关键词: 概率不完备信息, 犹豫模糊偏好关系, 群决策模型, 期望一致性, 群体一致性调整算法

Abstract: A group decision making model based on optimization model and consistency adjustment algorithm was established for the group decision problems with incomplete occurrence probability information of hesitant fuzzy elements. First of all, some new concepts were introduced, including Probability Incomplete Hesitant Fuzzy Preference Relations (PIHFPRs), the expected consistency of PIHFPRs and the acceptable additive expected consistency of PIHFPRs. Secondly, the minimization of deviations between PIHFPRs and the weight vectors was regarded as the objective function, a linear optimization model was constructed to calculate the probability information of the PIHFPRs. Then, by using the integrated operator for weighted probability incomplete hesitant fuzzy preference relations, the comprehensive PIHFPR was determined. A group consistency adjustment algorithm was further designed, which not only makes the adjusted PIHFPRs are acceptable expected consistent, but also can obtain the weight vectors for alternatives. Finally, the proposed group decision-making model was applied to a numerical example about the selection of block chain. Experimental results show that the decision-making results are reasonable and reliable, and the actual situation can be reflected.

Key words: probability incomplete information, hesitant fuzzy preference relation, group decision-making model, expected consistency, group consistency adjustment algorithm