Decision-Making Framework for an Effective Sanitizer to Reduce COVID-19 under Fermatean Fuzzy Environment

The purpose of this article is to develop some general aggregation operators (AOs) based on Einstein’s norm operations, to cumulate the Fermatean fuzzy data in decision-making environments. A Fermatean fuzzy set (FFS), possessing the more flexible structure than the intuitionistic fuzzy set (IFS) an...

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Main Authors: Muhammad Akram, Gulfam Shahzadi, Abdullah Ali H. Ahmadini
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2020/3263407
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author Muhammad Akram
Gulfam Shahzadi
Abdullah Ali H. Ahmadini
author_facet Muhammad Akram
Gulfam Shahzadi
Abdullah Ali H. Ahmadini
author_sort Muhammad Akram
collection DOAJ
description The purpose of this article is to develop some general aggregation operators (AOs) based on Einstein’s norm operations, to cumulate the Fermatean fuzzy data in decision-making environments. A Fermatean fuzzy set (FFS), possessing the more flexible structure than the intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS), is a competent tool to handle vague information in the decision-making process by the means of membership degree (MD) and nonmembership degree (NMD). Our target is to empower the AOs using the theoretical basis of Einstein norms for the FFS to establish some advantageous operators, namely, Fermatean fuzzy Einstein weighted averaging (FFEWA), Fermatean fuzzy Einstein ordered weighted averaging (FFEOWA), generalized Fermatean fuzzy Einstein weighted averaging (GFFEWA), and generalized Fermatean fuzzy Einstein ordered weighted averaging (GFFEOWA) operators. Some properties and important results of the proposed operators are highlighted. As an addition to the MADM strategies, an approach, based on the proposed operators, is presented to deal with Fermatean fuzzy data in MADM problems. Moreover, multiattribute decision-making (MADM) problem for the selection of an effective sanitizer to reduce coronavirus is presented to show the capability and proficiency of this new idea. The results are compared with the Fermatean fuzzy TOPSIS method to exhibit the potency of the proposed model.
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spelling doaj-art-927c59306efd4dfdab9e7e56977e0cb52025-08-20T03:20:37ZengWileyJournal of Mathematics2314-46292314-47852020-01-01202010.1155/2020/32634073263407Decision-Making Framework for an Effective Sanitizer to Reduce COVID-19 under Fermatean Fuzzy EnvironmentMuhammad Akram0Gulfam Shahzadi1Abdullah Ali H. Ahmadini2Department of Mathematics, University of the Punjab, New Campus, Lahore, PakistanDepartment of Mathematics, University of the Punjab, New Campus, Lahore, PakistanDepartment of Mathematics, Faculty of Science, Jazan University, Jazan, Saudi ArabiaThe purpose of this article is to develop some general aggregation operators (AOs) based on Einstein’s norm operations, to cumulate the Fermatean fuzzy data in decision-making environments. A Fermatean fuzzy set (FFS), possessing the more flexible structure than the intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS), is a competent tool to handle vague information in the decision-making process by the means of membership degree (MD) and nonmembership degree (NMD). Our target is to empower the AOs using the theoretical basis of Einstein norms for the FFS to establish some advantageous operators, namely, Fermatean fuzzy Einstein weighted averaging (FFEWA), Fermatean fuzzy Einstein ordered weighted averaging (FFEOWA), generalized Fermatean fuzzy Einstein weighted averaging (GFFEWA), and generalized Fermatean fuzzy Einstein ordered weighted averaging (GFFEOWA) operators. Some properties and important results of the proposed operators are highlighted. As an addition to the MADM strategies, an approach, based on the proposed operators, is presented to deal with Fermatean fuzzy data in MADM problems. Moreover, multiattribute decision-making (MADM) problem for the selection of an effective sanitizer to reduce coronavirus is presented to show the capability and proficiency of this new idea. The results are compared with the Fermatean fuzzy TOPSIS method to exhibit the potency of the proposed model.http://dx.doi.org/10.1155/2020/3263407
spellingShingle Muhammad Akram
Gulfam Shahzadi
Abdullah Ali H. Ahmadini
Decision-Making Framework for an Effective Sanitizer to Reduce COVID-19 under Fermatean Fuzzy Environment
Journal of Mathematics
title Decision-Making Framework for an Effective Sanitizer to Reduce COVID-19 under Fermatean Fuzzy Environment
title_full Decision-Making Framework for an Effective Sanitizer to Reduce COVID-19 under Fermatean Fuzzy Environment
title_fullStr Decision-Making Framework for an Effective Sanitizer to Reduce COVID-19 under Fermatean Fuzzy Environment
title_full_unstemmed Decision-Making Framework for an Effective Sanitizer to Reduce COVID-19 under Fermatean Fuzzy Environment
title_short Decision-Making Framework for an Effective Sanitizer to Reduce COVID-19 under Fermatean Fuzzy Environment
title_sort decision making framework for an effective sanitizer to reduce covid 19 under fermatean fuzzy environment
url http://dx.doi.org/10.1155/2020/3263407
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AT abdullahalihahmadini decisionmakingframeworkforaneffectivesanitizertoreducecovid19underfermateanfuzzyenvironment