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针对具有正态三角模糊随机变量且属性权重未知的多属性决策问题,提出基于前景均值-方差(M-V)准则的正态三角模糊随机多属性决策方法.该方法首先构建正态三角模糊随机决策矩阵,进而通过运算得到属性值的期望与方差,并将其转化为M-V决策矩阵;然后,通过定义前景效应构建前景M-V决策矩阵,利用改进灰色系统理论模型求解属性权重值,获取综合前景M-V决策矩阵;最后,定义前景序关系,两两比较前景M-V价值获取方案排序.在此基础上,通过案例验证了所提出方法的可行性及有效性.
Aiming at the multi-attribute decision-making problems with normal triangular fuzzy random variables and unknown attribute weights, a normal triangular fuzzy stochastic multiple attribute decision making method based on the foreground mean-variance (MV) criterion is proposed. Firstly, a normal triangular fuzzy stochastic decision matrix , And then derive the expectation and variance of the attribute value through calculation and convert it into a MV decision matrix. Then, the foreground MV decision matrix is constructed by defining the foreground effect, and the improved gray system theory model is used to solve the attribute weight value to obtain the comprehensive foreground MV decision matrix Finally, we define the relationship between foreground and foreground MV, and compare the two scenarios to get the value of MV.Finally, we verify the feasibility and effectiveness of the proposed method through examples.