Multi-attribute group decision-making method based on dual probabilistic linguistic integrated distance measure and regret theory
Dual probabilistic linguistic term sets(DPLTSs)are able to express the evaluation information of decision makers in both membership degree and non-membership degree,which is more effective in dealing with multi-attribute group decision-making(MAGDM)problems.First,to address the shortcomings of the current research on distance measures of the DPLTSs,this paper proposes a new integrated distance measure that can accurately characterize the differences between the DPLTSs without extending the number of probabilistic linguistic term elements.Second,the method of determining expert weights is given based on the similarity of evaluations and experts'trustworthiness;then,the specific steps of reaching group consensus are constructed and the required decision matrix is obtained.Third,the attribute weights are calculated based on the deviation maximization method,and the MAGDM decision method based on regret theory is constructed.Finally,the numerical analysis of the heavy-duty truck research and development strategy selection for a new energy vehicle enterprise is carried out as an example to verify the applicability and effectiveness of the method;and the stability and rationality are further verified through sensitivity analysis and comparative analysis.
dual probabilistic linguistic term setsmulti-attribute group decision-makingdistance measureconsensus-reachingregret theory
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