Title :
The new adaptive evolutionary programming
Author_Institution :
Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
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.
Keywords :
adaptive systems; evolutionary computation; learning (artificial intelligence); adaptive evolutionary programming; adaptive mutation operation; global optimization method; improved selection; learning efficiency; Adaptation model; Programming; Evolutionary programming; convergent speed; mutation operation;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580662
