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In this paper, we consider the issue of fuzzy objective functions when outliers exist. The outlier set is defined as the complement of the data set. Following this concept, a specially designed fuzzy membership weighted objective function is proposed and the corresponding optimal membership is derived. Based on the proposed robust objective functions, algorithms for clustering are implemented. Artificially generated data are used for comparison.