Browsing by Author "Iampan, Aiyared"

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A Novel Multicriteria Decision-Making Approach for Einstein Weighted Average Operator under Pythagorean Fuzzy Hypersoft Environment
(2022) Jarad, Fahd; Jarad, Fahd; Majdoubi, Jihen; Zulqarnain, Rana Muhammad; Iampan, Aiyared; Siddique, Imran; 234808
The experts used the Pythagorean fuzzy hypersoft set (PFHSS) in their research to discourse ambiguous and vague information in decision-making processes. The aggregation operator (AO) plays a prominent part in the sensitivity of the two forefront loops and eliminates anxiety from that perception. The PFHSS is the most influential and operative extension of the Pythagorean fuzzy soft set (PFSS), which handles the subparameterized values of alternatives. It is also a generalized form of Intuitionistic fuzzy hypersoft set (IFHSS) that provides better and more accurate assessments in the decision-making (DM) process. In this work, we present some operational laws for Pythagorean fuzzy hypersoft numbers (PFHSNs) and then formulate Pythagorean fuzzy hypersoft Einstein weighted average (PFHSEWA) operator based on developed operational laws. We discuss essential features such as idempotency, boundedness, and homogeneity for the proposed PFHSEWA operator. Furthermore, a DM approach has been developed based on the built-in operator to address multicriteria decision-making (MCDM) issues. A numerical case study of decision-making problems in real-life agricultural farming is considered to validate the settled technique's dominance and applicability. The consequences display that the planned model is more operative and consistent to handle inexact data based on PFHSS.
AggregationOperators for Interval-Valued Pythagorean FuzzyHypersoft Set with Their Application to SolveMCDMProblem
(2023) Jarad, Fahd; Siddique, Imran; Ali, Rifaqat; Jarad, Fahd; Iampan, Aiyared; 234808
Experts use Pythagorean fuzzy hypersoft sets (PFHSS) in their investigations to resolve the indeterminate and imprecise information in the decision-making process. Aggregation operators (AOs) perform a leading role in perceptivity among two circulations of prospect and pull out concerns from that perception. In this paper, we extend the concept of PFHSS to interval-valued PFHSS (IVPFHSS), which is the generalized form of intervalvalued intuitionistic fuzzy soft set. The IVPFHSS competently deals with uncertain and ambagious information compared to the existing interval-valued Pythagorean fuzzy soft set. It is the most potent method for amplifying fuzzy data in the decision-making (DM) practice. Some operational laws for IVPFHSS have been proposed. Based on offered operational laws, two inventive AOs have been established: interval-valued Pythagorean fuzzy hypersoft weighted average (IVPFHSWA) and interval-valued Pythagorean fuzzy hypersoft weighted geometric (IVPFHSWG) operators with their essential properties. Multi-criteria group decision-making (MCGDM) shows an active part in contracts with the difficulties in industrial enterprise for material selection. But, the prevalent MCGDM approaches consistently carry irreconcilable consequences. Based on the anticipated AOs, a robust MCGDMtechnique is deliberate formaterial selection in industrial enterprises to accommodate this shortcoming. A real-world application of the projectedMCGDMmethod for material selection (MS) of cryogenic storing vessels is presented. The impacts show that the intended model is more effective and reliable in handling imprecise data based on IVPFHSS.
Einstein Aggregation Operators for Pythagorean Fuzzy Soft Sets with Their Application in Multiattribute Group Decision-Making
(2022) Jarad, Fahd; Siddique, Imran; Jarad, Fahd; Hamed, Y.S.; Abualnaja, Khadijah M.; Iampan, Aiyared; 234808
The Pythagorean fuzzy soft set (PFSS) is the most proficient and manipulative leeway of the Pythagorean fuzzy set (PFS), which contracts with parameterized values of the alternatives. It is a generalized form of the intuitionistic fuzzy soft set (IFSS), which provides healthier and more accurate evaluations through decision-making (DM). The main determination of this research is to prolong the idea of Einstein's aggregation operators for PFSS. We introduce the Einstein operational laws for Pythagorean fuzzy soft numbers (PFSNs). Based on Einstein operational laws, we construct two novel aggregation operators (AOs) such as Pythagorean fuzzy soft Einstein-weighted averaging (PFSEWA) and Pythagorean fuzzy soft Einstein-weighted geometric (PFSEWG) operators. In addition, important possessions of proposed operators, such as idempotency, boundedness, and homogeneity, are discussed. Furthermore, to validate the practicability of the anticipated operators, a multiple attribute group decision-making (MAGDM) method is developed. We intend innovative AOs considering the Einstein norms for PFSS to elect the most subtle business. Pythagorean fuzzy soft numbers (PFSNs) support us to signify unclear data in real-world perception. Furthermore, a numerical description is planned to certify the efficacy and usability of the projected method in the DM practice. The recent approach's pragmatism, usefulness, and tractability are validated through comparative exploration with the support of some prevalent studies.
