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Journal ArticleDOI

Pythagorean fuzzy interactive Hamacher power aggregation operators for assessment of express service quality with entropy weight

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TLDR
This manuscript defined a Pythagorean fuzzy entropy measure, and established a method to determine the attribute weights, and explored a novel approach to manage multiple attribute decision making problems based on the conceived P FIHPWA and PFIHPWG operators.
Abstract
Reasonable and effective assessment of express service quality can help express company discover its own shortcomings and overcome them, which is crucial significant to enhance its service quality. When considering the decision assessment of express company, the key issue that emerge powerful ambiguity. Pythagorean fuzzy set as an efficient math tool can capture the indeterminacy successfully. The major focus of this manuscript is to explore various interactive Hamacher power aggregation operators for Pythagorean fuzzy numbers. Firstly, we defined novel interactive Hamacher operation, on this basis we presented some Pythagorean fuzzy interactive Hamacher power aggregation operators such as Pythagorean fuzzy interactive Hamacher power average, weighted average (PFIHPWA), ordered weighted average, Pythagorean fuzzy interactive Hamacher power geometric, weighted geometric (PFIHPWG) and ordered geometric operators,respectively. Meanwhile, we verified their general properties and specific cases as well. The salient feature of proposed operators is that they can not only reduce the impact of negative data and consider the interactions between membership and nonmembership degrees, but also provide more general results through a parameter. Secondly, we defined a Pythagorean fuzzy entropy measure, and then establish a method to determine the attribute weights. Further, based on the conceived PFIHPWA and PFIHPWG operators we explored a novel approach to manage multiple attribute decision making problems. At last, the proposed techniques are carried out in a real application concerning on the assessment of express service quality to display the applicability and effectiveness, as well as the influence of changed parameters on the results. In addition, its advantages are displayed by a systematic comparison with relevant approaches.

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Citations
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Robust Aggregation Operators for Intuitionistic Fuzzy Hypersoft Set With Their Application to Solve MCDM Problem.

TL;DR: In this article, the authors investigated the multi-criteria decision-making complications under intuitionistic fuzzy hypersoft set (IFHSS) information, which is a proper extension of the intuitionistic soft set.
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Sine trigonometric operational laws and its based Pythagorean fuzzy aggregation operators for group decision-making process

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References
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Journal ArticleDOI

Pythagorean membership grades in multicriteria decision making

TL;DR: The issue of having to choose a best alternative in multicriteria decision making leads the problem of comparing Pythagorean membership grades to be considered, and a variety of aggregation operations are introduced for these Pythagorian fuzzy subsets.
Proceedings ArticleDOI

Pythagorean fuzzy subsets

TL;DR: A new class of non-standard fuzzy subset called Pythagorean fuzzy subsets is introduced and the related idea of Pythgorean membership grades is introduced, with a focus on the negation operation and its relationship to the Pythagorian theorem.
Journal ArticleDOI

Extension of TOPSIS to Multiple Criteria Decision Making with Pythagorean Fuzzy Sets

TL;DR: Some novel operational laws of PFSs are defined and an extended technique for order preference by similarity to ideal solution method is proposed to deal effectively with them for the multicriteria decision‐making problems with PFS.
Journal ArticleDOI

The power average operator

TL;DR: The power average is introduced to provide an aggregation operator which allows argument values to support each other in the aggregation process and the supported aggregation facility of empowerment is extended to a wider class of mean operators, such as the OWA (ordered weighted averaging) operator and the generalized mean operator.