In this paper, we assess the performances of Differential Evolution on real-world clustering problems. To improve our results, we introduce Progressive Differential Evolution, a small modification of Differential Evolution which aims at optimizing a small number of parameters (eg. one cluster) at the beginning, and incrementally increase the number of optimized parameters.