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出 处:《控制与决策》2013年第5期716-720,725,共6页Control and Decision
基 金:国家973计划项目(2010CB328104-02);国家自然科学基金项目(71071034);江苏省普通高校研究生科研创新计划项目(CXZZ-0183);教育部博士研究生学术新人奖资助项目
摘 要:在直觉模糊群决策中,一般通过赋权法对不同专家或决策者进行有效区分,相关研究多偏重等值赋权与主观赋权,但两者均存在不足.基于此,提出一种仅依靠非犹豫度(专家对属性的非犹豫程度意味着对该属性信息的掌握程度)的精确加权(AWD)方法,并证明了该方法的单调性与尺度不变性.在AWD方法基础上,提出FOAWA和IFOAWG算子,证明了新算子的幂等性、有界性与交换性.最后,通过算例展示了所提出方法的可行性和有效性.The weight-determined method is a good technique to distinguish different experts in intuitionistic fuzzy group decision making, such as the equal-weight method and the subjective weight-determined method. However, there are some puzzles in these two weight-determined methods. Therefore, an accurate weight-determined(AWD) method based on the membership and non-membership is proposed. The main idea of the AWD method is that putting larger weight into the expert with more attribute information. Then the monotonicity and the scale-invariance of the AWD method are investigated. Based on the AWD method, two intuitionistic fuzzy ordered accurate weighted aggregation operators are developed, and their properties are investigated in detail. Finally, a practical example is provided to illustrate the feasibility and effectiveness of the proposed method.
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