Task scheduling is an important part of multi-core processor technology. List-based scheduling algorithms are widely concerned because of their low complexity and high efficiency, but the singleness of the task priority list method makes the algorithm not enough to search the solution space, and it is easy to fall into the local optimal. Therefore, proposes an iterative list scheduling algorithm (TPIA) based on task perturbation. The algorithm selects the task disturbance factor to iterate the scheduling list according to a certain disturbance strategy, greedily selects the iterated list, and generates a better scheduling list sequence to obtain better scheduling results. The thesis validates the algorithm through examples and a limited set of random DAG graphs. The results show that the algorithm can effectively improve the scheduling solution, and the scheduling performance can be improved by an average of 16. 51%. It is suitable for processing large-scale and high-entry complex DAG graphs. When the total number of tasks is low and the communication overhead is high, the performance is reduced. The task graphs with an average task node number of less than 130 are grouped and tested to obtain the corresponding upper CCR and its change trend.