Assigning appropriate weight to different indexes is a key also a difficult problem to various flood disaster evaluation models. According to the characteristics of the present subjective and objective assigning weight methods, decision maker’s preferences is introduced into the differential evolution (DE) algorithm to filter out those individuals which dissatisfy the preferences, and the indexes’ weight vectors of flood samples can be obtained by optimizing the fuzzy clustering iterative model which considers the decision maker’s preferences. Furthermore, with the characteristic value matrix of the floods samples, the comprehensive evaluation value of each flood disaster is obtained. According to the comprehensive evaluation value of each flood disaster and the cluster matrix, the eigenvalue of each degree that is followed by identifying the degree of each row in the cluster matrix automatically, can be obtained. Finally, all the flood samples under different decision maker’s preferences are assessed and sorted based on the identified degree of each row and the comprehensive evaluation value of each flood disaster. Simulation test on two flood samples, namely in Sichuan occurred in 2013 and Xinjiang in 1996, reveals the results of flood rating in different decision maker’s preferences, and provides reference for water conservancy department on choosing preference type.