Decision Support Technique Based on Spherical Fuzzy Yager Aggregation Operators and Their Application in Wind Power Plant Locations: A Case Study of Jhimpir, Pakistan

The problem of energy crisis and environmental pollution has been mitigated by the generation and use of wind power; however, the choice of locations for wind power plants is a difficult task because the decision-making process includes political, socioeconomic, and environmental aspects. Thus, seve...

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Main Authors: Ronnason Chinram, Shahzaib Ashraf, Saleem Abdullah, Pattarawan Petchkaew
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2020/8824032
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author Ronnason Chinram
Shahzaib Ashraf
Saleem Abdullah
Pattarawan Petchkaew
author_facet Ronnason Chinram
Shahzaib Ashraf
Saleem Abdullah
Pattarawan Petchkaew
author_sort Ronnason Chinram
collection DOAJ
description The problem of energy crisis and environmental pollution has been mitigated by the generation and use of wind power; however, the choice of locations for wind power plants is a difficult task because the decision-making process includes political, socioeconomic, and environmental aspects. Thus, several adverse consequences have been created by the choice of suboptimal locations. The objective of this paper is to address the integrated qualitative and quantitative multicriteria decision-making framework for the selection of wind power plant locations. Spherical fuzzy sets are the latest extension of the ordinary fuzzy sets. The main characteristic of the spherical fuzzy sets is satisfying the condition that the squared sum of the positive, neutral, and negative grades must be at least zero and at most one. In this research, we establish novel operational laws based on the Yager t-norm and t-conorm under spherical fuzzy environments (SFE). Furthermore, based on these Yager operational laws, we develop list of novel aggregation operators under SFE. In addition, we design an algorithm to tackle the uncertainty to investigating the best wind power plant selection in four potential locations in Pakistan. A numerical example of wind power plant location problem is considered to show the supremacy and effectiveness of the proposed study. Also, a detailed comparison is constructed to evaluate the performance and validity of the established technique.
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publishDate 2020-01-01
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spelling doaj-art-5e706de069cf4a47a46e1e6fba1a96b02025-08-20T02:05:08ZengWileyJournal of Mathematics2314-46292314-47852020-01-01202010.1155/2020/88240328824032Decision Support Technique Based on Spherical Fuzzy Yager Aggregation Operators and Their Application in Wind Power Plant Locations: A Case Study of Jhimpir, PakistanRonnason Chinram0Shahzaib Ashraf1Saleem Abdullah2Pattarawan Petchkaew3Algebra and Applications Research Unit, Division of Computational Science, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla 90110, ThailandDepartment of Mathematics and Statistics, Bacha Khan University, Charsadda, Khyber Pakhtunkhwa, PakistanDepartment of Mathematics, Abdul Wali Khan University, Mardan, Khyber Pakhtunkhwa, PakistanMathematics Program, Faculty of Science and Technology, Songkhla Rajabhat University, Songkhla, 90000, ThailandThe problem of energy crisis and environmental pollution has been mitigated by the generation and use of wind power; however, the choice of locations for wind power plants is a difficult task because the decision-making process includes political, socioeconomic, and environmental aspects. Thus, several adverse consequences have been created by the choice of suboptimal locations. The objective of this paper is to address the integrated qualitative and quantitative multicriteria decision-making framework for the selection of wind power plant locations. Spherical fuzzy sets are the latest extension of the ordinary fuzzy sets. The main characteristic of the spherical fuzzy sets is satisfying the condition that the squared sum of the positive, neutral, and negative grades must be at least zero and at most one. In this research, we establish novel operational laws based on the Yager t-norm and t-conorm under spherical fuzzy environments (SFE). Furthermore, based on these Yager operational laws, we develop list of novel aggregation operators under SFE. In addition, we design an algorithm to tackle the uncertainty to investigating the best wind power plant selection in four potential locations in Pakistan. A numerical example of wind power plant location problem is considered to show the supremacy and effectiveness of the proposed study. Also, a detailed comparison is constructed to evaluate the performance and validity of the established technique.http://dx.doi.org/10.1155/2020/8824032
spellingShingle Ronnason Chinram
Shahzaib Ashraf
Saleem Abdullah
Pattarawan Petchkaew
Decision Support Technique Based on Spherical Fuzzy Yager Aggregation Operators and Their Application in Wind Power Plant Locations: A Case Study of Jhimpir, Pakistan
Journal of Mathematics
title Decision Support Technique Based on Spherical Fuzzy Yager Aggregation Operators and Their Application in Wind Power Plant Locations: A Case Study of Jhimpir, Pakistan
title_full Decision Support Technique Based on Spherical Fuzzy Yager Aggregation Operators and Their Application in Wind Power Plant Locations: A Case Study of Jhimpir, Pakistan
title_fullStr Decision Support Technique Based on Spherical Fuzzy Yager Aggregation Operators and Their Application in Wind Power Plant Locations: A Case Study of Jhimpir, Pakistan
title_full_unstemmed Decision Support Technique Based on Spherical Fuzzy Yager Aggregation Operators and Their Application in Wind Power Plant Locations: A Case Study of Jhimpir, Pakistan
title_short Decision Support Technique Based on Spherical Fuzzy Yager Aggregation Operators and Their Application in Wind Power Plant Locations: A Case Study of Jhimpir, Pakistan
title_sort decision support technique based on spherical fuzzy yager aggregation operators and their application in wind power plant locations a case study of jhimpir pakistan
url http://dx.doi.org/10.1155/2020/8824032
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