Topsis method for hybrid multiple attribute decision making with 2-tuple linguistic information and its application to computer network security evaluation
Affiliations: Shanghai University of Electric Power, Shanghai, China
Note: [] Corresponding author. Yong-Bin Li, Shanghai University of Electric Power, Shanghai 200090, China. Tel.: +86 013371896856; Fax: +86 013371896856; E-mail: [email protected]
Abstract: With respect to the hybrid MADM problems for evaluating the computer network security, in which the attribute weights take the form of real numbers, and the attribute preference values take the form of real number, interval number, triangular fuzzy number and trapezoidal fuzzy number and linguistic variables, a new decision making analysis method for evaluating the computer network security is proposed. Firstly, real number, interval number, triangular fuzzy number and trapezoidal fuzzy number and linguistic variables are all transformed into 2-tuple linguistic variables. Then, according to the traditional ideas of technique for order preference by similarity to ideal solution (TOPSIS), the optimal alternative(s) is determined by calculating the shortest distance from the 2-tuple linguistic positive ideal solution (TLPIS) and on the other side the farthest distance of the 2-tuple linguistic negative ideal solution (TLNIS). The method has exact characteristic in linguistic information processing. It avoided information distortion and losing which occur formerly in the linguistic information processing. Finally, a numerical example for evaluating the computer network security is used to illustrate the use of the proposed method. The result shows the approach is simple, effective and easy to calculate.
