doi: 10.4304/jsw.6.3.508-515
Assigning Method for Decision Power Based on Linguisitc 2-tuple Judgment Matrices
- 1 Business School of Jiaxing University, Jiaxing, China
- 2 Mathematics and Information Engineering School of Jiaxing University, Jiaxing, China
- 3 Department of Computer Science and Technology, Huaihua University, Huaihua, China
Abstract
Decision power is very important in group decision making, which effects the final decision making result. When there exists uncertainty in group decision making, it is easy for an expert to express his/her preferences using fuzzy linguistic term such as ‘good’, ‘very good’. The linguistic 2-tuple representation model was selected to represent fuzzy linguistic term for its accuracy in representing fuzzy terms and less loss of information in processing. To obtain the objective decision power in group decision making where the experts express their opinions using linguistic 2-tuple judgment matrices, the paper put forward a new approach to assign decision power based on element consistency level. And the method for calculating the contribution degree of each expert was also provided. The proposed method thought of calculating the different weight to aggregate different element according to the element consistent level. An illustrated example was used to demonstrate the proposed method. And a GDSS based on the method was also developed to simplify the application in VB.NET. The GDSS was applied to building non-financial performance system for listed company in small and medium enterprise board in China, which showed its reasonability.
Keywords
- decision power
- linguistic 2-tuple
- grou
How to Cite
Xixiang Zhang, Guangxue Yue, and Xiajie Zheng, "Assigning Method for Decision Power Based on Linguisitc 2-tuple Judgment Matrices," Journal of Software, vol. 6, no. 3, pp. 508-515, 2011. https://doi.org/ 10.4304/jsw.6.3.508-515
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).