Abstract: A stochastic crossover particle swarm optimization algorithm is proposed by designing a stochastic cross-operator，which aims at the disadvantages of PSO such as the easily falling into local extremum point，slow convergence.In each iteration of this algorithm，the current particles and the optimal particle of the particle swarm make a stochastic crossover，and form new particles of good quality，which will substitute the former particles，so it advances the speed of convergence of the algorithm，and enhances the optimization capacity of the algorithm.The results illustrate this algorithm has higher optimization performance.