Title :
Immunized Continuous Ant Colony Algorithm
Author_Institution :
Wuhan Polytech. Univ., Wuhan
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;
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
DOI :
10.1109/CHICC.2006.4346802