Circular Intuitionistic Fuzzy Median Ranking Model with a Novel Scoring Mechanism for Multiple Criteria Decision Analytics
This study aims to pioneer an innovative circular intuitionistic fuzzy (C-IF) scoring-mediated median ranking model designed for multiple criteria decision analytics. The primary goal is to establish a comprehensive precedence ranking for competing alternatives, effectively addressing the inherent u...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | https://www.tandfonline.com/doi/10.1080/08839514.2024.2335416 |
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| _version_ | 1850064180908916736 |
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| author | Ting-Yu Chen |
| author_facet | Ting-Yu Chen |
| author_sort | Ting-Yu Chen |
| collection | DOAJ |
| description | This study aims to pioneer an innovative circular intuitionistic fuzzy (C-IF) scoring-mediated median ranking model designed for multiple criteria decision analytics. The primary goal is to establish a comprehensive precedence ranking for competing alternatives, effectively addressing the inherent uncertainties present in decision-analytic challenges within the C-IF environment. The core content delves into the creation of an original scoring mechanism tailored to navigate the complexities of C-IF uncertainties. Moreover, the research introduces a specialized C-IF median ranking model for decision analytics, leveraging the foundational concept of the C-IF scoring mechanism. A significant contribution is made through the formulation of a robust implementation procedure, specifically tailored for the seamless operation of the C-IF scoring-mediated median ranking model within the framework of C-IF information. Drawing from the suggested C-IF scoring mechanism, this research introduces novel concepts related to comprehensive C-IF scoring functions and comprehensive disagreement metrics. Subsequently, a comprehensive disagreement matrix is formulated, with its entries quantifying the extent of disagreement in assigning specific ranks to each alternative across all criterion-wise precedence relationships. This paves the way for the development of a new C-IF scoring-mediated median ranking model, offering decision analysts a tool to navigate intricate C-IF information and derive dependable decision-analytic outcomes. |
| format | Article |
| id | doaj-art-788679fb34724bda8344fc2dee616ecc |
| institution | DOAJ |
| issn | 0883-9514 1087-6545 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Applied Artificial Intelligence |
| spelling | doaj-art-788679fb34724bda8344fc2dee616ecc2025-08-20T02:49:22ZengTaylor & Francis GroupApplied Artificial Intelligence0883-95141087-65452024-12-0138110.1080/08839514.2024.2335416Circular Intuitionistic Fuzzy Median Ranking Model with a Novel Scoring Mechanism for Multiple Criteria Decision AnalyticsTing-Yu Chen0Department of Industrial and Business Management, Graduate Institute of Management, Chang Gung University, Taoyuan, TaiwanThis study aims to pioneer an innovative circular intuitionistic fuzzy (C-IF) scoring-mediated median ranking model designed for multiple criteria decision analytics. The primary goal is to establish a comprehensive precedence ranking for competing alternatives, effectively addressing the inherent uncertainties present in decision-analytic challenges within the C-IF environment. The core content delves into the creation of an original scoring mechanism tailored to navigate the complexities of C-IF uncertainties. Moreover, the research introduces a specialized C-IF median ranking model for decision analytics, leveraging the foundational concept of the C-IF scoring mechanism. A significant contribution is made through the formulation of a robust implementation procedure, specifically tailored for the seamless operation of the C-IF scoring-mediated median ranking model within the framework of C-IF information. Drawing from the suggested C-IF scoring mechanism, this research introduces novel concepts related to comprehensive C-IF scoring functions and comprehensive disagreement metrics. Subsequently, a comprehensive disagreement matrix is formulated, with its entries quantifying the extent of disagreement in assigning specific ranks to each alternative across all criterion-wise precedence relationships. This paves the way for the development of a new C-IF scoring-mediated median ranking model, offering decision analysts a tool to navigate intricate C-IF information and derive dependable decision-analytic outcomes.https://www.tandfonline.com/doi/10.1080/08839514.2024.2335416 |
| spellingShingle | Ting-Yu Chen Circular Intuitionistic Fuzzy Median Ranking Model with a Novel Scoring Mechanism for Multiple Criteria Decision Analytics Applied Artificial Intelligence |
| title | Circular Intuitionistic Fuzzy Median Ranking Model with a Novel Scoring Mechanism for Multiple Criteria Decision Analytics |
| title_full | Circular Intuitionistic Fuzzy Median Ranking Model with a Novel Scoring Mechanism for Multiple Criteria Decision Analytics |
| title_fullStr | Circular Intuitionistic Fuzzy Median Ranking Model with a Novel Scoring Mechanism for Multiple Criteria Decision Analytics |
| title_full_unstemmed | Circular Intuitionistic Fuzzy Median Ranking Model with a Novel Scoring Mechanism for Multiple Criteria Decision Analytics |
| title_short | Circular Intuitionistic Fuzzy Median Ranking Model with a Novel Scoring Mechanism for Multiple Criteria Decision Analytics |
| title_sort | circular intuitionistic fuzzy median ranking model with a novel scoring mechanism for multiple criteria decision analytics |
| url | https://www.tandfonline.com/doi/10.1080/08839514.2024.2335416 |
| work_keys_str_mv | AT tingyuchen circularintuitionisticfuzzymedianrankingmodelwithanovelscoringmechanismformultiplecriteriadecisionanalytics |