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针对状态概率与准则权重均为区间数且准则值有缺失的离散型模糊随机多准则决策问题,设计了一种基于信息集结的新方法.该方法在区分准则类型和确定决策者的风险偏好水平后,首先根据准则类型利用最大、最小算子计算方案集在不同状态下有缺失值的准则上的正、负理想值,再通过决策者的风险偏好水平与正、负理想值补充方案集在不同状态下缺失的准则值,然后参照准则类型与决策者的风险偏好水平集结方案集在不同状态下赋值为梯形模糊数的准则值并进行规范化,接着利用熵与离差最大化分别构建规划模型以求解最优状态概率分布与最优准则权重向量,进而得到方案集的综合评价值并确定排序,最后给出具体算例.结果显示了该方法的有效性和可行性.
Aiming at the discrete-time fuzzy stochastic multi-criteria decision making problem whose state probabilities and criterion weights are both interval numbers and the rule values are missing, a new method based on information aggregation is proposed. The method is based on the classification of criteria and the decision-maker’s risk preference level First, according to the criterion type, the maximum and minimum operators are used to calculate the positive and negative ideal values of the scheme with missing values under different states, and then through the decision-maker’s risk preference level and the positive and negative ideal value complement programs Then the criterion values missing in different states are normalized and normalized according to the criteria type and the risk preference level of the decision makers, and then the planning model is constructed by maximizing entropy and dispersion respectively To solve the optimal state probability distribution and the optimal criterion weight vector, and then get the comprehensive evaluation value of the program set and determine the order, and finally give the concrete example.The results show the effectiveness and feasibility of the method.