提出一种快速演化算法 (FEA) ,在演化过程中融合了梯度的随机模拟、免疫算子和模拟退火算法的思想 ,使得算法朝着优化的方向进行 ,在一定程度上避免了标准演化算法的演化时间过长和早熟问题。仿真结果表明 ,该算法具有精度高和收敛速度快的优点 A rapid evolution algorithm (FEA) is proposed in this paper. The idea of ​​gradient random simulation, immune operator and simulated annealing algorithm are integrated in the evolutionary process to make the algorithm proceed in the direction of optimization. To some extent, this method avoids the problem of standard evolutionary algorithm Evolution time is too long and precocity problems. Simulation results show that the proposed algorithm has the advantages of high precision and fast convergence