Title :
A Bayesian Method for Decision of Weight for MADM Model with Interval Data
Author :
Xuan, Sun ; Qinzhou, Niu ; Hefei, Xu
Author_Institution :
Dept. of Electron. & Comput. Sci., Guilin Univ. of Technol., Guilin
Abstract :
The weight in TOPSIS approach (technique for order preference by similarity ideal solution - TOPSIS ) is given by experts or decision makers. The value of weight would be influenced by expertspsila subjective judgments. A slight difference in value of weight may result in diversity of order of alternatives. In this paper, a Bayesian method for decision of weight for MADM model with interval data is introduced. The value of weight is decided by prior information (other expertspsila knowledge, or numerical simulation etc.) and experts´ knowledge (or decision makerspsila experience/preference). This method effectively takes advantage of expertspsila knowledge and avoids the problem with expertspsila subjectivity. An illustrative example is showed to explore the applications of proposed method. The method is valuable for field of multi-attribute decision-making with interval data.
Keywords :
Bayes methods; decision making; decision theory; Bayesian method; MADM model; TOPSIS approach; interval data; multiattribute decision-making; order preference technique; similarity ideal solution; Bayesian methods; Cities and towns; Computer science; Decision making; Information analysis; Information processing; Neural networks; Numerical simulation; Open wireless architecture; Sun; Bayesian networks; Decision of weights; Interval data; Multi-attribute decision-making (MADM); TOPSIS;
Conference_Titel :
Advanced Computer Control, 2009. ICACC '09. International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-3330-8
DOI :
10.1109/ICACC.2009.41
