Pythagorean fuzzy power aggregation operators in multiple attribute decision making

Wei, Guiwu; Lu, Mingyue

doi:10.1002/int.21946

Cited by 330 publications

(197 citation statements)

References 69 publications

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“…For example, Wei proposed some useful PF interaction aggregation operators to solve MCDA problems in the PF context. Wei and Lu utilized several valuable PF power aggregation operators to address MCDA problems. Rahman et al developed new PF weighted geometric aggregation operators to conduct group decision analysis for plant location selection.…”

Section: Introductionmentioning

confidence: 99%

Multiple criteria decision analysis under complex uncertainty: A Pearson-like correlation-based Pythagorean fuzzy compromise approach

Chen

2018

Int J Intell Syst

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The aim of this article is to develop a novel multiple criteria decision analysis (MCDA) method using a Pearson‐like correlation‐based Pythagorean fuzzy (PF) compromise approach under complex uncertainty based on PF sets and interval‐valued Pythagorean fuzzy (IVPF) sets. Because of the complexity and ambiguity involved in real‐life decision‐making situations, this article utilizes the theory of Pythagorean fuzziness, which is characterized by flexible degrees of membership, nonmembership, and indeterminacy to describe uncertain information more comprehensively. PF and IVPF sets possess exceptional abilities to accurately reflect the uncertainty, fuzziness, and vagueness inherent in the decision information. However, manipulating PF and IVPF information is a complicated and difficult task for most decision makers. In this regard, this article extends the well‐known and widely used concept of correlation coefficients to develop simple and effective compromise models for solving MCDA problems in PF and IVPF contexts. This article conducts an extended analysis of Pearson‐like correlation coefficients for PF and IVPF sets separately and introduces new concepts of PF and IVPF correlation coefficients to furnish a solid basis for the proposed methodology. Furthermore, this article develops useful concepts of PF and IVPF correlation‐based closeness coefficients to simultaneously measure the relative closeness to the positive‐ideal PF/IVPF solutions and the relative remoteness from the negative‐ideal PF/IVPF solutions. On the basis of the developed concepts, this article proposes a novel Pearson‐like correlation‐based PF/IVPF compromise approach to address uncertain MCDA problems involving PF/IVPF information and determine the ultimate priority orders among competing alternatives. Finally, this article provides an illustrative application about a financing decision of working capital management to verify the developed approach and demonstrate its feasibility and practicality.

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Section: Introductionmentioning

confidence: 99%

Multiple criteria decision analysis under complex uncertainty: A Pearson-like correlation-based Pythagorean fuzzy compromise approach

Chen

2018

Int J Intell Syst

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“…Finally we propose the modifications of these theorems and equations. In the future, we shall continue working in the extension and application of the developed operators to other domains and fuzzy setting, such as picture fuzzy sets, dual hesitant fuzzy sets, and so on [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22].…”

Section: Resultsmentioning

confidence: 99%

Correction to “Pythagorean fuzzy interaction aggregation operators and their application to multiple attribute decision making”

Wei

2018

IFS

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“…Actually, the space membership degree of PFS is greater than that of IFS, this implies that the class of PFS is greater than that of IFS. Since the PFS was proposed, it has been widely studied and applied in many fields, we can see the references …”

Section: Introductionmentioning

confidence: 99%

Some cosine similarity measures and distance measures between q -rung orthopair fuzzy sets

2019

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In this paper, we consider some cosine similarity measures and distance measures between q‐rung orthopair fuzzy sets (q‐ROFSs). First, we define a cosine similarity measure and a Euclidean distance measure of q‐ROFSs, their properties are also studied. Considering that the cosine measure does not satisfy the axiom of similarity measure, then we propose a method to construct other similarity measures between q‐ROFSs based on the proposed cosine similarity and Euclidean distance measures, and it satisfies with the axiom of the similarity measure. Furthermore, we obtain a cosine distance measure between q‐ROFSs by using the relationship between the similarity and distance measures, then we extend technique for order of preference by similarity to the ideal solution method to the proposed cosine distance measure, which can deal with the related decision‐making problems not only from the point of view of geometry but also from the point of view of algebra. Finally, we give a practical example to illustrate the reasonableness and effectiveness of the proposed method, which is also compared with other existing methods.

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Pythagorean fuzzy power aggregation operators in multiple attribute decision making

Cited by 330 publications

References 69 publications

Multiple criteria decision analysis under complex uncertainty: A Pearson-like correlation-based Pythagorean fuzzy compromise approach

Multiple criteria decision analysis under complex uncertainty: A Pearson-like correlation-based Pythagorean fuzzy compromise approach

Correction to “Pythagorean fuzzy interaction aggregation operators and their application to multiple attribute decision making”

Some cosine similarity measures and distance measures between q -rung orthopair fuzzy sets

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