An improved EDAS method based on the cosine measure under the nested probabilistic linguistic environment  

作　　者：Lan Li Xinxin Wang Zeshui Xu 

机构地区：[1]Business School,Sichuan University,Chengdu,People’s Republic of China

出　　处：《Journal of Control and Decision》2025年第1期65-80,共16页控制与决策学报(英文)

基　　金：supported by the National Natural Science Foundation of China under grant numbers 72101168,71571123;China Postdoctoral Science Foundation under grant number 2021M692259.

摘　　要：New opportunities and challenges for information representation and processing are brought about by the rapid development of artificial intelligence.This study offers a new decision-making method that decreases information distortion and increases computational efficiency by fusing the nested probabilistic linguistic terms with the EDAS decision-making method approach.Firstly,we introduce the concept,property,and demonstration of the cosine similarity of nested probabilistic linguistic terms,which allows for a more precise measurement of the degree of departure between their content.Secondly,the attribute weights are generated using the normalised attribute information difference value approach,which is based on the premise that attributes with bigger differences in evaluation information are more significant.Furthermore,the proposed method is utilised to address a supplier selection issue related to the procurement of medical equipment.Ultimately,the method is proven to be feasible and superior by comparison assessments with other measuring methods and decision-making methods.

关 键 词：Multidimensional decision-making nested probabilistic linguistic term set cosine measure EDAS weight determination 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]