{"title":"基于分布式语言偏好关系的合作博弈共识调整机制,用于群体决策","authors":"Yanjing Guo;Yiran Wang;Zhongming Wu;Fanyong Meng","doi":"10.1109/TFUZZ.2024.3496661","DOIUrl":null,"url":null,"abstract":"Distribution linguistic preference relations (DLPRs) play a crucial role in group decision making due to their ability to capture hesitation and uncertainty in individual judgments. By utilizing multiple linguistic variables with associated distribution proportions, DLPRs offer a flexible way to represent preferences. However, current models that use DLPRs often overlook two crucial factors: the ordinal consistency of preference relations and the fairness of adjustment allocation within the DLPRs-based consensus reaching process. In this article, we propose a cooperative game-based minimum adjustment consensus reaching mechanism that accounts for both ordinal consistency and the hesitant degree in DLPRs. This approach leverages the properties of indices in cooperative game theory to ensures a fair allocation of consistency and consensus adjustments, while maintaining ordinal consistency and controlling the hesitant degree of DLPRs through the construction of appropriate constraints to preserve their quality. In addition, a new algorithm is developed to manage completeness, ordinal and acceptable cardinal consistency, consensus-reaching, and hesitation in scenarios involving incomplete DLPRs. Finally, a case study is provided to demonstrate the practical application of the proposed method. Sensitivity and comparative analyzes with existing models are performed to assess the performance of the approach in terms of quality, fairness, and efficiency.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 3","pages":"919-931"},"PeriodicalIF":10.7000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cooperative Game-Based Consensus Adjustment Mechanism With Distribution Linguistic Preference Relations for Group Decision Making\",\"authors\":\"Yanjing Guo;Yiran Wang;Zhongming Wu;Fanyong Meng\",\"doi\":\"10.1109/TFUZZ.2024.3496661\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Distribution linguistic preference relations (DLPRs) play a crucial role in group decision making due to their ability to capture hesitation and uncertainty in individual judgments. By utilizing multiple linguistic variables with associated distribution proportions, DLPRs offer a flexible way to represent preferences. However, current models that use DLPRs often overlook two crucial factors: the ordinal consistency of preference relations and the fairness of adjustment allocation within the DLPRs-based consensus reaching process. In this article, we propose a cooperative game-based minimum adjustment consensus reaching mechanism that accounts for both ordinal consistency and the hesitant degree in DLPRs. This approach leverages the properties of indices in cooperative game theory to ensures a fair allocation of consistency and consensus adjustments, while maintaining ordinal consistency and controlling the hesitant degree of DLPRs through the construction of appropriate constraints to preserve their quality. In addition, a new algorithm is developed to manage completeness, ordinal and acceptable cardinal consistency, consensus-reaching, and hesitation in scenarios involving incomplete DLPRs. Finally, a case study is provided to demonstrate the practical application of the proposed method. Sensitivity and comparative analyzes with existing models are performed to assess the performance of the approach in terms of quality, fairness, and efficiency.\",\"PeriodicalId\":13212,\"journal\":{\"name\":\"IEEE Transactions on Fuzzy Systems\",\"volume\":\"33 3\",\"pages\":\"919-931\"},\"PeriodicalIF\":10.7000,\"publicationDate\":\"2024-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Fuzzy Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10750417/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Fuzzy Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10750417/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Cooperative Game-Based Consensus Adjustment Mechanism With Distribution Linguistic Preference Relations for Group Decision Making
Distribution linguistic preference relations (DLPRs) play a crucial role in group decision making due to their ability to capture hesitation and uncertainty in individual judgments. By utilizing multiple linguistic variables with associated distribution proportions, DLPRs offer a flexible way to represent preferences. However, current models that use DLPRs often overlook two crucial factors: the ordinal consistency of preference relations and the fairness of adjustment allocation within the DLPRs-based consensus reaching process. In this article, we propose a cooperative game-based minimum adjustment consensus reaching mechanism that accounts for both ordinal consistency and the hesitant degree in DLPRs. This approach leverages the properties of indices in cooperative game theory to ensures a fair allocation of consistency and consensus adjustments, while maintaining ordinal consistency and controlling the hesitant degree of DLPRs through the construction of appropriate constraints to preserve their quality. In addition, a new algorithm is developed to manage completeness, ordinal and acceptable cardinal consistency, consensus-reaching, and hesitation in scenarios involving incomplete DLPRs. Finally, a case study is provided to demonstrate the practical application of the proposed method. Sensitivity and comparative analyzes with existing models are performed to assess the performance of the approach in terms of quality, fairness, and efficiency.
期刊介绍:
The IEEE Transactions on Fuzzy Systems is a scholarly journal that focuses on the theory, design, and application of fuzzy systems. It aims to publish high-quality technical papers that contribute significant technical knowledge and exploratory developments in the field of fuzzy systems. The journal particularly emphasizes engineering systems and scientific applications. In addition to research articles, the Transactions also includes a letters section featuring current information, comments, and rebuttals related to published papers.