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The maximizing deviation method for group multiple attribute decision making under linguistic environment

机译：语言环境下群体多属性决策的最大偏差法

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摘要

The aim of this paper is to put forward a method for multi-attribute decision making problems with linguistic information, in which the preference values take the form of linguistic variables. An aggregating operator named linguistic weighted arithmetic averaging (LWAA) operator is introduced to aggregate the given decision information to get the overall preference value of each alternative. Some properties of the LWAA operator are also investigated. Based on the idea that the attribute with a larger deviation value among alternatives should be evaluated a larger weight, a method to determine the optimal weighting vector of LWAA operator is developed under the assumption that attribute weights are completely unknown. The based approach is extended to the situation where partially weight information can be obtained by solving a constrained non-linear optimization problem. Then a procedure to group multiple attribute decision making is provided under linguistic environment. Finally, an example of risk investment problem is given to verify the proposed approach; a comparative study to fuzzy ordered weighted averaging (F-OWA) operator methods is also demonstrated.
机译：本文的目的是提出一种针对语言信息的多属性决策问题的方法，其中偏好值采用语言变量的形式。引入了一个称为语言加权算术平均（LWAA）运算符的聚合运算符，以聚合给定的决策信息，以获得每个备选方案的总体偏好值。还研究了LWAA运算符的某些属性。基于对替代方案中具有较大偏差值的属性进行较大权重评估的思想，在属性权重完全未知的前提下，开发了一种确定LWAA算子最佳加权向量的方法。基于方法的方法扩展到可以通过解决约束非线性优化问题来获得部分权重信息的情况。然后提供了一种在语言环境下对多属性决策进行分组的过程。最后，以风险投资问题为例，验证了该方法的有效性。还证明了对模糊有序加权平均（F-OWA）算子方法的比较研究。

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