In the traditional virtual machine scheduling, we only focus on the current load, without fully considering the historical data in the virtual machine. As a result, we will suffer from load imbalance when scheduling the cloud computing resource. In order to solve that problem, this paper puts forward the algorithm of resource scheduling based on heuristic genetic algorithm, which can schedule the cloud computing resource while meeting the multi-objective planning. This algorithm fully considers various overheads and factors of virtual machine while providing service to users, so as to make the server, which provides cloud computing resource, achieve load balancing. By analyzing, researching and calculating current load and historical data, the writer induces the best scheduling scheme of cloud computer resource, which can meet the data constrains for the load variation and minimum dynamic migration overhead. Finally, by verifying the algorithm in a simulation experiment, the writer compares and measures the load of virtual machine by bringing in load change rate and two performance parameters of the average load distance. The experimental data shows that the proposed algorithm has very good global convergence and utilization rate of resources. It can solve the load imbalance and the large overheads of dynamic migration in the process of resource scheduling. Therefore, the algorithm is feasible and effective.