Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making Methods
The emergence and popularity of social media have made large-scale group decision-making (LSGDM) problems increasingly common, resulting in significant research interest in this field. LSGDM involves numerous evaluators, which can lead to disagreements and hesitancy among them. Hesitant fuzzy sets (...
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MDPI AG
2025-04-01
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| author | Wei Liang Álvaro Labella Meng-Jun Meng Ying-Ming Wang Rosa M. Rodríguez |
| author_facet | Wei Liang Álvaro Labella Meng-Jun Meng Ying-Ming Wang Rosa M. Rodríguez |
| author_sort | Wei Liang |
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| description | The emergence and popularity of social media have made large-scale group decision-making (LSGDM) problems increasingly common, resulting in significant research interest in this field. LSGDM involves numerous evaluators, which can lead to disagreements and hesitancy among them. Hesitant fuzzy sets (HFSs) become crucial in this context as they capture the uncertainty and hesitancy among evaluators. On the other hand, research on the Consensus Reaching Process (CRP) becomes particularly important in dealing with the inevitable differences among the great number of evaluators. Ways to mitigate these differences to reach an agreement are a crucial area of study. For this reason, this paper presents a new CRP model to deal with LSGDM problems in hesitant fuzzy environments. First, HFSs and Normal-type Hesitant Fuzzy Sets (N-HFSs) are introduced to integrate evaluators’ subgroup and collective opinions, aiming to preserve as much decision information as possible while reducing computational complexity. Subsequently, a CRP with a detailed feedback suggestion generation mechanism is developed, which considers the willingness of evaluators to modify their opinions, thereby improving the effectiveness of reaching an agreement. Finally, a LSGDM framework that does not require any normalization process is proposed, and its feasibility and robustness are demonstrated through a numerical example. |
| format | Article |
| id | doaj-art-7bdfaea3e96e4545a9fef2106f33bef5 |
| institution | OA Journals |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-04-01 |
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| series | Mathematics |
| spelling | doaj-art-7bdfaea3e96e4545a9fef2106f33bef52025-08-20T02:17:00ZengMDPI AGMathematics2227-73902025-04-01137118210.3390/math13071182Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making MethodsWei Liang0Álvaro Labella1Meng-Jun Meng2Ying-Ming Wang3Rosa M. Rodríguez4School of Economics and Management, Minjiang University, Fuzhou 350108, ChinaDepartment of Computer Science, University of Jaén, 23071 Jaén, SpainSchool of Vocational Education, Shandong Youth University of Political Science, Jinan 250103, ChinaDecision Science Institute, School of Economics & Management, Fuzhou University, Fuzhou 350108, ChinaDepartment of Computer Science, University of Jaén, 23071 Jaén, SpainThe emergence and popularity of social media have made large-scale group decision-making (LSGDM) problems increasingly common, resulting in significant research interest in this field. LSGDM involves numerous evaluators, which can lead to disagreements and hesitancy among them. Hesitant fuzzy sets (HFSs) become crucial in this context as they capture the uncertainty and hesitancy among evaluators. On the other hand, research on the Consensus Reaching Process (CRP) becomes particularly important in dealing with the inevitable differences among the great number of evaluators. Ways to mitigate these differences to reach an agreement are a crucial area of study. For this reason, this paper presents a new CRP model to deal with LSGDM problems in hesitant fuzzy environments. First, HFSs and Normal-type Hesitant Fuzzy Sets (N-HFSs) are introduced to integrate evaluators’ subgroup and collective opinions, aiming to preserve as much decision information as possible while reducing computational complexity. Subsequently, a CRP with a detailed feedback suggestion generation mechanism is developed, which considers the willingness of evaluators to modify their opinions, thereby improving the effectiveness of reaching an agreement. Finally, a LSGDM framework that does not require any normalization process is proposed, and its feasibility and robustness are demonstrated through a numerical example.https://www.mdpi.com/2227-7390/13/7/1182hesitant fuzzy setconsensus reaching processlarge-scale group decision makingmultiple criteria decision making |
| spellingShingle | Wei Liang Álvaro Labella Meng-Jun Meng Ying-Ming Wang Rosa M. Rodríguez Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making Methods Mathematics hesitant fuzzy set consensus reaching process large-scale group decision making multiple criteria decision making |
| title | Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making Methods |
| title_full | Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making Methods |
| title_fullStr | Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making Methods |
| title_full_unstemmed | Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making Methods |
| title_short | Hesitant Fuzzy Consensus Reaching Process for Large-Scale Group Decision-Making Methods |
| title_sort | hesitant fuzzy consensus reaching process for large scale group decision making methods |
| topic | hesitant fuzzy set consensus reaching process large-scale group decision making multiple criteria decision making |
| url | https://www.mdpi.com/2227-7390/13/7/1182 |
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