Similarity-Based Approach for Group Decision Making with Multi-Granularity Linguistic Information

Author(s):  
Jian Lin ◽  
Riqing Chen ◽  
Qiang Zhang

The aim of this article is to investigate the approach for multi-attribute group decision-making, in which the attribute values take the form of multi-granularity multiplicative linguistic information. Firstly, to process multiple sources of decision information assessed in different multiplicative linguistic label sets, a method for transforming multi-granularity multiplicative linguistic information into multiplicative trapezoidal fuzzy numbers is proposed. Then, a formula for ranking multiplicative trapezoidal fuzzy numbers is given based on geometric mean. Furthermore, the concept of similarity degree between two multiplicative trapezoidal fuzzy numbers is defined. The attribute weights are obtained by solving some optimization models. An effective approach for group decision making with multi-granularity multiplicative linguistic information is developed based on the ordered weighted geometric mean operator and proposed formulae. Finally, a practical example is provided to illustrate the practicality and validity of the proposed method.

Author(s):  
BO PENG ◽  
CHUNMING YE

In this paper, we develop some new aggregation operators with pure linguistic information including the uncertain pure linguistic weighted geometric mean (UPLWGM) operator, the induced uncertain pure linguistic ordered weighted geometric mean (IUPLOWGM) operator, and the induced uncertain pure linguistic hybrid geometric mean (IUPLHGM) operator. These developed aggregation operators are very suitable to deal with the situation where the input arguments are represented in uncertain pure linguistic variables. Also, as a more general type of aggregation operator, the IUPLHGM operator is based on the UPLWGM and IUPLOWGM operators, and it can reflect the importance degrees of both the given uncertain linguistic variables and their ordered positions. Moreover, in the situations where the information about all the attribute weights, the attribute values and the expert weights are expressed in the form of linguistic labels variables, we develop an approach based on the IUPLHGM operator for multiple attribute group decision making with pure linguistic information. Finally, an application of the developed approach to group decision making problem regarding the selection of investments is given. Also, we present a comparative analysis with other related decision making methods to demonstrate the effectiveness of the developed approach.


2012 ◽  
Vol 18 (2) ◽  
pp. 317-330 ◽  
Author(s):  
Guiwu Wei ◽  
Xiaofei Zhao ◽  
Hongjun Wang

In this paper, we investigate the multiple attribute group decision making (MAGDM) problems in which both the attribute weights and the expert weights take the form of real numbers, attribute values take the form of interval intuitionistic trapezoidal fuzzy numbers. Firstly, some operational laws of interval intuitionistic trapezoidal fuzzy numbers are introduced. Then some new aggregation operators including interval intuitionistic trapezoidal fuzzy ordered weighted geometric (IITFOWG) operator and interval intuitionistic trapezoidal fuzzy hybrid geometric (IITFHG) operator are proposed and some desirable properties of these operators are studied, such as commutativity, idempotency and monotonicity. An IITFWG and IITFHG operators-based approach is developed to solve the MAGDM problems in which both the attribute weights and the expert weights take the form of real numbers and attribute values take the form of interval intuitionistic trapezoidal fuzzy numbers. Finally, some illustrative examples are given to verify the developed approach and to demonstrate its practicality and effectiveness.


2020 ◽  
Author(s):  
Teimuraz Tsabadze

The purpose of this chapter is to introduce a new approach for an assessment of the credit risks. The initial part of the chapter is to briefly discuss the existing models of assessment of the credit risks and justify the need for a new approach. Since a new approach is created for conditions of uncertainty, we cannot do without fuzzy mathematics. The proposed approach is based on group decision-making, where experts’ opinions are expressed by trapezoidal fuzzy numbers. The theoretical basis of the offered approach is laid out in the metric space of trapezoidal fuzzy numbers. The new approach is introduced and discussed, and two realization algorithms are given. The toy example of application of the introduced approach is offered as well.


2015 ◽  
Vol 14 (4) ◽  
pp. 11-28 ◽  
Author(s):  
Wei Lin ◽  
Guangle Yan ◽  
Yuwen Shi

Abstract In this paper we investigate the dynamic multi-attribute group decision making problems, in which all the attribute values are provided by multiple decision makers at different periods. In order to increase the level of overall satisfaction for the final decision and deal with uncertainty, the attribute values are enhanced with generalized interval-valued trapezoidal fuzzy numbers to cope with the vagueness and indeterminacy. We first define the Dynamic Generalized Interval-valued Trapezoidal Fuzzy Numbers Weighted Geometric Aggregation (DGITFNWGA) operator and give an approach to determine the weights of periods, using the probability density function of Gamma distribution, and then a dynamic multi-attribute group decision making method is developed. The method proposed employs the Generalized Interval-valued Trapezoidal Fuzzy Numbers Hybrid Geometric Aggregation (GITFNHGA) operator to aggregate all individual decision information into the collective attribute values corresponding to each alternative at the same time period, and then utilizes the DGITFNWGA operator to aggregate the collective attribute values at different periods into the overall attribute values corresponding to each alternative and obtains the alternatives ranking, by which the optimal alternative can be determined. Finally, an illustrative example is given to verify the approach developed.


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