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For Round-Robin scheduling algorithm and genetic algorithm and simulated annealing algorithm in cloud resource scheduling having shortcomings, such as slow convergence speed, easy to premature and the imbalance of the resource load, the paper proposed the improved genetic algorithm combined with simulated annealing thought (Simulated Annealing Improved Genetic Algorithm:SAIGA). The improved algorithm gave a dual fitness function based on task average completion time and load balance and adaptive crossover mutation probability function. It allowed the algorithm in the annealing process to accept inferior solution with a certain probability to avoid prematurity phenomenon occurs. We regarded the virtual machine task allotment standard deviation as the basis of individual choice to realize the resource node load balancing. Simulation experiments showed that the improved algorithm is more superior on average task completion time, resource load balancing, and the convergence rate. It can rapidly find the optimal scheduling scheme and has good feasibility and practicability.