Pythagorean Fuzzy Multiattribute Group Decision Making with Probabilistic Information and OWA Approach

Zeng, Shouzhen

doi:10.1002/int.21886

Cited by 104 publications

(60 citation statements)

References 46 publications

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“…In this section, the proposed method is used to solve a problem studied previously by Zhang regarding the selection of the best photovoltaic cell in Pythagorean environment. The problem is described as follows.…”

Section: Numerical Examplementioning

confidence: 99%

“…Peng and Yang defined two operations, viz., division and subtraction between PFSs and discussed their properties based on Pythagorean aggregation operators in detail. Zeng presented Pythagorean fuzzy probabilistic ordered weighted averaging (PFPOWA) operator to develop a Pythagorean fuzzy multiattribute group decision making (MAGDM) method based on probabilistic information and the ordered weighted averaging (OWA) approach.…”

Section: Introductionmentioning

confidence: 99%

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Pythagorean fuzzy multicriteria group decision making through similarity measure based on point operators

Biswas

Sarkar

2018

Int. J. Intell. Syst.

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In this paper, a series of similarity measures based on point operators for Pythagorean fuzzy sets are proposed. Using the proposed similarity measures, two new aggregation operators, viz., Pythagorean fuzzy‐dependent averaging operator and Pythagorean fuzzy‐dependent geometric operator, are developed. The advantage of using these operators is that the influence of unfair arguments of aggregated results could be eliminated, since the associated weights are taken from the aggregated Pythagorean fuzzy arguments. Also, the proposed operators have the capability to adjust the degree of aggregated arguments with the controlling parameters. To establish the application potentiality of those operators, a methodology for solving multicriteria group decision‐making problems having Pythagorean fuzzy arguments is developed. A numerical example is provided to demonstrate the proficiency of the proposed method. The achieved results are compared with the results of other existing technique.

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Section: Numerical Examplementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pythagorean fuzzy multicriteria group decision making through similarity measure based on point operators

Biswas

Sarkar

2018

Int. J. Intell. Syst.

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“…The PFS has been investigated from different perspectives, including decision making technologies [5][6][7][8][9][10][11][12][13], aggregation operators [14][15][16][17][18][19][20][21][22], information measures [23][24][25] , the extensions of PFS [26][27][28][29][30][31], fundamental properties [32][33][34]. In particular, an extension of PFS named interval-valued Pythagorean fuzzy set (IVPFS) [10,21] is a hot topic at present [35].…”

Section: Introductionmentioning

confidence: 99%

New Operations for Interval-valued Pythagorean Fuzzy Set

Peng¹

2018

Scientia Iranica

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Interval-valued Pythagorean fuzzy set (IVPFS), originally proposed by Peng and Yang, is a novel tool to deal with vagueness and incertitude. As a generalized set, IVPFS has close relationship with interval-valued intuitionistic fuzzy set (IV-IFS). IVPFS can be reduced to IVIFS satisfying the condition µ + + ν + ≤ 1. However, the related operations of IVPFS do not take different conditions into consideration. In this paper, we initiate some new interval-valued Pythagorean fuzzy operators (♢, , ♠, ♣, , →, $) and discuss their properties in relation with some existing operators (∪, ∩, ⊕, ⊗) in detail. It will promote the development of interval-valued Pythagorean fuzzy operators. Later, we propose an algorithm to deal with multi-criteria decision making (MCDM) problem based on proposed ♠ operator. Finally, the effectiveness and feasibility of proposed algorithm is demonstrated by mine emergency decision making example.

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“…The goal of operationalizing the collaboration-based recommender system by using the PFSs was addressed by Reformat and Yager [18]. Zeng [19,20] developed a Pythagorean fuzzy multi-attribute group decision-making (MAGDM) method based on probabilistic information and the ordered weighted averaging (OWA) approach.…”

Section: Introductionmentioning

confidence: 99%

Multiple Criteria Group Decision-Making Considering Symmetry with Regards to the Positive and Negative Ideal Solutions via the Pythagorean Normal Cloud Model for Application to Economic Decisions

Zhou

Baležentis

et al. 2018

Symmetry

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Pythagorean fuzzy sets are highly appealing in dealing with uncertainty as they allow for greater flexibility in regards to the membership and non-membership degrees by extending the set of possible values. In this paper, we propose a multi-criteria group decision-making approach based on the Pythagorean normal cloud. Some cloud aggregation operators are presented in this paper to facilitate the appraisal of the underlying utilities of the alternatives under consideration. The concept and properties of the Pythagorean normal cloud and its backward generation algorithm, aggregation operators and distance measurement are outlined. The proposed approach resembles the TOPSIS technique, which, indeed, considers the symmetry of the distances to the positive and negative ideal solutions. Furthermore, an example from e-commerce is presented to demonstrate and validate the proposed decision-making approach. Finally, the comparative analysis is implemented to check the robustness of the results when the aggregation rules are changed.

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Pythagorean Fuzzy Multiattribute Group Decision Making with Probabilistic Information and OWA Approach

Cited by 104 publications

References 46 publications

Pythagorean fuzzy multicriteria group decision making through similarity measure based on point operators

Pythagorean fuzzy multicriteria group decision making through similarity measure based on point operators

New Operations for Interval-valued Pythagorean Fuzzy Set

Multiple Criteria Group Decision-Making Considering Symmetry with Regards to the Positive and Negative Ideal Solutions via the Pythagorean Normal Cloud Model for Application to Economic Decisions

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