基于证据理论的偏好型直觉模糊群决策方法

针对直觉模糊多属性群决策问题,研究属性和专家权重的确定以及信息的集结方法.利用直觉模糊熵确定属性客观权重,并根据偏好信息确定合理的属性综合权重;在属性层面区分专家权重,将直觉模糊评价值作为Mass函数,构建证据冲突度模型确定专家权重,并利用犹豫度加以修正,避免综合支持度低而对方案排序影响大的专家权重过分削弱;采用证据理论集结决策信息,根据得分值进行方案排序.最后通过算例分析,验证了所提出方法的合理性和有效性.

Method for intuitionistic fuzzy group decision-making with preference based on evidence theory

Aiming at the intuitionistic fuzzy multi-attribute group decision-making problem, the methods of attribution-weight and expert-weight determination and information integration are proposed. The intuitionistic fuzzy entropy is used to obtain the objective weight of attribution. The attribution''s subjective weight and objective weight are synthesized based on the preference information to determine the reasonable weight. In order to determine more reasonable expert-weight, diffident weight is given to diffident expert for the same attribution. The intuitionistic fuzzy value of attribution is turned into Mass function, and the method on expert-weight determination based on the evidence conflict degree is proposed. The hesitating degree is used to modify the expert''s weight whose comprehensive support is low but has great influence on project ranking. The decision-making information is integrated according to evidence synthesis rules, and the score function is used to rank projects. The rationality and effectiveness of the proposed method are verified by an example.