TOPSIS Method Based on Correlation Coefficient under Pythagorean Fuzzy Soft Environment and Its Application towards Green Supply Chain Management

Rana Muhammad Zulqarnain, Xiao Long Xin, Imran Siddique, Waseem Asghar Khan and Mogtaba Ahmed Yousif
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Rana Muhammad Zulqarnain: School of Mathematics, Northwest University, Xi’an 710127, China
Xiao Long Xin: School of Mathematics, Northwest University, Xi’an 710127, China
Imran Siddique: Department of Mathematics, University of Management and Technology, Lahore 54770, Pakistan
Waseem Asghar Khan: Department of Mathematics, Faculty of Sciences AlZulfi, Majmaah University, Majmaah 11952, Saudi Arabia
Mogtaba Ahmed Yousif: Department of Mathematics, Faculty of Sciences AlZulfi, Majmaah University, Majmaah 11952, Saudi Arabia

Sustainability, 2021, vol. 13, issue 4, 1-24

Abstract: The correlation coefficient between two variables is an important aspect of statistics. The accuracy of assessments of correlation relies on information from a set of discourses. Data collected in statistical studies are often full of exceptions. Pythagorean fuzzy soft sets (PFSS) are a parametrized family of extended Pythagorean fuzzy sets (PFS). They comprise a generalization of intuitionistic fuzzy soft sets which may be used to accurately assess deficiencies and uncertainties in evaluations. PFSS can accommodate uncertainty more competently than intuitionistic fuzzy soft sets and are the most important strategy when dealing with fuzzy information in decision-making processes. Herein, the concept and characteristics of correlation coefficients and the weighted correlation coefficients in PFSS are discussed. We also introduce the Pythagorean fuzzy soft weighted average (PFSWA) and Pythagorean fuzzy soft weighted geometric (PFSWG) operators and discuss their desirable characteristics. A prioritization technique for order preference by similarity to the ideal solution (TOPSIS) under the PFSS environment based on correlation coefficients and weighted correlation coefficients will be introduced. Through the proposed methodology, a technique for decision-making is developed. Additionally, an application of the proposed TOPSIS technique is presented for green supplier selection in green supply chain management (GSCM). The practicality, efficacy, and flexibility of the proposed approach is proved through comparative analyses, drawing upon existing studies.

Keywords: pythagorean fuzzy sets; pythagorean fuzzy soft sets; green supply chain management; TOPSIS (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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