基于云模型的Pythagorean模糊语言多属性决策方法

Multi attribute decision making method based on cloud model with Pythagorean fuzzy linguistic numbers

针对专家给出的属性值为Pythagorean模糊语言且专家权重与属性权重均未知的多属性决策问题进行了研究,提出一种基于云模型的多属性决策方法。首先,根据Pythagorean模糊语言决策信息的距离熵计算得到属性权重;其次,计算决策矩阵间的距离从而得到各决策专家权重;再次,构建Pythagorean模糊云模型决策矩阵并利用专家权重和属性权重进行信息集结;最后,基于TOPSIS方法求取正、负理想解,依据理想解计算各方案贴近度并据此对各备选方案进行排序选择。案例分析表明,该方法优化了复杂环境下的决策,避免了决策信息的丢失,能够较好地解决决策信息的不确定性和决策过程的随机性,具有一定的可行性和有效性。

To solve the multi-attribute decision making problem in which the attribute value is Pythagorean fuzzy language,and the expert weight as well as the attribute weight are unknown,this paper proposed a multi-attribute decision making method based on cloud model.Firstly,this method calculated the attribute weights according to the distance entropy of Pythagorean fuzzy language decision information.Secondly,this method obtained the weight of each decision expert based on the distance between his/her decision matrix and other expert decision matrices.Thirdly,this method constructed the decision matrix of the Pythagorean fuzzy cloud model,and utilized the expert weights,along with attribute weights,to integrate the decision information.Finally,it sorted the alternative schemes on the basis of the closeness which was calculated according to the positive and negative ideal solutions obtained by TOPSIS method.A numerical example shows that the method optimizes the decision-ma-king in complex environment and avoids the loss of decision-making information.It also demonstrates that the method can tackle the uncertainty of decision information and the randomness of decision process more effectively.