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The Maximizing Deviation Method Based on Interval-Valued Pythagorean Fuzzy Weighted Aggregating Operator for Multiple Criteria Group Decision Analysis

机译:基于间隔型毕达哥仑模糊加权聚合运算符的最大化偏差方法,用于多个标准组决策分析

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摘要

As a new extension of Pythagorean fuzzy set (also called Atanassov’s intuitionistic fuzzy set of second type), interval-valued Pythagorean fuzzy set which is parallel to Atanassov’s interval-valued intuitionistic fuzzy set has recently been developed to model imprecise and ambiguous information in practical group decision making problems. The aim of this paper is to put forward a novel decision making method for handling multiple criteria group decision making problems within interval-valued Pythagorean fuzzy environment based on interval-valued Pythagorean fuzzy numbers (IVPFNs). There are three key issues being addressed in this approach. The first is to introduce an interval-valued Pythagorean fuzzy weighted arithmetic averaging (IVPF-WAA) operator to aggregate the decision data in order to get the overall preference values of alternatives. Some desirable properties of the IVPF-WAA operator are also investigated. Based on the idea of the maximizing deviation method, the second is to establish an optimization model for determining the weights of criteria for each expert. The third is to construct a minimizing consistency optimal model to derive the weights of criteria for the group. Finally, an illustrating example is given to verify the proposed approach.
机译:如毕达哥拉斯模糊集(也称为Atanassov的直觉模糊集第二类型的),区间值毕达哥拉斯模糊集合的一个新的扩展最近已开发在实际组模型不精确和不明确的信息,其是平行于Atanassov的区间直觉模糊集决策问题。本文的目的是提出一种新颖的决策方法用于处理多个标准组决策基于区间值毕达哥拉斯模糊数(IVPFNs)内区间值毕达哥拉斯模糊环境问题。有在这种方法正在解决三个关键问题。第一种方法是引入一个区间值毕达哥拉斯模糊加权算术平均(IVPF-WAA)算子聚集,以获得替代品的整体偏好值的判定数据。在IVPF-WAA算子的一些理想的性能也调查。基于离差最大化方法的思想,第二是要建立一个优化模型,用于确定的标准的权重为每个专家。第三是构造一个最小化的一致性最佳模型来推导的标准的权重的组。最后,示出了示例给出,以验证所提出的方法。

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