Research On Multi-attribute Decision Making Method Based On MABAC And Prospect Theory

With the continuous development of society,the problem of decision-making becomes more and more complicated.Considering the uncertainty of decision environment and bounded rationality of decision makers,this thesis extended the multi-attribute decision making method based on MABAC and prospect theory to probabilistic linguistic term set,probabilistic double hierarchy linguistic term set and interval probabilistic double hierarchy linguistic term set,The proposed methods are probabilistic linguistic multi-attribute decision making method based on MABAC and prospect theory(PL-PT-MABAC),probabilistic double hierarchy linguistic multi-attribute decision making method based on MABAC and prospect theory(PDHL-PT-MABAC)and interval probabilistic double hierarchy linguistic multi-attribute decision making method based on MABAC and prospect theory(IPDHL-PT-MABAC),which optimized the existing uncertain multi-attribute decision making methods.Meanwhile,the improved entropy weight method and improved CRITIC method were adopted in the PL-PT-MABAC method and the PDHL-PT-MABAC method to obtain the objective attribute weights,respectively.Considering the influence of subjective attribute weights,combination weights are proposed to obtain attribute weights.In IPDHL-PT-MABAC method,an improved MEREC method was used to directly obtain attribute weights.Combined with the characteristics of MABAC method and prospect theory in different linguistic environments,the proposed methods are applied to location selection problems and numerical examples are analyzed.Finally,the proposed methods were compared with other existing methods,which verified the validity and scientificity of the innovative methods.