One of the most challenging issues in fuzzy systems design is generating suitable membership functions for fuzzy variables. This paper proposes a paradigm of applying an information theoretic model to generate fuzzy membership functions. After modeling fuzzy membership function by fuzzy partitions, a genetic algorithm based optimization technique is presented to find sub optimal fuzzy partitions. To generate fuzzy membership function based on fuzzy partitions, a heuristic criterion is also defined. Extensive numerical results and evaluation procedure are provided to demonstrate the effectiveness of the proposed paradigm.