The invention provides a cloud computing task scheduling method based on the improved NSGA-II and relates to the field of cloud computing. The method includes the steps that firstly, the number of meta tasks is input, and a task scheduling model is generated through a DAG chart; secondly, the number of virtual machines is input, the virtual machines of different specifications are generated randomly, and a cluster model is generated; thirdly, a cloud computing task scheduling problem is expressed as a multi-target solving problem relevant to time and cost, and the problem is solved with the combination of the improved NSGA-II. A new population is generated by the adoption of a similarity task sequence crossover operator and a displacement mutation operator in the population evolution process according to the features of task scheduling, meanwhile, a congestion distance self-adaptation operator is introduced in, it is ensured that the optimal border of the obtained time and cost is obtained, and cloud computing task scheduling is achieved. The searching capability for the optimal solution in the application of cloud computing task scheduling becomes stronger, the population diversity can be better kept, and the optimal solution set with the better distributivity is obtained.