Einstein Weighted Geometric Operator for Pythagorean Fuzzy Hypersoft with Its Application in Material Selection
(2023) Jarad, Fahd; Siddique, Imran; Ali, Rifaqat; Jarad, Fahd; Iampan, Aiyared
Hypersoft set theory is a most advanced form of soft set theory and an innovative mathematical tool for dealing with unclear complications. Pythagorean fuzzy hypersoft set (PFHSS) is the most influential and capable leeway of the hypersoft set (HSS) and Pythagorean fuzzy soft set (PFSS). It is also a general form of the intuitionistic fuzzy hypersoft set (IFHSS), which provides a better and more perfect assessment of the decision-making (DM) process. The fundamental objective of this work is to enrich the precision of decision-making. A novel mixed aggregation operator called Pythagorean fuzzy hypersoft Einstein weighted geometric (PFHSEWG) based on Einstein's operational laws has been developed. Some necessary properties, such as idempotency, boundedness, and homogeneity, have been presented for the anticipated PFHSEWG operator. Multi-criteria decision-making (MCDM) plays an active role in dealing with the complications of manufacturing design for material selection. However, conventional methods ofMCDMusually produce inconsistent results. Based on the proposed PFHSEWG operator, a robust MCDM procedure for material selection in manufacturing design is planned to address these inconveniences. The expected MCDM method for material selection (MS) of cryogenic storing vessels has been established in the real world. Significantly, the planned model for handling inaccurate data based on PFHSS is more operative and consistent.
Extension of Einstein Average Aggregation Operators to Medical Diagnostic Approach Under q-Rung Orthopair Fuzzy Soft Se
(2022) Jarad, Fahd; Rehman, Hafiz Khalil Ur; Awrejcewicz, Jan; Ali, Rifaqat; Siddique, Imran; Jarad, Fahd; Iampan, Aiyared; 234808
The paradigm of the soft set (SS) was pioneered by Moldotsov in 1999 by prefixing the parametrization tool in accustomed sets, which yields general anatomy in decision-making (DM) problems. The q-rung orthopair fuzzy soft set (q-ROFSS) is an induced form of the intuitionistic fuzzy soft set (IFSS) and Pythagorean fuzzy soft set (PFSS). It is also a more significant structure to tackle complex and vague information in DM problems than IFSS and PFSS. This manuscript explores new notions based on Einstein's operational laws for q-rung orthopair fuzzy soft numbers (q-ROFSNs). Our main contribution is to investigate some average aggregation operators (AOs), such as q-rung orthopair fuzzy soft Einstein weighted average (q-ROFSEWA) and q-rung orthopair fuzzy soft Einstein ordered weighted average (q-ROFSEOWA) operators. Besides, the fundamental axioms of proposed operators are discussed. Multi-criteria group decision-making (MCGDM) is vigorous in dealing with the compactness of real-world obstacles, and still, the prevailing MCGDM methods constantly convey conflicting consequences. Based on offered AOs, a robust MCGDM approach is deliberated to accommodate the defects of the prevalent MCGDM methodologies under the q-ROFSS setting. Based on the planned MCGDM method, a medical diagnostic procedure is implemented to recognize the nature of certain infections in different patients. The protracted model estimates illustrious score values to determine patients' health compared to prevailing models, which is more helpful for healthcare experts in identifying the severity of diseases in patients. Furthermore, an inclusive comparative analysis is accomplished to ratify the pragmatism and effectiveness of the proposed technique with some formerly standing methods. The consequences gained over comparative studies display that our established method is more proficient than predominant methodologies.
Multicriteria Decision-Making Approach for Aggregation Operators of Pythagorean Fuzzy Hypersoft Sets
(2021) Jarad, Fahd; Zulqarnain, Rana Muhammad; Ali, Rifaqat; Jarad, Fahd; Iampan, Aiyared; 234808
The Pythagorean fuzzy hypersoft set (PFHSS) is the most advanced extension of the intuitionistic fuzzy hypersoft set (IFHSS) and a suitable extension of the Pythagorean fuzzy soft set. In it, we discuss the parameterized family that contracts with the multi-subattributes of the parameters. The PFHSS is used to correctly assess insufficiencies, anxiety, and hesitancy in decision-making (DM). It is the most substantial notion for relating fuzzy data in the DM procedure, which can accommodate more uncertainty compared to available techniques considering membership and nonmembership values of each subattribute of given parameters. In this paper, we will present the operational laws for Pythagorean fuzzy hypersoft numbers (PFHSNs) and also some fundamental properties such as idempotency, boundedness, shift-invariance, and homogeneity for Pythagorean fuzzy hypersoft weighted average (PFHSWA) and Pythagorean fuzzy hypersoft weighted geometric (PFHSWG) operators. Furthermore, a novel multicriteria decision-making (MCDM) approach has been established utilizing presented aggregation operators (AOs) to resolve decision-making complications. To validate the useability and pragmatism of the settled technique, a brief comparative analysis has been conducted with some existing approaches.