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基于先进毕达哥拉斯模糊加权几何算子的多属性决策方法及其在房地产公司选择中的应用

Multi-attribute decision making method using advanced Pythagorean fuzzy weighted geometric operator and their applications for real estate company selection.

作者信息

Paul Tapas Kumar, Pal Madhumangal, Jana Chiranjibe

机构信息

Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore 721102, India.

出版信息

Heliyon. 2021 Jun 17;7(6):e07340. doi: 10.1016/j.heliyon.2021.e07340. eCollection 2021 Jun.

Abstract

In this paper, a novel multi-attribute decision-making method using Advanced Pythagorean fuzzy weighted geometric operator in a Pythagorean fuzzy environment is developed. Pythagorean fuzzy aggregation operators have drawbacks that they give indeterminate results in some special cases when membership value or non-membership value gets 0 value or 1 value and the weight vector is of type or . The Advanced Pythagorean fuzzy geometric operator, the proposed operator can overcome the drawbacks. In some situations, for example, where the sum of squares of membership degree and non-membership degree gets unit value of a Pythagorean fuzzy number, multi-attribute decision making (MADM) methods using some existing aggregation operators give unreasonable ranking orders (ROs) of alternatives or can't discriminate the ROs of alternatives. But the present MADM method can get over the drawbacks of the existing MADM methods. The present MADM method is devoted to eliminate the drawbacks of the existing MADM methods and to select the best real estate company for investment.

摘要

本文提出了一种在毕达哥拉斯模糊环境下使用高级毕达哥拉斯模糊加权几何算子的新型多属性决策方法。毕达哥拉斯模糊聚合算子存在一些缺点,即在某些特殊情况下,当隶属度值或非隶属度值为0或1且权重向量为 或 类型时,它们会给出不确定的结果。所提出的高级毕达哥拉斯模糊几何算子能够克服这些缺点。在某些情况下,例如,当隶属度和非隶属度的平方和等于毕达哥拉斯模糊数的单位值时,使用一些现有聚合算子的多属性决策(MADM)方法会给出不合理的备选方案排序顺序(ROs),或者无法区分备选方案的ROs。但本文提出的MADM方法可以克服现有MADM方法的缺点。本文提出的MADM方法致力于消除现有MADM方法的缺点,并选择最佳的房地产公司进行投资。

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