Fast immunized evolutionary programming

Evolutionary programming is a good global optimization method. By introducing the improved adaptive mutation operation and improved selection operation based on thickness adjustment of artificial immune system into traditional evolutionary programming, a fast immunized evolutionary programming is proposed in this paper. At last, this algorithm is verified by simulation experiment of typical optimization function. The results of the experiment show that, the proposed fast immunized evolutionary programming can improve not only the convergent speed of original algorithm but also the computation effect of original algorithm, and is a very good optimization method.