交互式直觉模糊群体共识决策模型研究

直觉模糊群体决策问题是模糊决策理论与方法研究领域的一个热点问题，但目前的研究主要关注基于直觉模糊数运算规则的直觉模糊信息集成问题，而对决策个体给出的偏好信息一致性和群体共识过程缺乏深入研究。本项目针对现有文献中直觉模糊数运算规则存在的局限性，开展基于区间数运算规则为基础的直觉和区间直觉模糊偏好关系一致性理论研究，提出直觉和区间直觉模糊偏好关系区间排序权重求解方法、一致性指标检验模型和不一致修正与调整方法；进一步地，进行交互式直觉与区间直觉模糊偏好关系以及直觉模糊多属性的群体共识决策方法的研究，提出群体直觉模糊信息集成、群体方案排序或选优的新方法，给出群体共识性测度模型和非共识交互式调整方法，并进行交互式直觉模糊群体共识决策的应用研究。其研究成果对进一步发展和完善直觉模糊群体决策理论与方法体系，改进信息集成机制，提高群决策科学化及其质量与效率具有重要意义。

Intuitionistic fuzzy group decision-making has arisen as an active research topic in the field of fuzzy decision making theory and methodology. Current research in this area focuses on different information aggregation mechanisms based on various operation rules for intuitionistic fuzzy numbers. In-depth and systematic research has yet to be conducted on the consistency of preference information furnished by the decision-maker and group consensus building process. After addressing limitations of operation rules for intuitionistic fuzzy numbers in existing literature, this proposal aims to investigate consistency of intuitionistic and interval-valued intuitionistic fuzzy preference relations based on operation rules for interval numbers. The applicants will establish mathematical models for deriving interval priority weights for intuitionistic and interval-valued intuitionistic fuzzy preference relations, testing consistency index, and repairing and adjusting inconsistent preference relations. Building upon the consistency research, the applicant will carry out research on interactive group consensus decision models based on intuitionistic and interval-valued intuitionistic fuzzy preference relations as well as the intuitionistic fuzzy multiattribute decision framework. The applicants will develop innovative approaches to aggregating group intuitionistic fuzzy decision information, ranking and selecting alternatives for group decisions. Measurement models will be furnished for assessing group consensus and interactive adjustment methods will be established to repair non-consensus decision data. These new decision technologies will be applied to and calibrated with complex and multi-facet real-world case studies. It is expected that this proposed research will further develop and refine intuitionistic fuzzy group decision methodology, improve information aggregation mechanisms, and play a significant role in providing a scientific framework for group decision and enhancing the quality and efficiency of group decision making.