Abstract
Evolutionary programming is a good global optimization method. By introduction the improved adaptive mutation operation and improved selection, the new adaptive evolutionary programming is proposed in this paper. This algorithm is verified by simulation experiment of typical optimization function. Comprehensive comparisons with other approach show that the proposed approach is superior over other in terms of learning efficiency and performance. The results of experiment show that, the proposed fast 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.
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