (IFHG) operator to aggregate all individual intuitionistic fuzzy decision matrices provided by the
decision makers into the collective intuitionistic fuzzy decision matrix, then we utilize the score function to calculate
the score of each attribute value and construct the score matrix of the collective intuitionistic fuzzy decision matrix. Based
on the score matrix and the given attribute weight information, we establish some optimization models to determine the weights
of attributes. Furthermore, we utilize the obtained attribute weights and the intuitionistic fuzzy weighted geometric (IFWG)
operator to fuse the intuitionistic fuzzy information in the collective intuitionistic fuzzy decision matrix to get the overall
intuitionistic fuzzy values of alternatives by which the ranking of all the given alternatives can be found. Finally, we give
an illustrative example. 相似文献
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Dong Gun Park Young Chel Kwun Jin Han Park Il Young Park 《Mathematical and Computer Modelling》2009,50(9-10):1279-1293
In this paper, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFN), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and then we use the obtained attribute weights and the interval-valued intuitionistic fuzzy weighted geometric (IIFWG) operator to fuse the interval-valued intuitionistic fuzzy information in the collective interval-valued intuitionistic fuzzy decision matrix to get the overall interval-valued intuitionistic fuzzy values of alternatives, and then rank the alternatives according to the correlation coefficients between IVIFNs and select the most desirable one(s). Finally, a numerical example is used to illustrate the applicability of the proposed approach. 相似文献
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TOPSIS is one of the well-known methods for multiple attribute decision making (MADM). In this paper, we extend the TOPSIS method to solve multiple attribute group decision making (MAGDM) problems in interval-valued intuitionistic fuzzy environment in which all the preference information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFNs), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and construct the weighted collective interval-valued intuitionistic fuzzy decision matrix, and then determine the interval-valued intuitionistic positive-ideal solution and interval-valued intuitionistic negative-ideal solution. Based on different distance definitions, we calculate the relative closeness of each alternative to the interval-valued intuitionistic positive-ideal solution and rank the alternatives according to the relative closeness to the interval-valued intuitionistic positive-ideal solution and select the most desirable one(s). Finally, an example is used to illustrate the applicability of the proposed approach. 相似文献
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研究了属性权重完全未知的区间直觉梯形模糊数的多属性决策问题,结合TOPSIS方法定义了相对贴近度及总贴近度公式.首先由区间直觉梯形模糊数的Hamming距离给出了每个方案的属性与正负理想解的距离,基于此,给出了相对贴近度矩阵,根据所有决策方案的综合贴近度最小化建立多目标规划模型,从而确定属性的权重值,然后根据区间直觉梯形模糊数的加权算数平均算子求出各决策方案的总贴近度,根据总贴近度的大小对方案进行排序;最后,通过实例分析说明该方法的可行性和有效性. 相似文献
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The aim of this paper is to extend the VIKOR method for multiple attribute group decision making in interval-valued intuitionistic
fuzzy environment, in which all the preference information provided by the decision-makers is presented as interval-valued
intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy
number, and the information about attribute weights is partially known, which is an important research field in decision science
and operation research. First, we use the interval-valued intuitionistic fuzzy hybrid geometric operator to aggregate all
individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued
intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and
construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and
the given attribute weight information, we establish an optimization model to determine the weights of attributes, and then
determine the interval-valued intuitionistic positive-ideal solution and interval-valued intuitionistic negative-ideal solution.
We use the different distances to calculate the particular measure of closeness of each alternative to the interval-valued
intuitionistic positive-ideal solution. According to values of the particular measure, we rank the alternatives and then select
the most desirable one(s). Finally, a numerical example is used to illustrate the applicability of the proposed approach. 相似文献
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针对当前动态直觉模糊多属性决策方法存在的不足,提出一种基于时间度的动态直觉模糊妥协决策方法。引入时间度准则,基于逼近理想解法融合主客观两类赋权法,获得兼顾主观偏好和样本客观信息的时序权重,克服现有时序权重主观赋值的随意性,同时运用直觉模糊熵(IFE)确定不同时序状态下各属性权重;根据动态直觉模糊加权几何算子(DIFWG)集结不同时序直觉模糊决策矩阵,构造动态直觉模糊综合决策矩阵,并利用VIKOR法,提供兼顾群体效用最大化与个体后悔最小化的各方案妥协折中排序,得到与理想解最近的妥协方案;以分布式创新企业合作伙伴选择为例,验证该方法在实际决策过程中的可行性和有效性。 相似文献