Research On Multi-attribute Group Decision Making With Multi-granularity Linguistic Terms

Multi-attribute group decision making with multi-granularity evaluative linguistic terms is an important research content of multi-attribute group decision making,and is a hotspot problem in the field of modern decision-making.It's approaches and theoretical knowledge has widely applied in people's daily life.In the decision-making process,because of the vagueness and uncertainty of objective things,decision-makers are difficult to obtain quantitative information of the criteria of the objects.Therefore,it's an optional method to use evaluative linguistic terms to describe the criteria of the decision-making objects.In the daily group decision-making problem,because of the different knowledge background and speaking habit,decision-makers usually use their own preference linguistic term sets.If the number of linguistic phrases in the different linguistic term sets are unequal,then it is called multi-granularity linguistic term sets.Aiming at the multi-granularity linguistic terms based multi-attribute group decision making problem,this paper studies the following:(1)Unification methods based on linguistic semantics.Based on the existing methods,this context proposes a new multi-granularity linguistic unification algorithm based on triangle membership function and 2-tuple linguistic model.The properties of the new algorithm is proposed,such as monotonicity and boundedness.Theoretically,we analyze and compare the new and the existing methods that based on linguistic semantics,in addition,an example is used to arrival at a conclusion.(2)Unification methods based on linguistic labels.According to the existing linguistic label based unification methods,this paper proposes an extension method,which based on the ordinal proportional 2-tuples.Theoretically,we analyze and compare the new and the existing linguistic label methods,in addition,an example is given to arrival at a conclusion.(3)Multi-attribute group decision making model based on new unification methods.First,according to the numerical entropy and 2-tuple entropy weight method,an improved entropy weight method based on the position index function of ordinal proportional 2-tuples is proposed to determine the criteria weights.Second,this paper proposes an improved aggregation operator by combining the ordinal proportional 2-tuple model and OWA operator to aggregate the ordinal proportional 2-tuples.Third,combining the above researches,this paper presents a multi-attribute group decision-making model.(4)Example analysis.The feasibility and effectiveness of the model is verified by the practical application of the basic work evaluation in the police station.