DocumentCode
1638379
Title
Immunized Continuous Ant Colony Algorithm
Author
Wei, GAO
Author_Institution
Wuhan Polytech. Univ., Wuhan
fYear
2007
Firstpage
705
Lastpage
709
Abstract
Nowadays, to solve continuous optimization problem and extend the traditional ant colony algorithm, some continuous ant colony algorithms have been proposed. To improve the searching performance, the principles of evolutionary algorithm and immune algorithm have been combined with the typical continuous ant colony algorithm, and one new immunized continuous ant colony algorithm is proposed here. In this new algorithm, the ant individual is transformed by adaptive Cauchi mutation and thickness selection. To verify the new algorithm, the typical functions, such as Schaffer function and "needle-in-a-haystack" function, are all used. The results show that, the convergent speed and computing precision of new algorithm are all very good.
Keywords
artificial immune systems; evolutionary computation; Schaffer function; adaptive Cauchi mutation; continuous optimization problem; evolutionary algorithm; immune algorithm; immunized continuous ant colony algorithm; thickness selection; Ant colony optimization; Evolutionary computation; Genetic mutations; Continuous ant colony algorithm; Continuous optimization; Evolutionary algorithm; Immune algorithm; Immunized continuous ant colony algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference, 2007. CCC 2007. Chinese
Conference_Location
Hunan
Print_ISBN
978-7-81124-055-9
Electronic_ISBN
978-7-900719-22-5
Type
conf
DOI
10.1109/CHICC.2006.4346802
Filename
4346802
Link To Document