Research On Several Types Of Fuzzy Multiple Attribute Decision Making Method By Considering Preference Information

With technological advances and rapid economic development,decision makers are faced with an ever-expanding amount of information and an ever-increasing level of uncertainty in the decision-making environment.The preferences for risk reflect the decision makers’ tendency and attitude towards risk,reflecting the subjective preference due to the differentiation of the decision makers’ cognitive level,which has a significant impact on the reasonableness and accuracy of the decision outcome.Therefore,taking into account and integrating the decision makers’ preference information can effectively enhance the flexibility and applicability of decision models in practice and facilitate better scientific decision-making.The construction of multi-attribute decision making models with preference under several special fuzzy data representations(independent trapezoidal intuitionistic fuzzy numbers,q-rung orthopair fuzzy number,L-R fuzzy numbers)is proposed and improved.The main contents and results of this thesis are as follows:(1)For multi-attribute decision problems in which the attribute values are independent trapezoidal intuitionistic fuzzy numbers,a novel independent trapezoidal intuitionistic fuzzy ranking method is first defined.The method not only reflects the risk preferences of the decision makers and covers all possible values in the feasible domain,but its degenerate form has also proven to be backward compatible.Secondly,an independent trapezoidal intuitionistic fuzzy similarity measure with preference is proposed based on a three-stage projection,and a novel attribute weight generation algorithm is established as a result.Finally,an independent trapezoidal intuitionistic fuzzy VIKOR decision method(V-ITIFE)is constructed based on the band preference order relationship and similarity measure formula,and the feasibility and effectiveness of the method is further illustrated by the siting calculation of photovoltaic power plants.(2)For multi-attribute decision problems with attributes valued as qorder orthogonal fuzzy numbers,a preference score function of q-rung orthopair fuzzy numbers with preference is defined in conjunction with the decision makers’ risk preferences,and it is shown that this preference score function with preference satisfies the good properties.Then,the QMAIRCA decision model was constructed in a q-rung orthopair fuzzy environment,which has high stability and ease of operation and can be adapted to more complex decision environments.Finally,the applicability of the model is illustrated through bank risk assessment calculations and the impact of differences in decision makers’ risk preferences on the model results is analyzed.(3)For the multi-attribute decision problem whose attribute values are L-R fuzzy numbers,firstly,we systematically review two outlier-based LR fuzzy ranking methods,clarify their shortcomings through counterexamples,and analyze various failure cases of existing ranking methods.Secondly,a novel hybrid preference two-dimensional outlier ranking method is proposed based on the two-dimensional outlier degree and the risk preferences of the decision maker.Then,through informative comparative examples,the unique advantages of this paper’s method in terms of differentiation and compatibility are demonstrated,and the rationality and effectiveness of the proposed L-R fuzzy number ranking method are verified.Finally,an L-R fuzzy multi-attribute decision making method based on a hybrid preference two-dimensional outlier ranking method is constructed.