首先简要介绍了传统的遗传算法,然后分析了遗传算法的优点和不足。针对遗传算法容易产生早熟现象和局部寻优能力差的特点,通过引入改进的灾变操作和模拟退火算法跟遗传算法相结合,而增强了算法的全局收敛性,并且提高了算法的收敛速度。最后使用一个典型的遗传算法性能测试函数验证了改进算法对函数最优化的有效性,其性能明显优于传统的遗传算法和模拟退火算法。 First of all, we briefly introduce the traditional genetic algorithm, and then analyze the advantages and disadvantages of the genetic algorithm. Aiming at the characteristics that the genetic algorithm is prone to premature phenomenon and the local optimization ability is poor, the global convergence of the algorithm is enhanced and the convergence speed of the algorithm is improved by introducing improved catastrophe operation and simulated annealing algorithm combined with genetic algorithm. Finally, a typical genetic algorithm performance test function is used to verify the effectiveness of the improved algorithm for function optimization. Its performance is obviously better than the traditional genetic algorithm and simulated annealing algorithm.