An Approach to Selection of Agricultural Product Supplier Using Pythagorean Fuzzy Sets

Dai, Lina; Bai, Shizhen

doi:10.1155/2020/1816028

Cited by 7 publications

(6 citation statements)

References 25 publications

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“…Olfat et al (2019) proposed a performance measurement approach based on the extended type-2 fuzzy network to determine the efficiency of distribution centers in fast moving consuming goods industry. Dai and Bai (2020) proposed an agricultural product supplier selection algorithm on the basis of the Pythagorean fuzzy power Bonferroni mean operator to deal with a supplier selection problem. Shamout (2020) applied the fuzzy setsbased qualitative comparative analysis technique to establish causal relations for achieving high scores of SC agility.…”

Section: Other Fuzzy Methodsmentioning

confidence: 99%

An Overview of Fuzzy Techniques in Supply Chain Management: Bibliometrics, Methodologies, Applications and Future Directions

Liao

Zavadskas

2021

Technological and Economic Development of Economy

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Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM.

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Section: Other Fuzzy Methodsmentioning

confidence: 99%

An Overview of Fuzzy Techniques in Supply Chain Management: Bibliometrics, Methodologies, Applications and Future Directions

Liao

Zavadskas

2021

Technological and Economic Development of Economy

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“…The rapid development in PF theory that was built primarily on Pythagorean membership grades has led to considerable increases in manifestations of PF characteristics for expressing uncertainties and triggered a vigorous growth in a diverse range of MCDA models and techniques in PF contexts. For example, Dai et al 13 launched an MCDA method by using PF power Bonferroni mean operators for agricultural product supplier selection. Feng et al 14 presented novel group generalized PF aggregation operators to treat MCDA issues.…”

Section: Preliminariesmentioning

confidence: 99%

“…Moreover, the theory of PF sets represents a convenient but robust tool to delineate unclearness and unsureness contained in human judgments and evaluations more comprehensively and explicitly, 9–12 which empowers PF theory to possess a more extensive applicability in the field of multiple criteria decision analysis (MCDA). Currently, the multiple criteria evaluation methods and decision models within PF environments are frequently maneuvered by the agency of the PF aggregation operators (e.g., Dai et al, 13 Feng et al, 14 Liang et al, 15 Rahman, 16 Xian et al, 17 and Zhang et al 18 ), the PF distance measures (e.g., Chen, 2,19 Ejegwa, 20 Xu et al, 21 and Zhou and Chen 22 ), or other valuable concepts (e.g., Akram et al 23 and Zhang et al 6 ).…”

Section: Introductionmentioning

confidence: 99%

Pythagorean fuzzy likelihood function based on beta distributions and its based dominance ordering model in an uncertain multiple criteria decision support framework

Tsao

Chen

2021

Int J Intell Syst

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The concept of Pythagorean fuzzy (PF) sets represents a superior tool to model complex uncertainties in an ambiguous and equivocal decision‐making framework. In consideration of the significant capacity for exhibiting the uncertainty of subjective appraisals and estimations under the aegis of the PF theory, this paper presents a simple‐to‐operate decision‐making approach that is grounded in some beneficial concepts of original likelihood functions and measurements of dominating and dominated characters. On the strength of beta distributions, this paper seeks to propound new notions of PF likelihood functions and likelihood‐oriented dominating/dominated characters and to launch an exploitable multiple criteria evaluation method by means of a dominance ordering model for treating decision analysis within PF environments. This paper initiates an efficient beta distribution‐based approach to the construction of novel PF likelihood functions that can quantify the possibility degrees of outranking and outranked relationships between Pythagorean membership grades. The applicable satisfaction and dissatisfaction estimations are established on the likelihood‐oriented dominating and dominated characters, respectively. Furthermore, this paper formulates a straightforward dominance ordering model to obtain the ultimate dominance ranking orders of candidate alternatives and accomplish multiple criteria decision‐making issues involving complicated uncertainty. A financing decision‐making problem concerning working capital requirements is investigated to validate the application results using the advanced methodology. The real‐world application is implemented to examine the reasonableness and efficacy of the established techniques. Moreover, comparative studies through the utility of a sensitivity analysis are performed to demonstrate the efficacy and merits of the dominance ordering model. The comparison results manifest that the initiated methodology is an advantageous and reliable decision‐making technique that can enhance the methodological development regarding the multiple criteria evaluation model under PF uncertainty. Finally, recommendations for future research directions are also presented in the conclusions.

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“…The definition of Pythagorean fuzzy set (PFS) was proposed by Yager [13,14]. In the year 2015, they [15] developed a Pythagorean fuzzy superiority and inferiority ranking method to solve uncertainty multiple attribute group decision making problem. Recently in 2020, they [16] proposed an agricultural product supplier selection algorithm based on the Pythagorean fuzzy power Bonferroni mean operator under Pythagorean fuzzy environment.…”

Section: Introductionmentioning

confidence: 99%

Fermatean Fuzzy Weighted Geometric Aggregation Operator inMultiple Attribute Group Decision Making Problems

Khan,

Ahmad

2022

MATEMATIKA

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Fermatean fuzzy set, an extension of Intuitionistic fuzzy set and Pythagoreanfuzzy set, plays a remarkable role in dealing with ambiguityowing to its vast spacecompared to Intuitionistic fuzzy set and Pythagorean fuzzyset. Aggregation operatorshave been helpful in multi-attribute group decision making(MAGDM) problems, becauseof their importance and efficacy in coping with uncertainty. The purpose of this paper isto prove important theorems in the domain of the Fermatean fuzzy weighted geometricoperator (FFWG) and discuss its essential properties. Mostimportantly, how to utilizethe Fermatean fuzzy weighted geometric operator in the MAGDM problem. An algorithmof the proposed method has been established. The proposed operator is applied to decisionmaking problems to show the validity, practicality and effectiveness of the new approach.The main advantage of using the FFWG method is that this method gives more accurateresults as compared to the existing methods.

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An Approach to Selection of Agricultural Product Supplier Using Pythagorean Fuzzy Sets

Cited by 7 publications

References 25 publications

An Overview of Fuzzy Techniques in Supply Chain Management: Bibliometrics, Methodologies, Applications and Future Directions

An Overview of Fuzzy Techniques in Supply Chain Management: Bibliometrics, Methodologies, Applications and Future Directions

Pythagorean fuzzy likelihood function based on beta distributions and its based dominance ordering model in an uncertain multiple criteria decision support framework

Fermatean Fuzzy Weighted Geometric Aggregation Operator inMultiple Attribute Group Decision Making Problems

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