DocumentCode
593278
Title
Study on genetic algorithm and evolutionary programming
Author
Gao Wei
Author_Institution
Wuhan Polytech. Univ., Wuhan, China
fYear
2012
fDate
6-8 Dec. 2012
Firstpage
762
Lastpage
766
Abstract
Genetic algorithm and evolutionary programming are two generally used evolutionary algorithms. Due to the difference of their origin, there are a lot of differences between their biologic bases, algorithm operation and some other operational details. So, the performances of the two algorithms are different. In this paper, these differences are analyzed comprehensively by theory and revealed by simulation experiments. The results show that the performance of evolutionary programming is better than that of genetic algorithm and the evolutionary programming is more suitable for practical applications.
Keywords
evolutionary computation; algorithm operation; biologic bases; evolutionary algorithms; evolutionary programming; genetic algorithm; performance improvement; Biological information theory; Biological system modeling; Biomedical optical imaging; Programming; compairson study; evolutionary algorithm; evolutionary programming; genetic algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel Distributed and Grid Computing (PDGC), 2012 2nd IEEE International Conference on
Conference_Location
Solan
Print_ISBN
978-1-4673-2922-4
Type
conf
DOI
10.1109/PDGC.2012.6449918
Filename
6449918
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