Abstract
In this paper, we discussed risk evaluation decision models combined cross-entropy and risk preference under interval type-2 fuzzy environment, in which all attribute values provided by expert take the form of interval type-2 fuzzy sets(IT2FSs). Firstly, some basic concepts and arithmetic average (AA) operator about IT2FSs are introduced. Then, we proposed the fuzzy factor, hesitant factor and interval factor to quantify the fuzziness, hesitancy and interval information of one IT2FS, respectively. An interval type-2 fuzzy cross-entropy has been initiated based on these three factors to measure the discrimination degree of uncertain information between two IT2FSs. Meanwhile, in order to reflect the decision maker's attitude towards risk, risk preference factor was put forward. Moreover, two programming models are built, which contain attribute weights are completely unknown and attribute weights are partly known under different risk preference. Finally, we utilize a simple example about liquidity risk evaluation for banks to illustrate the feasibility and effectiveness of the proposed method.
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