COVID-19 emergency decision-making using q-rung linear diophantine fuzzy set,differential evolutionary and evidential reasoning techniques  

作　　者：G Punnam Chander Sujit Das 

机构地区：[1]Department of Computer science and Engineering,National Institute of Technology,Warangal 506004,India

出　　处：《Applied Mathematics(A Journal of Chinese Universities)》2025年第1期182-206,共25页高校应用数学学报(英文版)(B辑)

摘　　要：In this paper,a robust and consistent COVID-19 emergency decision-making approach is proposed based on q-rung linear diophantine fuzzy set(q-RLDFS),differential evolutionary(DE)optimization principles,and evidential reasoning(ER)methodology.The proposed approach uses q-RLDFS in order to represent the evaluating values of the alternatives corresponding to the attributes.DE optimization is used to obtain the optimal weights of the attributes,and ER methodology is used to compute the aggregated q-rung linear diophantine fuzzy values(q-RLDFVs)of each alternative.Then the score values of alternatives are computed based on the aggregated q-RLDFVs.An alternative with the maximum score value is selected as a better one.The applicability of the proposed approach has been illustrated in COVID-19 emergency decision-making system and sustainable energy planning management.Moreover,we have validated the proposed approach with a numerical example.Finally,a comparative study is provided with the existing models,where the proposed approach is found to be robust to perform better and consistent in uncertain environments.

关 键 词：COVID-19 q-rung linear diophantine fuzzy set differential evolutionary evidential reasoning DECISION-MAKING 

分 类 号：O15[理学—数学]