Pythagorean Fuzzy Hamy Mean Operators in Multiple Attribute Group Decision Making and Their Application to Supplier Selection

Li, Zengxian; Wei, Guiwu; Lu, Mingyue

doi:10.3390/sym10100505

Cited by 107 publications

(49 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Zhang and Xu provided the detailed mathematical expression for PFS and introduced the concept of Pythagorean fuzzy number (PFN) and developed a Pythagorean fuzzy “technique for an order of preference by similarity to Ideal solution” for MADM problem within PFNs. Li et al developed some Pythagorean fuzzy Hamy mean operators in MAGDM for supplier selection. Gao proposed the Pythagorean Fuzzy Hamacher Prioritized aggregation operators in MADM on the basis of Prioritized aggregation operators .…”

Section: Introductionmentioning

confidence: 99%

The generalized Dice similarity measures for Pythagorean fuzzy multiple attribute group decision making

2019

Self Cite

View full text Add to dashboard Cite

The Pythagorean fuzzy set (PFS) is characterized by two functions expressing the degree of membership and the degree of nonmembership, which square sum of them is equal or less than 1. It was proposed as a generalization of a fuzzy set to deal with indeterminate and inconsistent information. In this study, we shall present some novel Dice similarity measures of PFSs and the generalized Dice similarity measures of PFSs and indicates that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures‐based multiple attribute group decision‐making models with Pythagorean fuzzy information. Then, we apply the generalized Dice similarity measures between PFSs to multiple attribute group decision making. Finally, an illustrative example is given to demonstrate the efficiency of the similarity measures for selecting the desirable ERP system.

show abstract

Section: Introductionmentioning

confidence: 99%

The generalized Dice similarity measures for Pythagorean fuzzy multiple attribute group decision making

2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…Finally, a practical example for the selection of a car car supplier was given. In the future, the application of the IFNs needs to be explored in decision-making processes [63][64][65][66][67][68][69][70][71][72], risk analysis [73,74], and other fuzzy environments [75][76][77][78][79][80].…”

Section: Discussionmentioning

confidence: 99%

Methods for Multiple Attribute Group Decision Making Based on Intuitionistic Fuzzy Dombi Hamy Mean Operators

2018

Self Cite

View full text Add to dashboard Cite

In this paper, we extended the Hamy mean (HM) operator, the Dombi Hamy mean (DHM) operator, the Dombi dual Hamy mean (DDHM), with the intuitionistic fuzzy numbers (IFNs) to propose the intuitionistic fuzzy Dombi Hamy mean (IFDHM) operator, intuitionistic fuzzy weighted Dombi Hamy mean (IFWDHM) operator, intuitionistic fuzzy Dombi dual Hamy mean (IFDDHM) operator, and intuitionistic fuzzy weighted Dombi dual Hamy mean (IFWDDHM) operator. Following this, the multiple attribute group decision-making (MAGDM) methods are proposed with these operators. To conclude, we utilized an applicable example for the selection of a car supplier to prove the proposed methods.

show abstract

“…Plenty of practical decision-making problems usually demand multiple DMs rather than a single DM. PFSs have the successful capacity to handle the indeterminacy under the MAGDM environment [8,17,[25][26][27][28][29]31].…”

Section: Magdm Methods By Using Gpfihwa and Gpfihwg Operatorsmentioning

confidence: 99%

Some Novel Interactive Hybrid Weighted Aggregation Operators with Pythagorean Fuzzy Numbers and Their Applications to Decision Making

Garg

Wang

2019

Mathematics

View full text Add to dashboard Cite

A Pythagorean fuzzy set (PFS) is one of the extensions of the intuitionistic fuzzy set which accommodate more uncertainties to depict the fuzzy information and hence its applications are more extensive. In the modern decision-making process, aggregation operators are regarded as a useful tool for assessing the given alternatives and whose target is to integrate all the given individual evaluation values into a collective one. Motivated by these primary characteristics, the aim of the present work is to explore a group of interactive hybrid weighted aggregation operators for assembling Pythagorean fuzzy sets to deal with the decision information. The proposed aggregation operators include interactive the hybrid weighted average, interactive hybrid weighted geometric and its generalized versions. The major advantages of the proposed operators to address the decision-making problems are (i) to consider the interaction among membership and non-membership grades of the Pythagorean fuzzy numbers, (ii) it has the property of idempotency and simple computation process, and (iii) it possess an adjust parameter value and can reflect the preference of decision-makers during the decision process. Furthermore, we introduce an innovative multiple attribute decision making (MADM) process under the PFS environment based on suggested operators and illustrate with numerous numerical cases to verify it. The comparative analysis as well as advantages of the proposed framework confirms the supremacies of the method.Mathematics 2019, 7, 1150 2 of 25 that 0.4 + 0.8 > 1, so IFS cannot solve this issue, but since 0.4 2 + 0.8 2 < 1, then the PFS can easily deal with it. Therefore, in some cases, the PFS can settle a large number of problems, while the IFS cannot. Since PFS appeared, it has become a useful technique for modeling vagueness and indeterminacy of the MADM issues or multiple attribute group decision making (MAGDM) issues [5][6][7][8][9][10][11][12]. Some evaluation methods in the light of PFS are given to solve Pythagorean fuzzy MADM problems. For instance, Rani et al. [13] extended traditional TOPSIS (technique for an order of preference by similarity to ideal solution) approach to Pythagorean fuzzy numbers (PFNs) and studied the selection of a sustainable recycling partner. Considering DM's psychological characteristics, in the light of the prospect and regret theories, Peng and Dai [14] explored a stochastic decision approach under Pythagorean fuzzy setting. Ren et al. [15] extended traditional TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) approach to PFNs. Chen [16] introduced a Pythagorean fuzzy VIKOR (vlseKriterijumska optimizacija I Kompromisno Resenje in Serbian) approach for MADM. Zhang [17] expanded the hierarchical QUALIFLEX (qualitative flexible multiple criteria method) algorithm to the interval-valued PFSs, and employed it to investigate the industries' risk evaluation.The way of evaluation methods in Pythagorean fuzzy decision-making problems is only one aspect, the other ...

show abstract

Pythagorean Fuzzy Hamy Mean Operators in Multiple Attribute Group Decision Making and Their Application to Supplier Selection

Cited by 107 publications

References 62 publications

The generalized Dice similarity measures for Pythagorean fuzzy multiple attribute group decision making

The generalized Dice similarity measures for Pythagorean fuzzy multiple attribute group decision making

Methods for Multiple Attribute Group Decision Making Based on Intuitionistic Fuzzy Dombi Hamy Mean Operators

Some Novel Interactive Hybrid Weighted Aggregation Operators with Pythagorean Fuzzy Numbers and Their Applications to Decision Making

Contact Info

Product

Resources

About