Research On Modeling And Application Of Pythagorean Hesitant Fuzzy Linguistic Group Decision Making

With the development and transformation of our country,many decision-making issues have become more complex and changeable in the new environment,and contain uncertainties such as the ambiguity.How to make objective and effective decision on issues under the environment of uncertain information has become domestic and foreign hot issues.Therefore,this thesis builds the decision-making models based on the Pythagorean hesitant fuzzy linguistic term set and its degenerate form and applies them to practical problems such as targeted poverty alleviation,talent selection,supplier garting,route planning and others.First of all,in view of the objective and effective aggregation of information which expressed by intuitionistic fuzzy linguistic term set,this thesis discusses the intuitionistic fuzzy linguistic entropy that comprehensively considers information,and introduces the intuitionistic fuzzy linguistic induced generalized ordered weighted averaging operator and intuitionistic fuzzy linguistic induced the generalized hybrid weighted averaging operator.The decision model based on the intuitionistic fuzzy linguistic hybrid weighted operator is constructed to solve the problem of targeted poverty alleviation.Secondly,under the interval-value Pythagorean uncertain linguistic term set which is the extended form of the intuitionistic fuzzy linguistic term set,the interval Pythagorean uncertain linguistic Euclidean distance measure and the aggregation operators are studied.The outranking relationship classification model of interval-value Pythagorean uncertain linguistic Euclidean distance measure is established to deal with supplier grating issues.The proposed classification model effectively solves the problem of determining the threshold in the priority relationship classification model.Thirdly,for the problem of incompletely reliable information evaluation caused by the unfamiliarity of things and cognitive limitations,this thesis proposes the interval probability hesitant fuzzy linguistic term set which considers reliability of the description.Based on the interval probability hesitant fuzzy linguistic variables,the distance degree measure,possibility degree measure,information aggregation operators,geometric consistency index are discussed.Also,the interval probability hesitant fuzzy linguistic TOPSIS classification model and the interval probability hesitant fuzzy linguistic AHP decision model are established to deal with the problem of supplier rating and talent selection respectively.Finally,in order to unify the processing different information representations,in this thesis we study the Pythagorean hesitant fuzzy linguistic term set.To help travelers fully consider time,distance,economic cost and other factors,the Pythagorean hesitant fuzzy linguistic aggregation operators are investigatived.Combined with the research of Dijkstra algorithm,the algorithm about the path intelligent recommendation based on Pythagorean hesitant fuzzy linguistic term set is constructed to deal with the route planning problem of scenic spots.The comparative analysis illustrates the practicability and rationality of the above models.These decision-making models can be applied to solve related types of multi-attribute group decision-making problems.