Picture fuzzy aggregation operators and their application to multiple attribute decision making

Wei, Guiwu

doi:10.3233/jifs-161798

Cited by 379 publications

(257 citation statements)

References 69 publications

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“…Compared with the PFS that is used in the study of [25] and [16], PHFS proposed in this paper can convey the human opinions more effectively, including yes, abstain, no, and refusal. For instance, the evaluation information of the alternative A 1 concerning the criteria C 1 that are given by decision maker is expressed as a PFN (0.53,0.33,0.09) [16,25]. In practice, decision maker may feel doubtful to determine an exact value of each membership level.…”

Section: Mcdm Methods Rankingmentioning

confidence: 99%

“…Suppose that an organization wants to construct the enterprise resource planning (ERP) system [25]. After investigating the existing vendors of ERP systems on the market, five potential ERP systems are primary determined to be chosen from, i.e., A i (i = 1, 2, 3, 4, 5).…”

Section: Methodsmentioning

confidence: 99%

“…To prove the feasibility of the proposed MCDM methods, the rankings of Example 1 in this paper are compared with the rankings obtained by the existing MCDM methods as presented in Table 7; including the PFWA and PFWG operators [25], and the picture fuzzy cross-entropy method [16]. Similarly, a comparison of Example 2 between the GPHFPWA and GPHFPWG operators and the HFPWA and HFPWG operators [34] is presented in Table 8.…”

Section: Comparative Analysismentioning

confidence: 99%

“…We adopt two numerical examples of MCDM problems from the study of [25] and [34] and an application of web service selection [37] to show the feasibility and advantages of the proposed methods.…”

Section: Numerical Examplesmentioning

confidence: 99%

“…Next, several interval-valued intuitionistic fuzzy aggregation operators were constructed to deal with the MCDM [22][23][24]. With respect to the picture fuzzy (PF) evaluation information, Wei [25] defined the operations of picture fuzzy numbers (PFNs) according to the study of [21] and proposed the picture fuzzy weighted aggregation operators. In addition, several PF aggregation operators according to different operations were put forward [12,26].…”

Section: Introductionmentioning

confidence: 99%

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Picture Hesitant Fuzzy Set and Its Application to Multiple Criteria Decision-Making

Wang

2018

Symmetry

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Abstract:To address the complex multiple criteria decision-making (MCDM) problems in practice, this article proposes the picture hesitant fuzzy set (PHFS) theory based on the picture fuzzy set and the hesitant fuzzy set. First, the concept of PHFS is put forward, and its operations are presented, simultaneously. Second, the generalized picture hesitant fuzzy weighted aggregation operators are developed, and some theorems and reduced operators of them are discussed. Third, the generalized picture hesitant fuzzy prioritized weighted aggregation operators are put forward to solve the MCDM problems that the related criteria are at different priorities. Fourth, two novel MCDM methods combined with the proposed operators are constructed to determine the best alternative in real life. Finally, two numerical examples and an application of web service selection are investigated to illustrate the effectiveness of the proposed methods. The sensitivity analysis shows that the different values of the parameter λ affect the ranking of alternatives, and the proposed operators are compared with several existing MCDM methods to illustrate their advantages.Keywords: multiple criteria decision-making; picture hesitant fuzzy set; generalized picture hesitant fuzzy weighted aggregation operator; generalized picture hesitant fuzzy prioritized weighted aggregation operator

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Section: Mcdm Methods Rankingmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Comparative Analysismentioning

confidence: 99%

Section: Numerical Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Picture Hesitant Fuzzy Set and Its Application to Multiple Criteria Decision-Making

Wang

2018

Symmetry

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Pythagorean fuzzy power aggregation operators in multiple attribute decision making

Wei

2017

Int. J. Intell. Syst.

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329

181

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In this paper, we utilize power aggregation operators to develop some Pythagorean fuzzy power aggregation operators: Pythagorean fuzzy power average operator, Pythagorean fuzzy power geometric operator, Pythagorean fuzzy power weighted average operator, Pythagorean fuzzy power weighted geometric operator, Pythagorean fuzzy power ordered weighted average operator, Pythagorean fuzzy power ordered weighted geometric operator, Pythagorean fuzzy power hybrid average operator, and Pythagorean fuzzy power hybrid geometric operator. The prominent characteristic of these proposed operators are studied. Then, we have utilized these operators to develop some approaches to solve the Pythagorean fuzzy multiple attribute decision-making problems. Finally, a practical example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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Similarity measures of Pythagorean fuzzy sets based on the cosine function and their applications

Wei

2018

Int. J. Intell. Syst.

Self Cite

268

184

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In this paper, we presented 10 similarity measures between Pythagorean fuzzy sets (PFSs) based on the cosine function by considering the degree of membership, degree of nonmembership and degree of hesitation in PFSs. Then, we applied these similarity measures and weighted similarity measures between PFSs to pattern recognition and medical diagnosis. Finally, two illustrative examples are given to demonstrate the efficiency of the similarity measures for pattern recognition and medical diagnosis.

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Picture fuzzy aggregation operators and their application to multiple attribute decision making

Cited by 379 publications

References 69 publications

Picture Hesitant Fuzzy Set and Its Application to Multiple Criteria Decision-Making

Picture Hesitant Fuzzy Set and Its Application to Multiple Criteria Decision-Making

Pythagorean fuzzy power aggregation operators in multiple attribute decision making

Similarity measures of Pythagorean fuzzy sets based on the cosine function and their applications

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