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Particle Swarm Optimization(PSO) algorithm has been wiedly used in many areas due to the advantages of simple realization and fast convergence.While it will trap in local minimum easily. To overcome the shortcoming, this paper proposes a hybrid algorithm PSO-SA by introducing the simulated annealing(SA) algorithm to the standard PSO and applies it to hybrid elevator group control system for optimizing scheduling. The hybrid algorithm integrates PSO's fast convergence and the advantage of jumping out of the local optimization in SA. Comparing the hybrid algorithm with the standard PSO and Artificial Immune(AI) under the same condition, shows that the hybrid algorithm can overcome this shortcoming of PSO effectively, demonstrates the feasibility and superiority of PSO-SA in optimizing scheduling. This paper adds the new scheduling algorithms for elevator group control system, and expands the application of PSO.