Abstract
Consensus measure is an important process for group decision-making. The traditional consensus-evaluation method determines the solution by fuzzy set and cannot treat the negative evidence for membership function. In this paper, we present a method for consensus measure in the risk assessment process by relaxing assumptions about the existing of hesitation situation. First, a new similarity measure of vague sets is introduced. Then, a fuzzy synthetic evaluation method is employed to attain the consensus interval of the group via the agreement matrix. Finally, a real example of risk assessment guided by BS7799 is given to demonstrate our method. The proposed method applies the soft consensus method proposed by Kacprzyk and Fedrizzi, analyzes the variation trend of group consensus using similarity measures of vague sets and consensus index. From numerical illustrations, the usefulness of the proposed method has shown, particularly in a situation with vague and ill-defined data.
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Lo, CC., Wang, P., Chao, KM. (2006). Solving Consensus Measure of Ambiguous GDM Problems Using Vague Sets – An Application of Risk Assessment. In: Shen, Wm., Chao, KM., Lin, Z., Barthès, JP.A., James, A. (eds) Computer Supported Cooperative Work in Design II. CSCWD 2005. Lecture Notes in Computer Science, vol 3865. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11686699_58
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DOI: https://doi.org/10.1007/11686699_58
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