Solving consensus measure of ambiguous MPDM problems using vague sets - an application to of risk assessment

The traditional consensus-evaluation method determines the solution by fuzzy set, but it cannot treat the negative evidence for membership function. In this paper, we present a new method for consensus measure in the risk assessment process by relaxing many assumptions on existing hesitation situations. A new similarity measure of vague sets is introduced. A fuzzy synthetic evaluation method is employed to attain the consensus interval of the group via the agreement matrix for group decision making (GDM) problems. The proposed solution algorithm is presented and two consensus policies are given to consensus analysis of risk assessment guided by BS7799. The proposed method improves the soft consensus method proposed by Kacprzyk and Fedrizzi and analyzes the variation trend of group consensus using similarity measures of vague sets and consensus index. From numerical illustrations, the usefulness and efficiency of the proposed method has shown, particularly in a situation with vague and ill-defined data.