Heterogeneous multi-attribute group decision making based on missing attributes
With the increasing complexity of decision-making environment,due to the limitation of human knowledge and experience,the difference of expression habits and the complexity of decision-making information,it is often difficult for decision makers to use a unified standard to measure the expression of decision-making information.Aiming at the common problems of attribute missing and information heterogeneity in complex decision-making environment,a new heterogeneous group decision-making method is proposed.This method is based on expert similarity,completes missing attributes based on the cross attribute set,and processes different attribute values through normal distribution transformation to achieve attribute standardization.The weight is determined by calculating the similarity between attributes,and the TOPSIS method is used to sort,and the decision is made according to the final sorting result.The effectiveness and practicability of this method are verified by taking the selection of cold chain distribution center of an agricultural product company in Guangxi as an example.
missing attribute setheterogeneous attribute setmulti-attribute group decision makingsimilarity
万方数据
维普
