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针对方案属性信息不确定、决策信息分布多个阶段以及传统加权平均算子权重没有考虑集成数据间相互关系等问题,提出一种基于不确定幂加权几何平均算子的动态多目标决策方法.该方法不仅可以集结决策者在多阶段给出的不确定信息,同时结合模糊集理论,考虑了集结模糊信息时数据间的支撑程度对权重系数的影响,强化了对模糊信息的处理,使得被评估的信息更加贴近实际.然后给出基于可能度的排序方法来选择最优方案.最后通过算例分析说明了所提出方法的合理性和可行性.
Aiming at the problems such as uncertainty of scheme attribute information, multiple stages of decision information distribution and the weight of traditional weighted average operator without considering the relationship of integrated data, a dynamic multi-objective decision-making method based on uncertain power-weighted geometric mean operator is proposed. The method not only integrates the uncertain information given by decision-makers in multi-stages, but also considers the influence of the degree of support between the data on the weighting coefficient when assembling the fuzzy information, and strengthens the processing of the fuzzy information, The information is more realistic, and then the ranking method based on probability is given to choose the optimal solution.Finally, the example analysis shows that the proposed method is reasonable and feasible.