Aggregation Of Expert's Opinion With Dynamic Weight For Fuzzy Group Decision-Making

Group decision-making is a method of making a decision by some people on the same question.As the complexity and uncertainty of the realistic questions and fuzziness of human knowing,the fuzzy numbers are more suitable employed to descript the realistic questions and response the expert's opinion.So fuzzy group decision-making(FGDM)are widely used to solve the realistic questions.Due to the special structure of fuzzy numbers, the theory and method of FGDM are not perfect and many questions in the fielded are still unsolved.How to aggregate the expert's opinion with L-R fuzzy numbers by dynamic weight are studied in this paper.In order to obtain a good aggregation that responses the experts' consistent opinion,the following two questions must be solved:1)whether theαcut sets of L-R fuzzy numbers can express the expert's opinion or not when the degree of membership isα;2)the relation between the expert's weight w and degree of membershipα.In order to solve these questions, firstly,theαsubordination sets are defined to express the expert's pessimistic and optimistic opinion.The average deviations and the similarities of the expert's pessimistic and optimistic opinion are defined respectively.We study the relationship between the expert's weight and degree of membership and find that the expert's weight is changeable and not fixed with the changing of the degree of membership.The weight is divided into pessimistic and optimistic weight at the same time.They are not linked to together. Secondly,the aggregation of dynamic weight is proposed.We have generalized to the aggregation of multi-attribute fuzzy group decision-making. Three kinds of algorithms are derived from L-R fuzzy numbers.Finally,we discuss the question based on TOPSIS.The aggregation from the dynamic weight is developed in this thesis.We consider not only inconsistent degree of the expert's pessimistic and optimistic opinion but also the relation between the expert's weight and the degree of memberships in this process.The method of dynamic weight is more practical and improves the method of integrating in the expert's opinion.