Abstract: To solve dynamic optimization problems of chemical processes with numerical methods, a new algorithm,iterative genetic algorithm (IGA) was developed, of which the main idea was to iteratively call genetic operations and gradually approximate the optimal control profile.The first step of IGA was to discretize time interval and control region to make the continuous dynamic optimization problem a discrete problem.Genetic operations were then used to seek the best control profile of the discrete dynamic system.Lastly,region-reduction strategy and iteration were used to increases numerical accuracy and enhance robustness.IGA was shown by a case study to be convenient, feasible, and efficient.When applied to optimizing feed-rate of Lee-Ramirez bioreactor, IGA displayed advantage over general methods.The result by IGA was better than that in the reference.IGA approach could be regarded as a reliable and useful optimization tool when the gradients are not available.