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TOPSIS approach for multi-attribute decision making problems based on n- intuitionistic polygonal fuzzy sets description

机译:基于n-直觉多边形模糊集描述的多属性决策问题的TOPSIS方法

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摘要

The polygonal fuzzy set describes a type of fuzzy information with the aid of the orderly representation of real numbers. It can approximate general fuzzy sets and overcome the complexity of arithmetic operations of fuzzy sets based on the Zadeh's extension principle. This research proposes the concept of an n-intuitionistic polygonal fuzzy set based on intuitionistic fuzzy and polygonal fuzzy sets. It then presents its arithmetic operation and Hamming distance formula. In addition, it adopts the standardized and weighting method to obtain the attribute matrix of the positive (negative) ideal solution, and calculates the Hamming distance between each scheme and the positive (negative) ideal solution to provide the TOPSIS (technique for order preference by similarity to an ideal solution) approach for the multi-attribute decision-making problem that describes the multi-attribute index information by n-intuitionistic polygonal fuzzy set. Finally, this research implements optimized ordering on the alternative solutions according to the degree of relative similarity and verifies its effectiveness and practicability through examples.
机译:多边形模糊集借助实数的有序表示来描述一种模糊信息。它可以基于Zadeh的可拓原理,对通用模糊集进行近似,克服了模糊集的算术运算的复杂性。本研究提出了一种基于直觉模糊和多边形模糊集的n-直觉多边形模糊集的概念。然后介绍了其算术运算和汉明距离公式。另外,它采用标准化和加权的方法来获得正(负)理想解的属性矩阵,并计算每个方案与正(负)理想解之间的汉明距离,以提供TOPSIS(定序偏好技术)。多属性决策问题的方法(通过n直觉多边形模糊集描述多属性索引信息)。最后,本研究根据相对相似度对备选方案进行了优化排序,并通过实例验证了其有效性和实用性。

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