Title: Multi-attribute decision-making application based on Pythagorean fuzzy soft expert set

Authors: Muhammad Ihsan; Muhammad Saeed; Atiqe Ur Rahman

Addresses: Department of Mathematics, University of Management and Technology, Lahore, 54000, Pakistan ' Department of Mathematics, University of Management and Technology, Lahore, 54000, Pakistan ' Department of Mathematics, University of Management and Technology, Lahore, 54000, Pakistan

Abstract: The Pythagorean fuzzy soft expert set (ƤƑЅƐ-set) is a parameterised family and one of the appropriate extensions of the Pythagorean fuzzy sets. It is also a generalisation of intuitionistic fuzzy soft expert set, used to accurately assess deficiencies, uncertainties, and anxiety in evaluation. Its main advantage over the existing models is that the Pythagorean fuzzy soft expert set is considered a parametric tool. The ƤƑЅƐ-set can accommodate more uncertainty comparative to the intuitionistic fuzzy soft expert set, this is the most important strategy to explain fuzzy information in the decision-making process. The main objective of the present research is to establish the new structure of ƤƑЅƐ-set along with its corresponding fundamental properties in a Pythagorean fuzzy soft expert environment. In this article, we introduce Pythagorean fuzzy soft expert set and discuss its desirable characteristics (i.e., subset, not set and equal set), results (i.e., commutative, associative, distributive and De Morgan's laws) and set-theoretic operations (i.e., complement, union intersection AND and OR) are explained. An algorithm is proposed to solve decision-making problem. A comparative analysis with the advantages, effectiveness, flexibility, and numerous existing studies demonstrates the effectiveness of this model.

Keywords: soft expert set; Pythagorean fuzzy soft set; Pythagorean fuzzy soft expert set; PFSE-set.

DOI: 10.1504/IJIDS.2024.142637

International Journal of Information and Decision Sciences, 2024 Vol.16 No.4, pp.383 - 408

Received: 12 Dec 2021
Accepted: 25 Mar 2022
Published online: 14 Nov 2024 *

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