Abstract: Diverse forms of opposition are already existent virtually everywhere and utilizing opposite numbers to accelerate an optimization method is a new idea. In this study, Differential Evolution (DE) and opposition-based differential evolution using the current optimum (COODE) are compared for different jumping rates. Experiments on 58 widely used benchmark problems show that, the higher jumping rate leads to faster convergence to global optimum and smaller success rate for most problems.