基于概率语言型Z-number的EDAS多属性决策方法研究OA

This paper proposes an EDAS multi-attribute decision-making method based on probabilistic linguistic Z-number,and the research is conducted from three aspects:methodological construction,numerical example verification,and comparative analysis.The EDAS method calculates the positive and negative distances from each alternative to the average solution,determines attribute weights using the entropy weight method,and further ranks the alternatives according to the weighted positive and negative distances.Subsequently,the Z-EDAS method is applied to the cloud service selection problem for new energy vehicles,and the optimal alternative is derived.Finally,a comparative analysis is conducted between the proposed method and the existing TOPSIS method,and the results show that the alternative rankings obtained by the two methods are completely consistent,which verifies the feasibility and effectiveness of the constructed Z-EDAS method.In conclusion,this research provides an important scientific tool for decision-makers to address complex and variable real-world decision-making problems,which helps improve the accuracy and reliability of decision-making.