Research On Dominant Decision Method Based On Complex Fuzzy Information

Multiple attribute decision theory and methods are one of the important parts of modern decision science,which have been widely used to solve problems such as investment schemes,location selection and project evaluation,etc.In order to describe complicated decision information more reasonably and effectively,fuzzy sets theory has been introduced into the field of decision analysis.Some multiple attribute decision making methods have been researched in this paper based on complicated fuzzy information.(1)A multiple attribute group decision making method has been proposed base on the PROMETHEE-AQM model under interval-valued intuitionistic fuzzy sets.Firstly,the similarity function is defined for interval-valued intuitionistic fuzzy values,and a method is presented for ranking interval-valued intuitionistic fuzzy numbers based on this function.Secondly,a new priority relationship is defined based on the 0-1 precedence relationship matrix and the preference index entropy of each decision maker.Finally,the optimal alternative is calculated by the collective 0-1 precedence relationship matrix.The interval-valued intuitionistic fuzzy information multiple attribute group decision making method retains the meaning of the original semantics by the PROMETHEE and AQM models and the optimal alternative problem can be solved by the comparison of entropy values.(2)The Pythagorean fuzzy ELECTRE method with unknown attribute weights is proposed.Firstly,the Pythagorean fuzzy symmetric entropy is defined,and then the method for solving the unknown attribute weight is given.Secondly,the Pythagorean fuzzy symmetric cross entropy is introduced into the PF-ELECTRE method to calculate the Pythagorean fuzzy discordance indexes,and the optimal alternative is determined.It is more objective and accurate to determine attribute weights by Pythagoras fuzzy symmetric entropy than the subjective assignment method,which can better explain the obtained results.The PF-ELECTRE method,which uses symmetric cross entropy to calculate the discordance index,effectively reduces the loss of information in the calculation process.(3)The double hierarchy hesitant fuzzy linguistic aggregation operators are proposed based on Einstein T-conorm and T-norm.Firstly,some new operations are defined for the double hierarchy hesitant fuzzy linguistic elements with Einstein T-conorm and T-norm,and their properties and relationships are studied.Secondly,some double hierarchy hesitant fuzzy linguistic aggregation operators have been defined based on Einstein operators.Furthermore,some Einstein double hierarchy hesitant fuzzy linguistic aggregation operators have been introduced including the Einstein double hierarchy hesitant fuzzy linguistic Bonferroni mean operator and the Einstein double hierarchy hesitant fuzzy linguistic weighted Bonferroni mean operator.Finally,based on new aggregation operators,a new method with unknown attribute weights is proposed to solve the multiple attribute decision making problems in the double hierarchy hesitant fuzzy linguistic environment.The double hierarchy hesitant fuzzy linguistic term set can describe fuzzy information more precisely and concretely than the hesitant fuzzy linguistic term set.Due to the flexibility and robustness of Einstein operator,Einstein double hierarchy hesitant fuzzy linguistic operator can explain the decision result more reasonably.