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TOPSIS-Based Nonlinear-Programming Methodology for Multiattribute Decision Making With Interval-Valued Intuitionistic Fuzzy Sets

机译:基于TOPSIS的非线性规划的区间值直觉模糊集多属性决策方法

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Interval-valued intuitionistic fuzzy (IVIF) sets are useful to deal with fuzziness inherent in decision data and decision-making processes. The aim of this paper is to develop a nonlinear-programming methodology that is based on the technique for order preference by similarity to ideal solution to solve multiattribute decision-making (MADM) problems with both ratings of alternatives on attributes and weights of attributes expressed with IVIF sets. In this methodology, nonlinear-programming models are constructed on the basis of the concepts of the relative-closeness coefficient and the weighted-Euclidean distance. Simpler auxiliary nonlinear-programming models are further deduced to calculate relative-closeness of IF sets of alternatives to the IVIF-positive ideal solution, which can be used to generate the ranking order of alternatives. The proposed methodology is validated and compared with other similar methods. A real example is examined to demonstrate the applicability and validity of the methodology proposed in this paper.
机译:区间值直觉模糊(IVIF)集可用于处理决策数据和决策过程中固有的模糊性。本文的目的是开发一种非线性编程方法,该方法基于顺序偏好技术,通过类似于理想解决方案的方法来解决多属性决策(MADM)问题,该方法具有对属性的备选方案的评级以及用权重表示的属性的权重IVIF集。在这种方法中,非线性规划模型是根据相对接近系数和加权欧几里德距离的概念构建的。进一步推导出更简单的辅助非线性规划模型,以计算IF替代方案与IVIF阳性理想解的IF集的相对接近度,该模型可用于生成替代方案的排名顺序。所提出的方法已得到验证,并与其他类似方法进行了比较。研究了一个真实的例子,以证明本文提出的方法的适用性和有效性。

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