共查询到19条相似文献,搜索用时 375 毫秒
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针对决策信息为三角模糊数直觉模糊数(TFNIFN)且属性间存在相互关联的多属性群决策(MAGDM)问题,提出了一种基于三角模糊数直觉模糊PA (TFNIFPA)算子的决策方法.首先,基于TFNIFN的运算法则和PA (Power Average)算子,定义了TFNIFPA算子.然后,研究了该算子的一些性质,建立基于TFNIFPA算子的MAGDM模型,结合排序方法进行决策.最后通过MAGDM算例验证了该算子的有效性与可行性. 相似文献
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对属性权重信息完全未知且属性值为模糊数直觉模糊数的多属性决策问题进行了研究,定义了模糊数直觉模糊数的得分函数,进而提出了一种基于线性规划模型的模糊数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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针对属性值为直觉模糊数,已知部分属性偏好关系及属性交互类型的属性关联多属性决策问题给出决策方法.首先定义方案到正(负)理想方案的距离及各方案与正理想方案相对贴近度.然后以极大化各方案与相对贴近度为目标建立优化模型,确定出属性集的模糊测度.进而基于直觉模糊Choquet积分算子计算各方案的直觉模糊综合评价值,再根据直觉模糊数的得分值及精确度得到方案的排序.最后通过实例验证了方法的有效可行性. 相似文献
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针对决策信息为区间直觉梯形模糊数(IVITFN)且属性间存在相互关联的多属性群决策(MAGDM)问题,提出一种基于加权区间直觉梯形模糊Bonferroni平均(WIVITFBM)算子的决策方法.首先,基于IVITFN的运算法则和Bonferroni平均(BM)算子,定义了区间直觉梯形模糊Bonferroni平均(VITFBM)算子和WIVITFBM算子.然后,研究了这些算子的一些性质,建立基于WIVITFBM算子的MAGDM模型,结合排序方法进行决策。最后通过MAGDM算例验证了该算子的有效性与可行性。 相似文献
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梯形模糊数直觉模糊Bonferroni平均算子及其应用 总被引:1,自引:0,他引:1
本文研究决策信息为梯形模糊数直觉模糊数(TFNIFN)且属性间存在相互关联的多属性群决策(MAGDM)问题,提出一种基于梯形模糊数直觉模糊加权Bonferroni平均(TFNIFWBM)算子的决策方法.首先,介绍了TFNIFN的概念和运算法则,基于这些运算法则和Bonferroni平均(Bonferroni mean,BM)算子,定义了梯形模糊数直觉模糊Bonferroni平均算子和TFNIFWBM算子.然后,研究了这些算子的一些性质,建立基于TFNIFWBM算子的多属性群决策模型,结合排序方法进行决策.最后,将该方法应用在MAGDM中,算例结果表明了该方法的有效性与可行性. 相似文献
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针对决策信息为区间直觉梯形模糊数(IVITFN)且属性间存在相互关联的多属性群决策问题,提出了基于Choquet积分理论的区间直觉梯形模糊关联平均(IVITFCA)算子.首先,基于IVITFN的运算法则和Choquet积分,定义了IVITFCA算子,并研究了该算子的相关性质.然后,提出了基于IVITFCA算子的多属性群决策方法.最后,通过供应商选择算例证明了所提方法的有效性与可行性. 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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多属性决策过程中,每个方案的属性值有时体现为由直觉模糊数所刻划的语言变量,通过定义直觉模糊数间的距离,首先提出了基于直觉模糊数的TOPSIS方法;其次,考虑到在实际问题中往往会遇到不完备直觉模糊信息的事实,提出一种将不完备直觉模糊数完备化的方法,并建立了基于不完备直觉模糊信息的TOPSIS方法,同时通过实例说明该方法的有效性以及在多属性决策中的应用. 相似文献
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基于集对分析联系数的信息不完全直觉模糊多属性决策 总被引:2,自引:1,他引:1
信息不完全直觉模糊多属性决策是一类不确定性决策问题,其不确定性来自属性权重信息不完全和属性值的直觉模糊数表示.为了系统地刻画直觉模糊多属性决策中的不确定性,避免直觉模糊多属性决策中利用得分函数做决策的片面性和不准确性,可以将信息不完全的权重和直觉模糊数表示的属性值转化成集对分析理论中的联系数,并建立信息不完全直觉模糊多属性决策模型,通过对不确定性进行分析后作出决策.实例应用表明该决策方法具有合理性和可行性. 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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研究了属性值为实数且决策者对属性的偏好信息以直觉判断矩阵或残缺直觉判断矩阵给出的模糊多属性决策问题.首先介绍了直觉判断矩阵、一致性直觉判断矩阵、残缺直觉判断矩阵、一致性残缺直觉判断矩阵等概念,而后分别考虑关于直觉判断矩阵和残缺直觉判断矩阵的多属性决策问题,接着建立了基于直觉判断矩阵和残缺直觉判断矩阵的多属性群决策模型,通过求解这些模型获得属性的权重.进而给出了不同直觉偏好信息下的多属性决策方法.最后通过一个例子说明了该方法的可行性和实用性. 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