DocumentCode
2247373
Title
The new adaptive evolutionary programming
Author
Fang, Liu
Author_Institution
Sch. of Electron. Inf. & Control Eng., Beijing Univ. of Technol., Beijing, China
Volume
5
fYear
2010
fDate
11-14 July 2010
Firstpage
2341
Lastpage
2344
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-6526-2
Type
conf
DOI
10.1109/ICMLC.2010.5580662
Filename
5580662
Link To Document